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Full State Constrained Adaptive Fuzzy Control for Stochastic Nonlinear Switched Systems With Input Quantization

机译:输入量化随机非线性开关系统的全状态约束自适应模糊控制

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In this paper, a fuzzy adaptive full state constrained control approach is proposed for a class of stochastic switched systems subject to quantized input signals and actuator faults. The inherent discontinuous and hybrid characteristics of the concerned systems lead to a difficult task for designing a stable controller. Several fuzzy logic systems are utilized to approximate the unknown nonlinearities and the bound estimation approach is employed to deal with the stochastic switched disturbances. As a result, the negative effects caused by the discontinuous multiple uncertainties can be suppressed. Furthermore, several four-order Barrier Lyapunov Functions are introduced to guarantee that the constraints of the system states are not violated. It is proved that all the signals in the closed-loop system is semiglobally uniformly ultimately bounded. Numerical simulation results have been provided to illustrate the satisfactory performance of the proposed control algorithm.
机译:本文提出了一种模糊自适应全州约束控制方法,用于一类经过量化输入信号和执行器故障的随机交换系统。有关系统的固有的不连续和混合特性导致设计稳定控制器的困难任务。几个模糊逻辑系统用于近似未知的非线性,采用结合的估计方法来处理随机切换干扰。结果,可以抑制由不连续多个不确定性引起的负面影响。此外,引入了几个四阶屏障Lyapunov功能以保证没有侵犯系统状态的约束。事实证明,闭环系统中的所有信号都是半球形均匀的最终限定的。已经提供了数值模拟结果来说明所提出的控制算法的令人满意的性能。

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