具有状态约束的机电伺服系统自适应鲁棒控制

针对执行器动态及其状态受限、状态中存在测量噪声的问题,为伺服系统设计了一种基于非线性高增益观测器的自适应非线性鲁棒跟踪方法.基于系统位置测量值设计高增益观测器,利用滤波器消除噪声对观测器精度的影响,采用自适应律估计观测器增益,以保证观测器的鲁棒性.在设计过程中,引入一种新的障碍Lyapunov函数,以限制中间控制信号的幅值而满足系统对状态变量的约束要求,并通过Lyapunov方法验证了闭环系统的一致有界稳定性.结果表明,所提出的方法能够准确估算负载位置和速度.与传统的控制方法相比,其所观测的信息量较充分、估计精度较高、抗干扰能力及参数变化的鲁棒性较强.

Adaptive Robust Control for Mechatronic Servo System with State Constraints

A nonlinear adaptive robust tracking strategy based on high-gain observer was designed for the servo system with state constraint for actuator dynamics and state measurement noise. A high-gain observer based on the value of the position measurement system was introduced, which consisted of a series of filters to eliminate the noise on the accuracy of the observer and the gain was estimated to ensure the observer robustness. A novel barrier Lyapunov function was proposed for tracking desired guidance commands. In the process of the design, requirements on system states could be satisfied by limiting the magnitude of the virtual control signals. The entire uniform bounded stability of the closed-loop system was proved by Lyapunov method. The system test shows the method suggested in this paper can estimate the speed and position of the load. Compared with the traditional control method, it has the advantages of strong anti-jamming capability, good robustness and rapid speed.