The traditional Proportional-Integral-Derivative (PID) controller is a feedback control loop that is commonly used in industrial control systems with fixed parameters, whereas the adaptive PID (APID) controller is based on the analysis of traditional PID controllers. It utilizes an online parameter adjustment method built on the state of the system resulting in better system adaptability. In this paper, the APID controller that is suggested by (Ebel, 2011) is used firstly to control a 2-degree of freedom (DOF) lower limb rehabilitation robot. The structure of this controller is then modified to perform a Modified Adaptive PID (MAPID) control in order to improve the efficiency of APID controller and hence improve the performance of the rehabilitation robot. The parameters of APID and the suggested MAPID controllers are optimized by using Grey Wolf Optimization (GWO) algorithm. Linear and non-linear desired trajectories are used to test the performance of the controlled rehabilitation robot. Simulation results show that the obtained performance of the rehabilitation robot is more efficient with the MAPID than with the APID having no overshoot and very small steady state error. The controller has settling time of (0.463) and (0.851) seconds, and rise time of (0.485) and (0.752) seconds respectively for link1 and link2.

The Sliding Mode Controllers (SMCs) are considered among the most common stabilizer and controllers used with robotic systems due to their robust nonlinear scheme designed to control nonlinear systems. SMCs are insensitive to external disturbance and system parameters variations. Although the SMC is an adaptive and model-based controller, some of its values need to be determined precisely. In this paper, an Optimal Sliding Mode Controller (OSMC) is suggested based on Whale Optimization Algorithm (WOA) to control a two-link lower limb rehabilitation robot. This controller has two parts, the equivalent part, and the supervisory controller part. The stability assurance of the controlled rehabilitation robot is analyzed based on Lyapunov stability. The WO algorithm is used to determine optimal parameters for the suggested SMC. Simulation results of two tested trajectories (linear step signal and nonlinear sine signal) demonstrate the effectiveness of the suggested OSMC with fast response, very small overshoot, and minimum steady-state error.

This paper Presents Modified Model Reference Adaptive Controller (MRAC) to regulate the hight blood pressure. It is based on slate model that represent the mathematical equation that clarifies relationship between blood pressure and vasoactive drug injection. In this work Squirrel Search Algorithm (SSA) and Grey Wolf Optimizer (GWO)algorithms are considered to optimize the controller parameters. the results showed that the suggested controller has good performance and stabilize the mean arterial pressure with small settling time (below than 400s) and small overshoot (below than 1 mmHg) with low amount of error.