自适应模糊控制为复杂对象的控制提供了有效途径,引起控制领域的广泛关注.针对一类单输入单输出非线性不确定对象,利用Popov超稳定理论提出了一种新型的间接自适应模糊控制器设计方案.该方案首先采用对象模型构成理想的控制器,利用模糊系统的万能逼近特性构造若干模糊系统在线逼近未知的对象模型,然后将闭环系统转换为1个线性定常的前向环节和1个非线性时变的反馈环节组成的等效误差模型,通过Popov超稳定理论推导出稳定的参数自适应律.该方案能确保系统的输出渐近收敛到给定的参考信号,同时放宽了对最小逼近误差的限制,并且具有更广泛和灵活的参数调节形式.仿真结果验证了方案对非线性对象的有效性.
Adaptive fuzzy control provides an effective approach for the complicate plants, and it gets abroad attention in control field. A new scheme of indirect adaptive fuzzy controller is developed based on Popov hyperstability theory for a class of SISO uncertain nonlinear plants. At first an ideal controller is constructed by plant model, and some fuzzy systems are employed to approximate unknown plant model using universal approximation property of fuzzy systems. Then the close-loop system is converted to an equivalent error model which is composed of a linear constant forward block and a nonlinear time-varying feedback block, and stable adaptive law of parameter is deduced. It can guarantee the convergence of the system output to the given signal, at the same time restriction of minimum approximation error is relaxed, and it can offer more general and flexible form of parameters adjustment. Simulation results illustrate the validity of the proposed scheme to the nonlinear plants.