Fault-Tolerant Controller Design for a Class of Discrete Time Systems With Actuator Faults
this paper investigates the adaptive actuator failure compensation control for a class of uncertain multi input single out (MISO) discrete time systems with triangular forms.The systems contain the actuator faults of both loss of effectiveness and lock-in-place.With the help of radial basis function neural networks (RBFNN) to approximate the unknown noulinear functions, an adaptive RBFNN fault-tolerant control (FTC)scheme is designed.Compared with some exist result in which solving linear matrix inequality (LMI) is required, we introduce the backstepping technique to ashieve the FTC task.It is proved that the proposed control approach can guarantee that all the signals of the closed-loop system are bounded and that the output can successfully track a reference signal in the presence of the actuator failures.Finally, simulation results are provided to confirm the effectiveness of the control approach.
Adaptive fault-tolerant control RBF neural network discrete time system actuator failure
Lei Liu Zhengwei Shen Zhanshan Wang
College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, 110819, China
国内会议
西南大学2014年全国博士生学术论坛(电子技术与信息科学领域)
重庆
英文
315-320
2014-12-01(万方平台首次上网日期,不代表论文的发表时间)