一种克服模型参数失配的广义预测控制算法

针对模型参数失配对广义预测控制输出的影响,提出了一种输出增量反馈的广义预测控制简化算法.该算法通过引入一个输出增量速度函数,设计了输出增量参考序列,以控制输出增量的方式间接控制系统输出；同时利用阶梯控制方式,对输入增量引入柔化系数矩阵进行约束,既避免了传统预测控制律中逆矩阵的求解,减少了计算量,又防止了控制量的剧烈变化；最后引入控制增量增益,利用这个自由度提高了系统的鲁棒稳定性.仿真结果表明:该预测控制简化算法能有效克服模型参数失配带来的影响,抑制系统输出调整过程中的输出波动,缩短调整时间,提高系统的动态特性,并抑制系统控制输入的剧烈变化.

Generalized predictive control algorithm overcoming model parametric mismatch

Aiming at the effect of model parametric mismatch to generalized predictive control, an output increment feedback generalized predictive control algorithm was presented. A speed function of output increment was introduced to design an output increment reference sequence and the system output was indirectly controlled by directly controlling output increment. The input increments were constrained by softness coefficient matrix to obtain smoothing input based on stepped control, and the computation of inverse matrix was avoided. Stability of system robustness was improved by using a factor to multiply the control increment. The simulation results indicate that the effect of model parametric mismatch is overcomed successfully by simplified predictive control algorithm. The output fluctuation during output adjusting process is offset, the adjusting time of dynamic response is reduced and the input is smoothed.