Robust human-imitating intelligent control for a class of nonlinear systems
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摘要: 针对一类非线性不确定系统,结合二级倒立摆控制系统设计作为实例,提出一种鲁棒拟人智能控制器设计方法.首先,基于被控对象的物理模型设计拟人定性控制律,采用优化搜索算法得到标称系统的定量控制律;然后在拟人控制律基础上增加一个鲁棒补偿器,用以抑制模型不确定性部分对系统稳定的不利影响、提高系统的鲁棒性.补偿器的设计根据Lyapunov稳定性理论进行,但设计过程中避免了构造具体的Lyapunov函数这一难题.对二级倒立摆系统的稳定控制问题进行了实验验证,实验结果进一步证明了设计方案的有效性.Abstract: A robust human-imitating intelligent control was proposed for nonlinear systems. Firstly, a human-imitating qualitative control law was developed through the analyses of the physical model of the plant. The qualitative control law was quantified by some method of parameter-optimization based on the nominal model of the plant. Then, on the basis of the developed human-imitating controller, a robust compensator was proposed to overcome the bad influences resulted from modeling errors, unmodeled dynamics and disturbances. The compensator was derived by Lyapunov stability theory, thus the stability of the closed-loop system was guaranteed. However, the specified Lyapunov function usually essential in a common Lyapunov-based approach was not needed during the design ofthe robust compensator, as a result, the difficulties in designing the Lyapunov function for a nonlinear system was conquered. Applying the proposed scheme to control a double inverted pendulum, the results of experiment verify the validity of this design.
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