Vehicle speed control using MRAC PID strategy for gradient disturbance rejection

Controlling vehicle speed is a challenging task,moreover when road gradient disturbance is taken into consideration.In this study,Model Reference Adaptive Control PID (MRAC PID) was proposed to handle the task. The study was conducted via simulation in MATLAB Simulink environment.Vehicle model used...

Full description

Saved in:
Bibliographic Details
Main Author: Abdul Kadir, Faizul Akmar
Format: Thesis
Language:English
English
Published: 2018
Subjects:
Online Access:http://eprints.utem.edu.my/id/eprint/23363/1/Vehicle%20Speed%20Control%20Using%20Mrac%20Pid%20Strategy%20For%20Gradient%20Disturbance%20Rejection.pdf
http://eprints.utem.edu.my/id/eprint/23363/2/Vehicle%20Speed%20Control%20Using%20Mrac%20Pid%20Strategy%20For%20Gradient%20Disturbance%20Rejection.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-utem-ep.23363
record_format uketd_dc
institution Universiti Teknikal Malaysia Melaka
collection UTeM Repository
language English
English
advisor Tamaldin, Noreffendy

topic T Technology (General)
T Technology (General)
spellingShingle T Technology (General)
T Technology (General)
Abdul Kadir, Faizul Akmar
Vehicle speed control using MRAC PID strategy for gradient disturbance rejection
description Controlling vehicle speed is a challenging task,moreover when road gradient disturbance is taken into consideration.In this study,Model Reference Adaptive Control PID (MRAC PID) was proposed to handle the task. The study was conducted via simulation in MATLAB Simulink environment.Vehicle model used was constructed by combining validated Vehicle Longitudinal Model (VLM) and Electronic Throttle Body model (ETB) where VLM act as plant and ETB as the actuator.MRAC PID was utilized as the plant controller whereas Fixed Gain PID (FG PID) controls the actuator.A unique self-induced data was used as the Reference Model for the proposed controller together with MIT Rule as the adjustment mechanism.The performance of MRAC PID was studied by subjecting the vehicle to a set of gradient disturbances ranging from 0° to 25° with 5° increment at a driven speed of 90 kph.The results were compared against Gain Scheduling PID (GS PID) and FG PID control strategies.Simulation results shows that the proposed controller outperform the other controllers in both transient and disturbance region.HILS with Throttle-in-the-Loop was conducted as the means of validating the simulation results.It was observed that the simulations and HILS results shows similar pattern thus conclude that the results are valid.Several HILS data were collected for Repeatability Analysis.The Coefficient of Variance (CV) obtained from the analysis indicates that the HILS has high repeatability and well conducted.For future works,it is recommended that the actual torque curve from dynamometer test is used for the vehicle model and the braking effect is considered as it may offer better result as well as exploring several new actuators for HILS.
format Thesis
qualification_name Doctor of Philosophy (PhD.)
qualification_level Doctorate
author Abdul Kadir, Faizul Akmar
author_facet Abdul Kadir, Faizul Akmar
author_sort Abdul Kadir, Faizul Akmar
title Vehicle speed control using MRAC PID strategy for gradient disturbance rejection
title_short Vehicle speed control using MRAC PID strategy for gradient disturbance rejection
title_full Vehicle speed control using MRAC PID strategy for gradient disturbance rejection
title_fullStr Vehicle speed control using MRAC PID strategy for gradient disturbance rejection
title_full_unstemmed Vehicle speed control using MRAC PID strategy for gradient disturbance rejection
title_sort vehicle speed control using mrac pid strategy for gradient disturbance rejection
granting_institution Universiti Teknikal Malaysia Melaka
granting_department Faculty Of Mechanical Engineering
publishDate 2018
url http://eprints.utem.edu.my/id/eprint/23363/1/Vehicle%20Speed%20Control%20Using%20Mrac%20Pid%20Strategy%20For%20Gradient%20Disturbance%20Rejection.pdf
http://eprints.utem.edu.my/id/eprint/23363/2/Vehicle%20Speed%20Control%20Using%20Mrac%20Pid%20Strategy%20For%20Gradient%20Disturbance%20Rejection.pdf
_version_ 1747834043491155968
spelling my-utem-ep.233632022-06-03T11:11:24Z Vehicle speed control using MRAC PID strategy for gradient disturbance rejection 2018 Abdul Kadir, Faizul Akmar T Technology (General) TL Motor vehicles. Aeronautics. Astronautics Controlling vehicle speed is a challenging task,moreover when road gradient disturbance is taken into consideration.In this study,Model Reference Adaptive Control PID (MRAC PID) was proposed to handle the task. The study was conducted via simulation in MATLAB Simulink environment.Vehicle model used was constructed by combining validated Vehicle Longitudinal Model (VLM) and Electronic Throttle Body model (ETB) where VLM act as plant and ETB as the actuator.MRAC PID was utilized as the plant controller whereas Fixed Gain PID (FG PID) controls the actuator.A unique self-induced data was used as the Reference Model for the proposed controller together with MIT Rule as the adjustment mechanism.The performance of MRAC PID was studied by subjecting the vehicle to a set of gradient disturbances ranging from 0° to 25° with 5° increment at a driven speed of 90 kph.The results were compared against Gain Scheduling PID (GS PID) and FG PID control strategies.Simulation results shows that the proposed controller outperform the other controllers in both transient and disturbance region.HILS with Throttle-in-the-Loop was conducted as the means of validating the simulation results.It was observed that the simulations and HILS results shows similar pattern thus conclude that the results are valid.Several HILS data were collected for Repeatability Analysis.The Coefficient of Variance (CV) obtained from the analysis indicates that the HILS has high repeatability and well conducted.For future works,it is recommended that the actual torque curve from dynamometer test is used for the vehicle model and the braking effect is considered as it may offer better result as well as exploring several new actuators for HILS. 2018 Thesis http://eprints.utem.edu.my/id/eprint/23363/ http://eprints.utem.edu.my/id/eprint/23363/1/Vehicle%20Speed%20Control%20Using%20Mrac%20Pid%20Strategy%20For%20Gradient%20Disturbance%20Rejection.pdf text en public http://eprints.utem.edu.my/id/eprint/23363/2/Vehicle%20Speed%20Control%20Using%20Mrac%20Pid%20Strategy%20For%20Gradient%20Disturbance%20Rejection.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=113086 phd doctoral Universiti Teknikal Malaysia Melaka Faculty Of Mechanical Engineering Tamaldin, Noreffendy 1. Abdelhameed, M. M., Abdelaziz, M., Elhady, N. E. & Hussein, A. M., 2014. Development of Integrated Brakes and Engine Traction Control System, 15th International Workshop on Research and Education in Mechatronics (REM), pp.1-5. 2. Ahmad, F., Mazlan, S., Zamzuri, H., Jamaluddin, H., Hudha, K. & Short, M., 2014. Modelling and Validation of the Vehicle Longitudinal Model. International Journal of Automotive and Mechanical Engineering, 10, pp.2042. 3. Ahmad, F., Shah, S. U. R., and Siddiqui, M. S., 2014. Optimization of an Internal Combustion Engine's Efficiency for Fuel Conservation & Green Environment, International Conference on Energy Systems and Policies (ICESP), 24-26 Nov. 2014. 4. Ahmed, M. S., 1994. Block Partial Derivative and Its Application to Neural-Net-Based Direct Model-Reference Adaptive Control. IEE Proceedings - Control Theory and Applications, 141 (5), pp.305-314. 5. Ahmed, S., and Akhtar, M., 2016. Gain Scheduling of Auxiliary Noise and Variable Step- Size for Online Acoustic Feedback Cancellation in Narrow-band Active Noise Control Systems. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 25 (2), pp.333-343 6. Al-Assadi, S., Breitinger, J. & Traver, M., 2006. Electronic Throttle Simulation Using Nonlinear Hammerstein Model. SAE Technical Paper 2006-01-0112. 7. Alagappan, A. V., Rao, K. V. N., and Kumar, R. K., 2015. A Comparison of Various Algorithms to Extract Magic Formula Tyre Model Coefficients for Vehicle Dynamics Simulations. Vehicle System Dynamics, 53, pp.154-178. 8. Alavi, S. M. S., Akbarzadeh, A., and Farughian, A., 2011. Auto-tuning Smith-Predictive Control of Three-Tanks System Based on Model Reference Adaptive System, The 2nd International Conference on Control, Instrumentation and Automation, 27-29 Dec. 2011. 9. Alonso, L., et al. 2010. Genetically Tuned Controller of an Adaptive Cruise Control for Urban Traffic Based On Ultrasounds. In Artificial Neural Networks (Diamantaras K., Duch W., Iliadis L.S.), pp.479-485. Berlin, Heidelberg: Springer. 10. Altmannshofer, S., Endisch, C., Martin, J., GerngroƒÀ, M., and Limbacher, R., 2016. Robust Estimation of Vehicle Longitudinal Dynamics Parameters, 2016 IEEE Intelligent Vehicles Symposium (IV), 19-22 June 2016. 11. Aparow, V. R., Hudha, K., Ahmad, F. & Jamaluddin, H., 2014. Model-In-The-Loop Simulation of Gap and Torque Tracking Control Using Electronic Wedge Brake Actuator. International Journal of Vehicle Safety, 7, pp.390-408. 12. Asere, H., Lei, C., and Jia, R., 2015. Cruise Control Design Using Fuzzy Logic Controller, 2015 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 9-12 Oct. 2015. 13. Astrom, K. J. & Canudas-De-Wit, C., 2008. Revisiting the Lugre Friction Model. IEEE Control Systems, 28, pp.101-114. 14. Astrom, K. J., and Hagglund, T., 2001. The Future of PID Control. Control Engineering Practice, 9, pp.1163-1175. 15. Astrom, K. J., and Hagllund, T., 1994. PID Controllers Theory, Design and Tuning, 2nd ed., USA: Instrument Society of America. 16. Atman, M. W. S., and Bambang, R. T., 2015. Design and Implementation of Gain- Scheduling Flight Control System on PC/104 Platform, International Conference on Electrical Engineering and Informatics (ICEEI), 10-11 Aug. 2015. 17. Bae, H. S., and Gerdes, J. C., 2003. Parameter Estimation and Command Modification for Longitudinal Control of Heavy Vehicles. California Partners for Advanced Transit and Highways (PATH). 18. Bae, H. S., Ruy, J., and Gerdes, J. C., 2001. Road Grade and Vehicle Parameter Estimation for Longitudinal Control Using GPS, Proceeding of IEEE Conference on Intelligent Transportation Systems, San Francisco, CA, USA. 19. Bai, R., and Tong, S., 2014. Adaptive Backstepping Sliding-Mode Control of the Electronic Throttle System in Modern Automobiles. Mathematical Problems in Engineering, pp.8-16. 20. Bakker, E., Pacejka, H., and Lidner, L., 1989. A New Tire Model with Application in Vehicle Dynamics Studies. SAE Paper No. 890087, pp.101-113. 21. Bakshi, N. A., and Ramachandran, R., 2016. Indirect Model Reference Adaptive Control of Quadrotor UAVS using Neural Networks, 10th International Conference on Intelligent Systems and Control (ISCO), 7-8 Jan. 2016. 22. Balazs, N., and Peter, G., 2016. The Relationship between the Traffic Flow and the Look- Ahead Cruise Control. IEEE Transactions on Intelligent Transportation Systems, 18 (5), pp.1154-1164. 23. Baotic, M., Vasak, M., Morari, M., and Peric, N., 2003. Hybrid System Theory Based Optimal Control of an Electronic Throttle, Proceedings of the American Control Conference, Denver, Colorado, 4-6 June 2003. 24. Bari., M., Petrovi., I., and Peri., N., 2005. Neural Network-Based Sliding Mode Control of Electronic Throttle. Engineering Applications of Artificial Intelligence, 18, pp.951-961. 25. Bartlett, J. W., and Frost, C., 2008. Reliability, Repeatability and Reproducibility: Analysis of Measurement Errors in Continuous Variables. Ultrasound in Obstetrics and Gynaecology, 31, pp.466-475. 26. Bauer, A., Gail, J., and Lorig, M., 2006. Impact of Cruise Control on Traffic Safety, Energy Consumption and Environmental Pollution. Impact Assessment of Road Safety Measures for Vehicles and Road Equipment (IMPROVER). 27. Benalie, N., Pananurak, W., Thanok, S., and Parnichkun, M., 2009. Improvement of Adaptive Cruise Control System Based on Speed Characteristics and Time Headway, IEEE/RSJ International Conference on Intelligent Robots and Systems, 10-15 Oct. 2009. 28. Benjamin, N., 2015. 18 Orang Mati di Jalan Raya Malaysia Setiap Hari - JPJ. Mstar, April 27. 29. Besselink, I. J. M., Schmeitz, A. J. C., and Pacejka, H. B., 2010. An Improved Magic Formula/Swift Tyre Model That Can Handle Inflation Pressure Changes. Vehicle System Dynamics, 48, pp.337-352. 30. Bishop, R., 2005. Intelligent Vehicle Technology and Trends, Artech House. 31. Blundell, M., and Harty, D., 2004. The Multibody Systems Approach to Vehicle Dynamics, Elsevier Butterworth-Heinemann. 32. Chabaan, R. C., 2009. Optimal Control and Gain Scheduling of Electrical Power Steering Systems, IEEE Vehicle Power and Propulsion Conference, 7-10 Sept. 2009. 33. Chang-Chieh, H., and Parks, P., 1973. Comparative Studies 0f Model Reference Adaptive Control Systems. IEEE Transactions on Automatic Control, 18, pp.419-428. 34. Chang, A. T. S., 1994. ADVANCE-F's Car-Following Policy on Vehicle Cruise and Automatic Speed Control, Proceedings of the Intelligent Vehicles '94 Symposium, 24-26 Oct. 1994. 35. Charfeddine, S., and Sbita, L., 2015. Performances Compared to The Sliding Mode and Gain Scheduling Control Methods of A CSTR Chemical Reactor, IEEE 12th International Multi-Conference on Systems, Signals & Devices (SSD15), 16-19 March 2015. 36. Chen, Y., Cheng, S., Wei, Y., and Wang, Y., 2016. Indirect Model Reference Adaptive Control for a Class of Linear Fractional Order Systems, American Control Conference (ACC), 6-8 July 2016. 37. Cletus, T., 2011. Dynamic Test Scheduling in Hardware-In-the-Loop Simulation of Commercial Vehicles. Masterfs Theses, University of Connecticut. 38. Conatser, R., Wagner, J., Ganta, S., and Walker, I., 2004. Diagnosis of Automotive Electronic Throttle Control Systems. Control Engineering Practice, 12, pp.23-30. 39. Crolla, D., and Mashadi, B., 2012. Vehicle Powertrain Systems, John Wiley & Sons Ltd. Leith, 40. Daniels, J., 2003. Driving Force: The Evolution of the Car Engine, Haynes Manual. 41. Deur, J., Pavkovi., D., Jansz, M., and Peri., N., 2003. Automatic Tuning of Electronic Throttle Control Strategy, The 11th Mediterranean Conference on Control and Automation, Rhodes Island, Greece. 42. Deur, J., Pavkovic, D., Peric, N., Jansz, M., and Hrovat, D., 2004. An Electronic Throttle Control Strategy Including Compensation of Friction and Limp-home Effects. IEEE Transactions on Industry Applications, 40, pp.821-834. 43. Dewantoro, G., and Feriyonika, F., 2011. Model Reference Adaptive Control of Cavity Pressure In Injection Molding During Filling and Packing Phases, 2nd International Conference on Instrumentation Control and Automation, 15-17 Nov. 2011. 44. El Majdoub, K., Giri, F., Ouadi, H., Dugard, L. & Chaoui, F. Z., 2012. Vehicle Longitudinal Motion Modeling for Nonlinear Control. Control Engineering Practice, 20, pp. 69-81. 45. Feng, W., Tong, Z., Yan-Jie, W., Lin, Y., and Bin, Z., 2006. Steady-State Optimization of Internal Combustion Engine for Hybrid Electric Vehicles, IEEE International Conference on Vehicular Electronics and Safety, 13-15 Dec. 2006. 46. Flood, A. E., 1999. A Comparison of Empirical Controller Tuning Methods for Third Order Inverse Response Processes. Suranaree Journal of Science and Technology, 6, pp.125-137. 47. Fujiwara, Y., and Adachi, S., 2003. Steering Assistance System for Driver Characteristics Using Gain Scheduling Control, European Control Conference (ECC), 1-4 Sept. 2003. 48. Gillispie, T. D., 1992. Fundamentals of Vehicle Dynamics, SAE International. 49. Goodwin, G. C., and Mayne, D. Q., 1987. A Parameter Estimation Perspective of Continuous Time Model Reference Adaptive Control. Automatica, 23, pp.57-70. 50. Hartman, H., Schautt, M., Pascussi, A. & Gombert, B., 2002. eBrake-The Mechatronic Wedge Brake. SAE Technical Paper 2002-01-2582. 51. He, S. Z., Tan, S., Xu, F. L., and Wang, P.Z., 1993. Fuzzy Self-Tuning of PID Controllers. Fuzzy Sets and Systems, 56, pp.37-46. 52. Holland, J. H., 1975. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, University of Michigan Press. 53. Hongyu, H., and Jun, L., 1999. Cruise Control Based on Gain Scheduling PI Diesel Engine Speed Controller, Proceedings of the IEEE International Vehicle Electronics Conference 1999 (IVEC '99), 9 Sept 1999. 54. Hu, C., Qi, Z., Ma, Q., and Zhou, X., 2016. Factional Order Model Reference Adaptive Control Based on Lyapunov Stability Theory, 35th Chinese Control Conference (CCC), 27-29 July 2016. 55. Hu, Y., Desheng, H., Yanan, F., and Chen, H., 2014. Electronic Throttle Controller Design Using A Triple-Step Nonlinear Method, 11th World Congress on Intelligent Control and Automation (WCICA), June 29 2014-July 4 2014. 56. Hudha, K., Zakaria, M. H., and Tamaldin, N., 2011. Hardware in the Loop Simulation of Active Front Wheel Steering Control for Yaw Disturbance Rejection. International Journal of Vehicle Safety, 5, pp.356-373. 57. Hunt, K. J., Johansen, T. A., Kalkkuhl, J., Fritz, H., and Gottsche, T., 2000. Speed Control Design for An Experimental Vehicle using A Generalized Gain Scheduling Approach. IEEE Transactions on Control Systems Technology, 8, pp.381-395. 58. Ioannou, P., and Xu, Z., 1993. Throttle Control for Vehicle Following, The First IEEE Regional Conference on Aerospace Control System, California, USA, 25-27 May 1993. 59. Jain, P., and Nigam, M. J., 2013. Real Time Control of Ball and Beam System with Model Reference Adaptive Control Strategy using MIT Rule, IEEE International Conference on Computational Intelligence and Computing Research, 26-28 Dec. 2013. 60. Jansri, A., Chatpoj, M., Phatrapornnant, T., and SOORAKSA, P., 2016. Fuzzy Strategy with Overshoot Suppressor for Electronic Throttle Control. 7th International Conference of Information and Communication Technology for Embedded Systems (IC-ICTES), 20-22 March 2016. 61. Jena, K. S. & Joseph, A. V., 2016. Dynamic Modelling and Control Design for a Vehicle in Its Longitudinal Motion. Indian Journal of Science and Technology. 9 (30). 62. Jiang, J., 1993a. Design and Implementation of An Optimal Gain Scheduling Controller For A Diesel Engine, Proceedings of IEEE International Conference on Control and Applications, 13-16 Sep 1993. 63. Jiang, J., 1993b. Generalized Gain Scheduling Control of a Diesel Engine based on H Optimization, American Control Conference, 2-4 June 1993. 64. Jiang, J., 1994. Optimal Gain Scheduling Controller for a Diesel Engine. IEEE Control Systems, 14, pp.42-48. 65. Jinying, A. H., Bo, B. M., and Haojing, C. W., 2009. Design of Vehicle Speed Controller Based on Immune Feed-back, IEEE International Conference on Fuzzy Systems, Jeju Island, Korea, 20-24 Aug. 2009. 66. Jiuhong, R., Mengyin, F., Yibin, L., and Jinying, H., 2005. Study on Throttle Control of Intelligent Vehicle Longitudinal Motion, IEEE International Conference on Vehicular Electronics and Safety, Xifan, Shaanfxi, China, 14-16 Oct. 2005. 67. Johanyak, Z. C. & Ailer, P. G., 2014. Particle Swarm Optimization Based Tuning for Fuzzy Cruise Control. IEEE 15th International Symposium on Computational Intelligence and Informatics (Cinti), 19-21 Nov. 2014. 68. JPM., n.d. Peningkatan Kemalangan Jalanraya [Online]. Available: http://pmr.penerangan.gov.my/index.php/component/content/article/445-kolumnis/10842- peningkatan-kemalangan-jalan-raya.html [Accessed 30 September 2016]. 69. Kadir, F. A. A., Tamaldin, N., Ayob, M. R., Abdullah, M. A., Hudha, K., and Yamin, A. K. M., 2014. Vehicle Speed Control Using Gain Scheduling PID with Experimental Throttle-in-the-Loop. International Review on Modelling and Simulations (I.RE.MO.S.), 7 (4), pp.682-693. 70. Kahveci, N. E., and Ioannou, P. A., 2010. Cruise Control with Adaptation and Wheel Torque Constraints for Improved Fuel Economy, IEEE Intelligent Vehicles Symposium, San Diego, CA, USA, 21-24 June 2010. 71. Kangwanrat, S., Tipsuwannaporn, V., and Numsomran, A., 2010. Design of PI Controller using MRAC Techniques for Coupled-Tanks Process, International Conference on Control Automation and Systems (ICCAS), 27-30 Oct. 2010. 72. Khodayari, A., Ghaffari, A., Ameli, S., and Flahatgar, J., 2010. A Historical Review on Lateral and Longitudinal Control of Autonomous Vehicle Motions, 2nd International Conference on Mechanical and Electrical Technology (ICMET), 10-12 Sept. 2010. 73. Kimseng, K., Hoit, M., Tiwari, N., and Pecht, M., 1999. Physics-Of-Failure Assessment of a Cruise Control Module. Microelectronics Reliability, 39, pp.1423-1444. 74. Kochummen, S. A., Jaffar, N. E., and Nasar, A., 2015. Model Reference Adaptive Controller Designs of Steam Turbine Speed Based on MIT Rule, International Conference on Control Communication & Computing India (ICCC), 19-21 Nov. 2015. 75. Kovacic, Z., and Bogdan, S., 2005. Fuzzy Controller Design: Theory and Applications, Taylor & Francis. 76. Krishnaswamy, P. R., Chan, B. E. M., and Rangaiah, G. P., 1987. Closed-Loop Tuning of Process Control Systems. Chemical Engineering Science, 42, pp.2173-2182. 77. Kumada, T., Chen, G., and Takami, I., 2014. Gain Scheduling Control for Magnetic Levitation Device Using Redundant Descriptor Representation, 4th Australian Control Conference (AUCC), 17-18 Nov. 2014. 78. Kurfess, T. R., 2007. Getting In Tune with Ziegler-Nichols [Online]. Available: http://www.controleng.com/single-article/getting-in-tune-with-zieglernichols/ 909066bf057ea926b1b20d99905438fd.html [Accessed 5 December 2016]. 79. Labertaux, K., Caminiti, L., Caveney, D., and Hada, H., 2006. Pervasive Vehicular Networks for Safety. IEEE Pervasive Computing, 5, pp.60-62. 80. Lee, G. D., Kim, S. W., and Park, T. J., 2001. Premise-Part Adaptation Laws for Adaptive Fuzzy Control and Its Application to Vehicle Speed Control, Proceedings of the 40th IEEE Conference on Decision and Control, 2-4 Dec. 2001. 81. Lee, J., and Cho, W., 1990. An Improved Technique for PID Controller Tuning from Closed Loop Tests. AIChE Journal, 36. 82. Leith, D. J. & Leithead, W., 1998. Survey of Gain-Scheduling Analysis & Design. International Journal of Control, 73 (11), pp.1001-1025. 83. Lelic, M., and Gajic, Z., 2001. Adaptive Control System Techniques. In: Intelligent Vehicle Technologies, Oxford: Butterworth-Heinemann. 84. Lhachemi, H., Saussie, D., and Zhu, G., 2016. Gain-Scheduling Control Design in The Presence of Hidden Coupling Terms via Eigenstructure Assignment: Application to a Pitch-Axis Missile Autopilot, American Control Conference (ACC), 6-8 July 2016. 85. Lheureux, F., Saad, F., Pianelli, C., Abric, J.C., and Roland, J., 2006. Behavioural Changes Due To Long Term Use of Speed Limiter and Cruise Control. AIDE project (Adaptive Integrated Driver-vehicle Interface), 1, pp.39-64. 86. Li, S., Yang, L., Gao, Z., and Li, K., 2016. Optimal Guaranteed Cost Cruise Control for High-Speed Train Movement. IEEE Transactions on Intelligent Transportation Systems, 17, pp.2879-2887. 87. Lin, G., and Liu, G., 2010. Tuning PID Controller using Adaptive Genetic Algorithms, 5th International Conference on Computer Science & Education, 24-27 Aug. 2010. 88. Liu, Y. F., Li, J., Zhang, Z. M., Hu, X. H., and Zhang, W. J., 2015. Experimental Comparison of Five Friction Models on the Same Test-Bed of the Micro Stick-Slip Motion System. Mechanical Sciences, 6, pp.15-28. 89. Ma, Q., Shao, L., and Yurkovich, S., 2005. Diagnostics for Automotive Electronic Throttle Body Systems, Proceedings of the American Control Conference, Portland, OR, USA, 8- 10 June 2005. 90. Maji, P., Patra, S. K., and Mahapatra, K., 2014. Implementation of FPGA Based Fuzzy PI Approximate Control for Automatic Cruise Control System, International Conference on Circuits, Communication, Control and Computing (I4C), 21-22 Nov. 2014. 91. Mark, V., Schleicher, S., and Gelau, C., 2011. The Influence of Cruise Control and Adaptive Cruise Control on Driving Behaviour . A Driving Simulator Study. Accident Analysis & Prevention, 43, pp.1134-1139. 92. Markucic, D., 2006. How to Determine Repeatability and Reproducibility (R&R). 3rd European-American Workshop on NDE Reliability. 93. Martin Bland, J., and Altman, D., 1986. Statistical Methods for Assessing Agreement between Two Methods of Clinical Measurement. The Lancet, 327, pp.307-310. 94. Mathworks. n.d. Solvers [Online]. Available: https://www.mathworks.com/help/simulink/ug/choosing-asolver. html?requestedDomain=www.mathworks.com [Accessed 16 December 2016]. 95. Mercorelli, P., 2009. Robust Feedback Linearization using an Adaptive PD Regulator for a Sensorless Control of a Throttle Valve. Mechatronics, 19, pp.1334-1345. 96. Ming, Q., 1997. Sliding Mode Controller Design for ABS System. Masterfs Theses, Virginia Polytechnic Institute and State University. 97. Mitchell, M., 1998. An Introduction to Genetic Algorithms. Cambridge, MA, USA: MIT Press. 98. Mohammed, N. F., Ma, X., and Song, E., 2013. Tuning of PID Controller for Diesel Engines using Genetic Algorithm, IEEE International Conference on Mechatronics and Automation, 4-7 Aug. 2013. 99. Mohammed, N. F., Song, E., Ma, X., and Hayat, Q., 2014. Tuning of PID Controller of Synchronous Generators using Genetic Algorithm, IEEE International Conference on Mechatronics and Automation, 3-6 Aug. 2014. 100. Morand, A., Moreau, X., Melchior, P., Moze, M., and Guillemard, F., 2016. CRONE Cruise Control System. IEEE Transactions on Vehicular Technology, 65, pp.15-28. 101. Morlock, M. B., Burkhardt, M., and Seifried, R., 2015. Friction Compensation, Gain Scheduling and Curvature Control for A Flexible Parallel Kinematics Robot, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Sept. 28 2015-Oct. 2 2015. 102. Naeem, H. M. Y., and Mahmood, A., 2016. Autonomous Cruise Control of Car Using LQR and H2 Control Algorithm, International Conference on Intelligent Systems Engineering (ICISE), 15-17 Jan. 2016. 103. Nahapetian, N., Motlagh, M. R. J., and Analoui, M., 2009. PID Gain Tuning Using Genetic Algorithms and Fuzzy Logic for Robot Manipulator Control, International Conference on Advanced Computer Control, 22-24 Jan. 2009. 104. Nouveliere, L., and Mamm, S. I., 2007. Experimental Vehicle Longitudinal Control using A Second Order Sliding Mode Technique. Control Engineering Practise, 15, pp.943-954. 105. O'Dwyer, A., 2003. Handbook of PI and PID Controller Tuning Rules, London: Imperial College Press. 106. Oda, K., Takeuchi, H., Tsujii, M., and Ohba, M., 1991. Practical Estimator for Self-Tuning Automotive Cruise Control, American Control Conference, Boston, MA, USA, 26-28 June 1991. 107. Ogata, K., 2001. Modern Control Engineering, New Jersey: Prentice Hall. 108. Olsen, B. J., Shaw, S. W., and Stepan, G., 2003. Nonlinear Dynamics of Vehicle Traction. Vehicle System Dynamics, 40, pp.377-399. 109. Oreskes, N., Shrader-Frechette, K. & Belitz, K., n.d. Verification, Validation and Confirmation of Numeral Models in the Earth Sciences. Science, 263, pp.641-646. 110. Orsag, M., Korpela, C., Bogdan, S., and Oh, P., 2013. Lyapunov Based Model Reference Adaptive Control for Aerial Manipulation, International Conference on Unmanned Aircraft Systems (ICUAS), 28-31 May 2013. 111. Osman, K., Rahmat, M. F., and Ahmad, M. A., 2009. Modelling and Controller Design for a Cruise Control System, IEEE 5th International Colloquium on Signal Processing & Its Applications, Kuala Lumpur, Malaysia, 6-8 March 2009. 112. Osusky, J., and Vesely, V., 2016. Engine Speed Control using Gain Scheduling Method, Cybernetics & Informatics (K&I), 2-5 Feb. 2016. 113. Overington, S., and Rajakaruna, S., 2014. A Novel Model of Internal Combustion Engine for High Efficiency Operation of Hybrid Electric Vehicles and Power Systems, Australasian Universities Power Engineering Conference (AUPEC), Sept. 28 2014-Oct. 1 2014. 114. Overington, S., and Rajakaruna, S., 2015. High-Efficiency Control of Internal Combustion Engines in Blended Charge Depletion/Charge Sustenance Strategies for Plug-In Hybrid Electric Vehicles. IEEE Transactions on Vehicular Technology, 64, pp.48-61. 115. Ozguner, U., Sulgi, H., and Yaodong, P., 2001. Discrete-Time Sliding Mode Control of Electronic Throttle Valve, Proceedings of the 40th IEEE Conference on Decision and Control, 4-7 Dec. 2001. 116. P.Srinivas, Lakshmi, K. V., and Kumar, V. N., 2014. A Comparison of PID Controller Tuning Methods for Three Tank Level Process. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 3. 117. Pacejka, H. B., 2002. Tyre and Vehicle Dynamics, Butterworth-Heinemann. 118. Pacejka, H. B., and Bakker, E., 1992. The Magic Formula Tyre Model. Vehicle System Dynamics, 21, pp.1-18. 119. Pacejka, H. B., and Besselink, I. J. M., 1997. Magic Formula Tyre Model with Transient Properties. Vehicle System Dynamics, 27, pp.234-249. 120. Palella, N., Colombo, L., Pisoni, F., Avellone, G., and Philippe, J., 2016. Sensor Fusion for Land Vehicle Slope Estimation, DGON Intertial Sensors and Systems (ISS), 20-21 Sept. 2016. 121. Pan, Y., Ozguner, U., and Dagci, O. H., 2008. Variable-Structure Control of Electronic Throttle Valve. IEEE Transactions on Industrial Electronics, 55, pp.3899-3907. 122. Parekar, N. N., Kadu, C. B., and Parvat, B. J., 2015. Modified MRAC for Controlling Water Level of Boiler Syste, International Conference on Computational Intelligence and Communication Networks (CICN), 12-14 Dec. 2015. 123. Pavkovic, D., Deur, J., Jansz, M., and Peric, N., 2003. Self-Tuning Control of an Electronic Throttle, Proceedings of 2003 IEEE Conference on Control Applications (CCA), 23-25 June 2003. 124. Pavkovi., D., Deur, J., Jansz, M., and Peri., N., 2006. Adaptive Control of Automotive Electronic Throttle. Control Engineering Practice, 14, pp.121-136. 125. Pereira, M., Bruyas, M. P., Kaufmann, C., Britschgi, V., Gil, J. L. D., and Zaoral, A., 2013. Reported Use of Speed Control Systems: Cruise Control and Speed Limiter. IET Intelligent Transport Systems, 7, pp.425-431. 126. Qiu, C., 2014. A Design of Automobile Cruise Control System Based on Fuzzy PID, International Conference on Information Science, Electronics and Electrical Engineering (ISEEE), 26-28 April 2014. 127. Raffin, A., Taragna, M. & Giorelli, M., 2017. Adaptive Longitudinal Control of an Autonomous Vehicle with an Approximate Knowledge of Its Parameters. 11th International Workshop on Robot Motion and Control (Romoco). 128. Rafizadeh, M., and Gahrabaghi, H., 2002. A Gain-Scheduling PI Controller for the Reactor Temperature of Batch Polymerization of Methyl Methacrylate, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301), 8-10 May 2002. 129. Rao, M. P. R. V., and Hassan, H. A., 2004. New Adaptive Laws for Model Reference Adaptive Control Using A Non-Quadratic Lyapunov Function, Proceedings of the 12th IEEE Mediterranean Electrotechnical Conference (IEEE Cat. No.04CH37521), 12-15 May 2004. 130. Ravi, V. R., Thyagarajan, T., and Priyadharshni, S. Y., 2012. Gain Scheduling Adaptive Model Predictive Controller for Two Conical Tank Interacting Level System, Third International Conference on Computing Communication & Networking Technologies (ICCCNT), 26-28 July 2012. 131. Razmara, M., Bidarvatan, M., Shahbakhti, M., and Robinett, R. D., 2016. Novel Exergy- Wise Predictive Control of Internal Combustion Engines, American Control Conference (ACC), 6-8 July 2016. 132. Regan, M., and Young, K., 2007. Use of Manual Speed Alerting and Cruise Control Devices by Car Drivers. Safety Science, 45 (4), pp.473-485. 133. Rehm, T., and Schmidt, P., 1995. Intelligent Model Reference Adaptive Control Applied to Motion Control, Conference Record of the 1995 IEEE Industry Applications Conference Thirtieth IAS Annual Meeting, 8-12 Oct 1995. 134. Reinholz, B. A., and Seethaler, R. J., 2016. Experimental Validation of a Cogging-Torque- Assisted Valve Actuation System for Internal Combustion Engines, IEEE/ASME Transactions on Mechatronics, 21, pp.453-459. 135. Rill, G., 2007. Wheel Dynamics. In: Proceedings of the XII International Symposium on Dynamic Problems of Mechanics (DINAME 2007), Ilhabela, SP, Brazil. 136. Rossi, C., Tilli, A., and Tonielli, A., 2000. Robust Control of a Throttle Body for Drive by Wire Operation of Automotive Engines. IEEE Transactions on Control Systems Technology, 8, pp.993-1002. 137. Sahlholm, P., and Johansson, K. H., 2010. Road Grade Estimation for Look-ahead Vehicle Control using Multiple Measurement Runs. Control Engineering Practice, 18, pp.1328- 1341. 138. Sahlholm, P. and Johansson, K. H., 2010. Segmented Road Grade Estimation for Fuel Efficient Heavy Duty Vehicles, 49th IEEE Conference on Decision and Control (CDC), 15-17 Dec. 2010. 139. Sahraeian, A., Shahbakhti, M., Aslani, A. R., Jazayeri, S. A., Azadi, S. & Shamekhi, A. H., 2004. Longitudinal Vehicle Dynamics Modeling on The Basis of Engine Modeling. SAE Technical Paper 2004-01-1620. 140. Sajadi-Alamdari, S. A., Voos, H., and Darouach, M., 2016. Nonlinear Model Predictive Extended Eco-Cruise Control for Battery Electric Vehicles, 24th Mediterranean Conference on Control and Automation (MED), 21-24 June 2016. 141. Satar, M. I., Hudha, K., Mat, W. A. W., Othman, R. N. I. R., Murrad, M., Aparow, V. R. & 142. Salleh, M. S., 2015. Modelling and Verification of 5 Degree of Freedom Vehicle Longitudinal Model. 10th Asian Control Conference (Ascc), 2015. 143. Saxena, P., Gaur, P., and Yadav, A. K., 2016. A Comparative Analysis between MRAC and FMRAC for an Unstable System, 3rd International Conference on Computing for Sustainable Global Development (INDIACom), 16-18 March 2016. 144. Scattolini, R., Siviero, C., Mazzucco, M., Ricci, S., Poggio, L.L, and Rossi, C., 1997. Modelling and Identification of an Electromechanical Internal Combustion Engine Throttle Body. Control Engineering Practice, 5, pp.1253-1259. 145. Schuette, H., and Waeltermann, P., 2005. Hardware-in-the-Loop Testing of Vehicle Dynamics Controller . A Technical Survey. SAE Technical Paper 2005-01-1660. 146. Seborg, D. E., Edgar, T. F., and Mellichamp, D. A., 1989. Process Dynamics and Control, John Wiley & Sons. 147. Sei-Bum, C., 1994. Vehicle Longitudinal Control Test. University of California, Berkeley. 148. Seungkyu, O., Hyoungsoo, K., and Jinhee, J., 2009. Proposals For Improvement of AFS System using HIL & SIL Simulation, ICCAS-SICE, Fukuoka International Congress Centre, Japan, 18-21 Aug. 2009. 149. Shahrokhi, M., and Zomorrodi, A., n.d. Comparison of PID Controller Tuning Methods [Online]. Available: http://www.personal.psu.edu/users/a/u/auz107/Publicationsfiles/ Zomorrodi-Shahrokhi-PID-Tunning-Comparison.pdf [Accessed 5 Dicember 2016]. 150. Shakouri, P., Ordys, A., Askari, M., and Laila, D. S., 2010. Longitudinal Vehicle Dynamics using Simulink/Matlab. UKCC International Conference on Control 2010, 7-10 Sept. 2010. 151. Shakouri, P., Ordys, A., Darnell, P. & Kavanagh, P., 2013. Fuel Efficiency by Coasting in the Vehicle. International Journal of Vehicular Technology, pp.14. 152. Shaout, A., and Jarrah, M. A., 1997. Cruise Control Technology Review. Computers & Electrical Engineering, 23, pp.259-271. 153. Sharp, R., and Bettella, M., 2003. Shear Force and Moment Descriptions by Normalisation of Parameters and the "Magic Formulah. Journal of Vehicle System Dynamics, 39, pp.27-56 154. Shinskey, F. G., 1996. Process Control Systems -Application, Design and Tuning, New York: McGraw-Hill Inc. 155. Shinskey, F. G., 2000. Optimization of the Charge Regulation. Chemical Engineering Applications of Artificial Intelligence. 156. Shiriaev, A., Robertsson, A. & Johansson, R., 2003. Friction Compensation For Passive Systems Based on The Lugre Model1. International Federation of Automatic Control (IFAC) Proceedings, 36 (2), pp.159-164. 157. Short, M., and Pont, M. J., 2005. Hardware in the Loop Simulation of Embedded Automotive Control System, Proceedings of IEEE Intelligent Transportation Systems, 13- 15 Sept. 2005. 158. Short, M., Pont, M. J., and Huang, Q., 2004. Simulation of Vehicle Longitudinal Dynamics, Embedded System Laboratory, University of Leicester. 159. Smith, C. A., and Copripio, A. B., 1985. Principles and Practice of Automatic Process Control, John Wiley & Sons. 160. Smuts, J. F., 2011. Cohen-Coon Tuning Rules [Online]. Available: http://blog.opticontrols.com/archives/383 [Accessed 6 December 2016]. 161. Sun, Y., He, D., Song, X., and Zhang, L., 2016. Multi-Performance Predictive Cruise Control of Connected Vehicles on Urban Roads, 35th Chinese Control Conference (CCC), 27-29 July 2016. 162. Svendenius, J., 2007. Tire Modelling and Friction Estimation. PhD Theses, Lund University. 163. Syed, F. U., Kuang, M. L., Smith, M., Okubo, S., and Ying, H., 2009. Fuzzy Gain- Scheduling Proportional-Integral Control for Improving Engine Power and Speed Behaviour in a Hybrid Electric Vehicle. IEEE Transactions on Vehicular Technology, 58, pp.69-84. 164. Tae-Hoon, K., and Byoung-Kuk, L., 2016. HILS-Based Analysis of Characteristics and Performance of Internal Combustion Engine Vehicles with Varying Battery Types, IEEE Transportation Electrification Conference and Expo, Asia-Pacific (ITEC Asia-Pacific), 1-4 June 2016. 165. Tahersima, H., Saleh, M., Mesgarisohani, A., and Tahersima, M., 2013. Design of Stable Model Reference Adaptive System via Lyapunov Rule for Control of a Chemical Reactor, Australian Control Conference, 4-5 Nov. 2013. 166. Takinami, A., and Takeuchi, Y., 2004. Model Gain Scheduling and Reporting for Ethylene Plant On-Line Optimizer, Proceedings of the 2004 IEEE International Conference on Control Applications, 2-4 Sept. 2004. 167. Tan, P., 2006. Waja Campro vs Waja 4G18 [Online]. Available: http://paultan.org/2006/01/13/waja-campro-vs-waja-4g18/ [Accessed 30 September 2016]. Thomasson, A. & Eriksson, L., 2011. Model-Based Throttle Control using Static Compensators and Pole Placement. Oil Gas Sci. Technol. . Rev. IFP Energies Nouvelles, 66, pp.717-727. 168. Tzafestas, S., and Papanikolopoulos, N. P., 1990. Incremental Fuzzy Expert PID Control. IEEE Transactions on Industrial Electronics, 37, pp.365-371. 169. Van Oosten, J. J. M., and Bakker, E., 1992. Determination of Magic Tyre Model Parameters. Vehicle System Dynamics, 21, pp.19-29. 170. Vedam, N., Diaz-Rodriguez, I., and Bhattacharyya, S. P., 2014. A Novel Approach to The Design of Controllers in An Automotive Cruise-Control System, IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society, Oct. 29 2014-Nov. 1 2014. 171. Vesely, V., and Ilka, A., 2013. Gain-Scheduled PID Controller Design. Journal of Process Control, 23, pp.1141-1148. 172. Visioli, A., 1999. Fuzzy Logic Based Set-Point Weight Tuning of PID Controllers. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 29, pp.587-592. 173. Visioli, A., 2001. Tuning Of PID Controllers with Fuzzy Logic. IEE Proceedings - Control Theory and Applications, 148, pp.1-8. 174. Wang, C. H., and Huang, D. Y., 2013. A New Intelligent Fuzzy Controller for Nonlinear Hysteretic Electronic Throttle in Modern Intelligent Automobiles. IEEE Transactions on Industrial Electronics, 60, pp.2332-2345. 175. Wang, J., Zhang, G., Wang, R., and Schnelle, S. C., 2016. A Gain-Scheduling Driver Assistance Trajectory Following an Algorithm Considering Different Driver Steering Characteristics. IEEE Transactions on Intelligent Transportation Systems, pp.1-12. 176. Wang, W., 1992. Modelling Scheme for Vehicle Longitudinal Control. Proceedings of the 31st IEEE Conference on Decision and Control, Tucson, AZ, USA. 177. Weikang, Q., Li, W., Lingjun, X., and Yifang, Z., 2008. Practical Solution for Automotive Electronic Throttle Control Based on FPGA, 9th International Conference on Signal Processing, Beijing, China, 26-29 Oct. 2008. 178. White, A., Choi, J., and Zhu, G., 2011. Dynamic Gain-Scheduling Controller Design for Port-Fuel-Injection Processes. Proceedings of the 2011 American Control Conference, June 29 2011-July 1 2011. 179. WHO., n.d. Road Traffic Injuries [Online]. Available: http://www.who.int/mediacentre/factsheets/fs358/en/ [Accessed 30 September 2016]. 180. Witt, C. C. D., Kolmanovsky, I., and Sun, J., 2001. Adaptive Pulse Control of Electronic Throttle, American Control Conference, 2001. 181. Yadav, A. K., Gaur, P., and Tripathi, S., Design and Control Of An Intelligent Electronic Throttle Control System, International Conference on Energy Economics and Environment (ICEEE), 27-28 March 2015. 182. Yang, Z., Hiroshi, H., and Nobuo, K., 2010. Quick Response of Electronic Throttle Control by Expanding SMC, 2nd International Conference on Advanced Computer Control (ICACC), 27-29 March 2010. 183. Youney, J., 2007. A Comparison and Evaluation of Common PID Tuning Methods. Masterfs Theses, University of Central Florida. 184. Yufka, A., and Yacizi, A., 2010. An Intelligent PID Tuning Method for an Autonomous Mobile Robot. UVW'10 International Workshop on Unmanned Vehicles, Istanbul, Turkey. 185. Yuwata, M., and Seborg, D. E., 1982. A new Method for Online Controller Tuning. AIChE Journal, 35. 186. Zady, M. F., 2016. Mean, Standard Deviation, and Coefficient Of Variation [Online]. Available: https://www.westgard.com/lesson34.htm#6 [Accessed 11 December 2016]. 187. Zhang, B. S., Leigh, I., and Leigh, J. R., 1995. Learning Control Based on Pattern Recognition Applied to Vehicle Cruise Control Systems, Proceedings of the 1995 American Control Conference, 21-23 Jun 1995. 188. Zhao, Z. Y., Tomizuka, M., and Isaka, S., 1992. Fuzzy Gain Scheduling of PID Controllers, The First IEEE Conference on Control Applications, 13-16 Sep 1992. 189. Zhen-Yu, Z., Tomizuka, M., and Isaka, S., 1993. Fuzzy Gain Scheduling of PID Controllers. IEEE Transactions on Systems, Man, and Cybernetics, 23, pp.1392-1398. 190. Ziegler, J. G., and Nichols, N. B., 1942. Optimum Settings for Automatic Controllers. ASME Transactions, 64, pp.759-768. 191. Zimmer, D. & Otter, M., 2010. Real-Time Models for Wheels and Tyres in an Object- Oriented Modelling Framework. Vehicle System Dynamics, 48, pp.189-216. 192. Zoroofi, S., 2008. Modelling and Simulation of Vehicular Power Systems. Master Theses, Chalmers University of Technology.