Mohamed Kmich, Hicham Karmouni, and Mhamed Sayyouri
Controller PID, corona virus search optimiser, metaheuristic algorithms, wheeled mobile robot.
Proportional-Integral-Derivative controllers are widely used in process industries for their simplicity and reliability. Current research focuses on optimising PID controller gain parameters to reduce overshoot and system settling time. These controllers manage dynamic systems such as mobile robots, which are non-linear and time-varying. In this context, applying heuristics and metaheuristics to these robots aims to make them autonomous and intelligent. The main objective of this work is to optimally adjust the gain parameters of the PID controller by reducing the transient response criteria to regulate the speed of the DC motor integrated into a wheeled mobile robot to control it more effectively. To this end, we propose using the Corona Virus search optimiser (CVSO) metaheuristic to adjust the speed of the permanent magnet DC motor of the mobile robot by optimising the gains of the PID controller. This approach improves the performance of the wheeled mobile robot under consideration. The simulation results prove the effectiveness of the proposed control method (CVSO-PID), with a rise time of tr = 0.1000 s, a stabilisation time of ts = 0.8000 s, no peak, and no overshoot. These results indicate that the gain control of the CVSO-PID controller outperforms that obtained by other metaheuristics such as the Arithmetic optimisation algorithm (AOA-PID), the slime mould algorithm (SMA-PID), the teaching learning-based optimisation (TLBO-PID), as well as the traditional chien–hrones–reswick (CHR-PID) control for non-linear and time- varying mobile robots.
Important Links:
Go Back
