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基于无模型控制、粒子群优化和预测控制的思想,提出一种新型非线性无模型预测控制器,并对该控制器的收敛性进行了分析.该控制器以带误差修正的泛模型为预测模型,以高速收敛的粒子群优化算法为滚动优化策略,不仅避免了非线性预测控制中复杂的矩阵求逆运算,而且提高了算法的收敛速度,增强了实时性.仿真研究表明了该控制器的有效性.
Based on the idea of modelless control, particle swarm optimization and predictive control, a new type of nonlinear modelless predictive controller is proposed and the convergence of the controller is analyzed. The controller uses a generic model with error correction as a predictor Model, a particle swarm optimization algorithm with high-speed convergence is a rolling optimization strategy, which not only avoids the complicated matrix inversion operation in nonlinear predictive control, but also improves the convergence speed of the algorithm and enhances the real-time performance. Simulation results show that the controller Effectiveness.