Intelligent PID controller for PIP (Point-to-Point) motion control systems - Wali Ahmad (a) Myo Min Htut (Kulliyyah of Engineering, International Islamic University Malaysia, 2009)
Point to Point (PTP) motion control systems play an important role in industrial engineering applications such as advanced manufacturing systems, semiconductor manufacturing, and robotics systems. Until now, proportional-integral-derivative (PID) controllers are still the most popular controller used in industrial control systems including PTP motion control systems due to their simplicity and also satisfactory performances. However, since the PID controller is developed based on the linear control theory, the controller gives inconsistent performance for different conditions due to system nonlinearities. In order to overcome this problem, Neuraltuned PID controller using Extended Minimal Resource Allocation Network (EMRAN) algorithm, and Fuzzy-tuned PID controller are proposed, and comparative analysis of their performance is carried out. By applying the aforementioned methods, the PID controller can learn, adapt and change its parameters based on the condition of the controlled-object in real-time. The effectiveness of the proposed methods is evaluated experimentally in real time on an experimental rotary motion control system. The experimental results show that the proposed systems perform better than classical PID controller in terms of not only positioning performance but also robustness to inertia variations.