Abstract
In order to simplify the design procedure of traditional neural network backstepping and improve the robustness and precision of control, an improved scheme is studied for a class of nonlinear systems. To avoid reconstructing virtual control inputs in each recursive step, RBF neural networks are utilized as approximators to estimate the desired feedback control of the whole system only. Meanwhile, the integral action of tracking error is introduced into the backstepping design procedure, which not only participates in updating the neural network weight, but also serves as a component part of the control input. This design may benefit the parameter tuning and make controller perform better sometimes. Based on the Lyapunov synthesis approach, theoretical analysis and simulation results are provided to show the feasibility of the improved scheme.
Highlights
Backstepping technique can date back to [1]
The application in practice may be limited for high order systems until dynamic surface control is proposed [3]
For air-breathing hypersonic vehicle control, dynamic surface control technique is involved in conjunction with the backstepping control approach [4]
Summary
Backstepping technique can date back to [1]. As a systematic design approach, its recursive design procedure is suitable for complex strict-feedback systems. Based on Lyapunov’s stability theory, stable adaptive NN controller can be designed, so that the neural network weight can achieve on-line adjustment. By utilizing some properties of the system, the desired feedback control of the whole system has the form in which the unknown nonlinearities and known quantities are separated It is not necessary for each subsystem to acquire a virtual control input estimated by neural network. We introduce the integral action of tracking error into the backstepping design procedure, which participates in updating the neural network weight, and serves as a component part of the control input.
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call