Design of a Taguchi-GRA optimized PID and adaptive PID controllers for speed control of DC motor

DC motors have wide acceptance in industries due to their high efficiency, low costs, and flexibility. The paper presents the unique design concept of a multi-objective optimized proportional-integral-derivative (PID) controller and Model Reference Adaptive Control (MRAC) based controllers for effective speed control of the DC motor system. The study aims to optimize PID parameters for speed control of a DC motor, emphasizing minimizing both settling time (Ts )and % overshoot (% OS) of the closed-loop response. The PID controller is designed using the Ziegler Nichols (ZN) method primarily subjected to Taguchi-grey relational analysis to handle multiple quality characteristics. Here, the Taguchi L9 orthogonal array is defined to find the process parameters that affect Ts and % OS. The analysis of variance shows that the most significant factor affecting Ts and % OS is the derivative gain term. The result also demonstrates that the proposed Taguchi- GRA optimized controller reduces Ts and % OS drastically compared to the ZN-tuned PID controller. This study also uses MRAC schemes using the MIT rule, Lyapunov rule, and a modified MIT rule. The DC motor speed tracking performance is analyzed by varying the adaptation gain and reference signal amplitude. The results also revealed that the proposed MRAC schemes provide desired closed-loop performance in real-time in the presence of disturbance and varying plant parameters. The study provides additional insights into using a modified MIT rule and the Lyapunov rule in protecting the response from signal amplitude dependence and the assurance of a stable adaptive controller, respectively