Implementation of PID Controller with PSO Tuning for FES-Assisted Exercise

Abstract

This paper describes the implementation of PID control strategy for a functional electrical stimulation (FES) in specific rehabilitation exercise known as elliptical stepping exercise. The PID controller is used to regulate the FES in controlling the knee joint torque of the paretic and non-paretic legs of the hemiplegic stroke patient during the exercise. The cadence speed error is used as the control variable and input to the PID controller. The Particle Swarm Optimization (PSO) technique is used to optimize the PID control parameters and the performance is compared to that of the manual tuning. The result shows that the system has good interaction with PID controller in completing the exercise. The result also shows that PSO is an efficient technique in optimizing the control parameters compared to manual tuning. Further investigation of the control and optimization technique will be considered in the future in order to improve the efficiency of the FES-assisted elliptical stepping exercise.

An Effective Speed Control Strategy for Synchronous Generators of an Interconnected Hydropower System

“…Meanwhile, the conventional PID regulators, even determined by an automatic tuning tool in MATLAB/Simulink, they are not able to achieve good control performances. The simulation results also reveal that the fitness function provided in (15) obtained significantly better control performances compared to the first one indicated in (14).…”

“…Particle swarm optimization (PSO) technique has been considered to be one of the most effective bio-inspired optimization methods [7][8][9][10][11][12][13][14][15]. This optimization mechanism is inspired from social behavior of animal groups such as birds and fish.…”

“…The PID controller with the optimization of parameters is completely able to tackle the speed control problem of the interconnected hydropower system. This work is to propose a speed control strategy applying the modified PID controllers, in which the particle swarm optimization (PSO) algorithm considered to be one of the most successful optimization mechanisms is utilized to effectively determine three coefficients of the PID controller [6][7][8][9][10][11][12][13][14][15]. The applicability of the proposed control methodology will be testified and compared with the traditional PID regulator tuned by auto-tuning method existed in MATLAB/Simulink and the fuzzy logic controller studied in [5].…”