Optimum Design of Robust Adaptive Controller with Actuator Constraints

In this paper, a direct optimal adaptive nonlinear tracking control method for a class of uncertain Multi-Input Multi-Output (MIMO) nonlinear systems with actuator amplitude constraints in presence of unknown disturbance is developed. In order to handle parametric model uncertainties and external disturbance, an adaptive controller is presented. Particle Swarm Optimization (PSO) algorithm is employed to prevent constraints violation through determining the optimal adaptive controller parameters. The performance of this control approach is studied using a new index function in time-domain, and the stability analysis is conducted by Lyapunov theory. In addition, indicative robot examples are provided to illustrate how investigated method effectively stabilizes system and confines tracking error to prescribed bounds without control input saturation, particularly with large parametric uncertainties.