Prescribed performance dynamic surface control for nonlinear systems subject to partial and full state constraints

作者:

Highlights:

• In comparison with the existing results concerning the methods of coping with the state constraints, we present a more beneficial control method in which the state constraint variables are tackled with the constructed funnel error variables rather than the conventional BLF method.

• The performance metric cannot be prescribed in the existing results. With the control method of this paper, we can guarantee that the steady error and convergence rate satisfy the prescribed performance metrics, and the infringements of state constraints never happen simultaneously.

• To verify the feasibility of the scheme proposed, we discuss the prescribed performance control issues for NSs with partial and full state constraints, respectively. Under the framework of Lyapunov stability, all closed-loop variables can be SGUUB in each case.

摘要

•In comparison with the existing results concerning the methods of coping with the state constraints, we present a more beneficial control method in which the state constraint variables are tackled with the constructed funnel error variables rather than the conventional BLF method.•The performance metric cannot be prescribed in the existing results. With the control method of this paper, we can guarantee that the steady error and convergence rate satisfy the prescribed performance metrics, and the infringements of state constraints never happen simultaneously.•To verify the feasibility of the scheme proposed, we discuss the prescribed performance control issues for NSs with partial and full state constraints, respectively. Under the framework of Lyapunov stability, all closed-loop variables can be SGUUB in each case.

论文关键词:Prescribed performance control,Dynamic surface control,State-constrained system,Funnel control

论文评审过程:Received 12 March 2022, Revised 19 May 2022, Accepted 7 June 2022, Available online 20 June 2022, Version of Record 20 June 2022.

论文官网地址:https://doi.org/10.1016/j.amc.2022.127318