Design of Adaptive PID Controller for Lower Limb Rehabilitation Robot Based on Particle Swarm Optimization Algorithm.

The proportional-integral-derivative (PID) is still the most common controller and stabilizer used in industry due to its simplicity and ease of implementation. However, in most of the real applications, the controlled system has parameters that slowly vary or are uncertain. Thus, PID gains must be adapted to cope with such changes. In this research, an Adaptive Proportional-Integral-derivative controller (APID) is proposed to control the 2-DOF lower limb rehabilitation robot system. The parameters gains of the proposed controller are optimized using the Particle Swarm Optimization algorithm (PSO). The simulation results show no overshoot and zero steady-state error, but large settling time (ts=3.654 sec. for link1 and ts=2.844 sec. for link2) for linear path, and the actual path tracks the desired path with a large error for the nonlinear path. The results illustrate that the robot's performance is inefficient for linear and nonlinear paths when using the APID controller to control the lower limb rehabilitation robot. Therefore, the controller needs to modify for controlling the robot efficiently.