Adaptive Command Filtered Control of Strict Feedback Systems With Uncertain Control Gains
In this paper,a command filtered-based adaptive neural control scheme is developed for strict feedback systems with uncertain control gains.In the developed scheme,neural networks are adopted to approximate the un-known nonlinear system functions and command filtered backstepping technique is utilized to solve the"explosion of complexity"problem.Compared with the literature on command filtered backstepping control,in this paper,an adaptive error compensating system is constructed to eliminate the impacts of the boundary layer errors generated by the filters and the uncertain control gains on system performance simultaneously.Simulation results are presen-ted to verify the effectiveness of the proposed control scheme.
Nonlinear systemscommand filtered backsteppingneural network controladaptive control
万方数据
维普
