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针对高阶系统提出了一种模型降阶以及分数阶内模IDμ控制器设计方法。首先基于积分平方误差(ISE)性能指标,利用微粒群优化(Particle Swarm Optimization,PSO)算法将高阶系统模型降阶为含有时滞环节的分数阶模型;然后根据内模控制(Internal Model Control,IMC)原理,并用一阶泰勒表达式逼近模型中的时滞环节,推导出了分数阶IMC-IDμ控制器,该控制器仅包含一个可调参数;最后根据系统的最大灵敏度指标,实现了控制器参数的鲁棒整定。仿真结果表明,本文方法可使系统同时具有较好的动态响应、干扰抑制性能以及克服参数摄动的鲁棒性。
Aiming at the high-order system, a design method of model order reduction and fractional-order IDμ-controller is proposed. Firstly, the high-order system model is reduced to a fractional model with time-lag links based on ISS performance index and Particle Swarm Optimization (PSO) algorithm. Then according to the internal model control (Internal Model Control, IMC) principle, and the first-order Taylor’s expression is used to approximate the time-lapse in the model, a fractional IMC-IDμ controller is derived, which contains only one adjustable parameter. Finally, according to the maximum sensitivity index of the system, Robust tuning of the parameters of the device. Simulation results show that this method can make the system have better dynamic response, interference suppression performance and overcome the robustness of parameter perturbation.