Adaptive collaborative speed control of PMDC motor using hyperbolic secant functions and particle swarm optimization

Authors: OMER SALEEM, KHALID MAHMOOD-UL-HASAN

Abstract: This paper presents an adaptive collaborative speed controller for a permanent magnet direct-current (PMDC) motor. The proposed scheme beneficially combines the control efforts of a proportional-integral (PI) controller and a linear-quadratic regulator (LQR) via a weighted summing module. Initially, the weightages of the summing module are kept fixed. They are optimally tuned and tested via the particle swarm optimization algorithm. In order to synergize the controller combination, these weightages are adaptively modulated as well, using hyperbolic secant functions of the error dynamics of the motor's angular speed. The adaptive combination renders significant enhancement in the transient response, steady-state response, input-energy consumption, disturbance rejection, and variable load-torque handling capability of the motor. The adaptive-weighted controller is tested against the PI controller, the LQR, and a fixed-weighted collaborative controller via `hardware-in-the-loop' experiments. The experimental results are presented to validate the robustness of the adaptive controller.

Keywords: PMDC motor, linear-quadratic regulator, PI controller, adaptive-weighted control, particle swarm optimization, hyperbolic secant function

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