Adaptive Robust Control Of Nonlinearly Parameterized System With Unmodeled Dynamics

Due to various reasons, unmodeled dynamics can be produced in practical systems. For example, it is very difficult to find the accurate models of systems. On the other hand, some dynamic properties of systems will be lost when simplifying the model to acquire the convenience of research. Unmodeled dynamics exist in any practical plant, so the satisfying control performance can't be achieved if we neglect the unmodeled dynamics. Therefore, it is necessary to consider the unmodeled dynamics in order that the controllers designed can be better applied in practical systems.This paper presents a new adaptive robust controller for a class of nonlinearly parameterized systems with unmodeled dynamics and other uncertainties. Using Lyapunov function methods, a dynamic signal is used to restrain the unmodeled dynamics, and other uncertainties are bounded by a function of fractional parameterization. It is shown that the proposed adaptive robust control scheme guarantees the stability of the nonlinear system, and all the variables in the closed-loop system are bounded. Simulation results show that compared with the adaptive controllers reported in the literature, the controllers presented in this paper guarantee global stability and stronger robustness of the system. Furthermore, all the states can approach to the equilibrium in arbitrary precise by choosing the design constants appropriately.