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Adaptive Fuzzy Identification and Control for a Class of Nonlinear Pure-Feedback MIMO Systems With Unknown Dead Zones

机译:一类未知死区的非线性纯反馈MIMO系统的自适应模糊识别与控制

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The adaptive fuzzy identification and control problems are considered for a class of multi-input multi-output nonlinear systems with unknown functions and unknown dead-zone inputs. The main characteristics of the considered systems are that 1) they are composed of subsystems and each subsystem is in nested lower triangular form, 2) dead-zone inputs are in nonsymmetric nonlinear form, and 3) dead-zone inputs appear nonlinearly in the systems and their parameters are not required to be known. The controller design for this class of systems is a difficult and complicated task because of the existences of unknown functions, the couplings among the nested subsystems, and the dead-zone inputs. In the controller design, the fuzzy logic systems are employed to approximate the unknown functions and the differential mean value theorem is used to separate dead-zone inputs. To compensate for dead-zone inputs, the compensative terms are designed in the controllers. The stability of the closed-loop system is proved via the Lyapunov stability theorem. A simulation example is provided to validate the feasibility of the approach.
机译:针对一类具有未知函数和未知死区输入的多输入多输出非线性系统,考虑了自适应模糊辨识和控制问题。所考虑的系统的主要特征是:1)它们由子系统组成,每个子系统为嵌套的下三角形式; 2)死区输入为非对称非线性形式; 3)死区输入在系统中呈非线性状态不需要知道它们的参数。由于存在未知功能,嵌套子系统之间的耦合以及死区输入,用于此类系统的控制器设计是一项艰巨而复杂的任务。在控制器设计中,采用模糊逻辑系统来近似未知函数,并使用微分平均值定理来分离死区输入。为了补偿死区输入,在控制器中设计了补偿项。通过Lyapunov稳定性定理证明了闭环系统的稳定性。提供了一个仿真示例,以验证该方法的可行性。

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