改进差分进化算法在非线性模型预测控制中的应用

为了解决非线性模型预测控制在实际工程系统应用时,传统方法求解非凸的非线性规划问题容易陷入局部极小,计算量随着问题维数的增加呈几何级数增长的问题,对传统的差分进化算法进行了改进.通过动态调节差分进化算法的主要参数加快差分进化算法的收敛速度,同时采用多种突变策略增加种群的多样性,有效克服了传统差分进化算法容易陷入局部极小的缺点.在简单三容液位系统上的仿真实验结果证明了该算法的有效性和可行性,在工业应用中具有较好的应用前景.

Application of Modified Differential Evolution Algorithm to Non-linear MPC

The main problem for the application of nonlinear model predictive control is to solve the non-convex in finite sampling time. Traditional method has some defects such as high computation and easy to fall into local solution. It is a wise choice to solve this problem by using intelligent method. In this paper, some modifications of the traditional differential evolution ( DE ) algorithm are made, including accommodating main parameters to increase the convergence rate, and employing various mutation strategies to increase multiplicity of the population and avoid falling into local solution. The simulation results in the three-tank system show that it is effective and available, with a good feature for application in industry.