非线性系统执行器死区故障的鲁棒自适应控制

针对一类具有不对称执行器死区故障的不确定非线性系统,基于反推滑模控制原理提出了一种神经网络鲁棒自适应控制方案。通过简化死区故障模型,取消了模型倾斜度相等和边界对称条件,结合动态面控制避免了传统反推设计方法存在的计算复杂性问题。所提控制方案取消了控制方向已知的条件,消除了执行器死区故障的影响,使得系统输出趋于给定参考轨迹的一个小领域。仿真结果验证了该方法的有效性。

Robust adaptive control of nonlinear systems with actuator dead-zone fault

A neural network robust adaptive control scheme for a class of uncertain nonlinear systems with non-symmetric actuator dead-zone fault is proposed based on the principle of backstepping sliding mode control.The restrictions that the dead-zone slopes and the boundaries are equal and symmetrical are removed by simplifying the dead-zone fault model.The explosion of complexity in traditional backstepping design is avoided by combining with the dynamic surface control.The proposed method does not require the priori knowledge of the control direction to be known and eliminates the effect of actuator dead-zone fault,thus the output of the system is able to converge to a small neighborhood of the desired trajectory.Simulation results validate the effectiveness of the proposed method.