Fuzzy control design of uncertain nonlinear active fault tolerant control systems
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摘要: 考虑到实际主动容错控制系统中故障以及故障检测与隔离(FDI,Fault Detection and Isolation)决策出现的随机性,随机故障与FDI决策行为分别用两个Markov过程描述,用T-S(Takagi-Sugeno)模糊模型表达不确定非线性主动容错控制系统,并基于并行分布补偿(PDC,Parallel Distributed Compensation)方案,给出了能够保证闭环模糊系统鲁棒随机稳定的模糊控制器设计方法.鲁棒容错模糊控制器的存在条件由一组线性矩阵不等式(LMI,Linear Matrix Inequality)给出,从而方便地利用优化技术求解,随后倒车控制系统的仿真结果验证了所建议方法的有效性.Abstract: By considering the random nature of the failure events and the FDI(failure detection and isolation)decisions in real FTC(fault tolerant control)systems, two Markov processes were introduced to describe the random failures and the FDI decision behavior separately. The Takagi and Sugeno fuzzy model was employed to represent a nonlinear active FTC system with norm-bounded uncertainties. Based on the parallel distributed compensation scheme, a method for the design of a fuzzy control law such that the closed-loop fuzzy system is robustly stochastically stable, was proposed. The sufficient condition for the existence of a robust and fault tolerant control law was given in terms of linear matrix inequalities, which can be solved efficiently by using the existing LMI(linear matrix inequality)optimization techniques. The latter truck-trailer simulation results show the effectiveness of the proposed method.
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Key words:
- active fault tolerant control /
- Markov processes /
- fuzzy control /
- random errors
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