A fast MPC algorithm for reducing computation burden of MIMO

The computation burden in the model-based predictive control algorithm is heavy when solving QR optimization with a limited sampling step, especially for a complicated system with large dimension. A fast algorithm is proposed in this paper to solve this problem, in which real-time values are modulated to bit streams to simplify the multiplication. In addition, manipulated variables in the prediction horizon are deduced to the current control horizon approximately by a recursive relation to decrease the dimension of QR optimization. The simulation results demonstrate the feasibility of this fast algorithm for MIMO systems.

船舶动力定位的快速模型预测控制算法

动力定位(Dynamic Positioning,DP)系统可使船舶或海洋平台在外界环境干扰下通过足够数量的推进器来实现位置和航向的控制。为快速计算推进器的近似最优输入,利用模型预测控制(Model Predictive Control,MPC)问题的稀疏结构,提出一种提高MPC求解速度的方法。通过数值算例比较该快速MPC算法与传统算法的性能差异。仿真结果表明,该快速MPC技术具有一定的实时性和准确性。

一种降低计算负荷的快速预测控制算法（英文）

大多数模型预测控制算法因求解优化问题时在规定的采样时间内需要在线处理矩阵乘法操作而存在繁重的计算负荷问题。为了解决这一问题,本文提出了一种降低计算负荷的快速预测控制算法,将实时观测信号调制成正负一的比特流序列来简化传统的乘法运算。同时,将控制时域内未来时刻的控制律序列通过线性反馈控制律离线递推,用当前时刻控制律近似替代,从而降低了求解优化问题时的矩阵维数。