一种新型的输入受约束的自适应控制

An Adaptive Model Algorithmic Control with Input Constraints

在系统输入受约束时,采用一般的广义预测控制有可能会造成算法的不可行,从而使系统的控制质量变坏,甚至造成系统的不稳定。针对输入受约束系统,采用简化的三角化脉冲响应模型,提出一种输入受约束的自适应模型算法控制。该算法只需在线辨识一个参数,不必求逆矩阵,极大地减少了计算量。而且,在输入和输入增量约束条件下,通过调整参考输出,使得约束条件的个数简化为一个,并可保证闭环系统的渐近稳定和全局收敛性。仿真结果进一步证实了该算法的有效性。

For input-constrained systems,an adaptive model algorithmic control with input constraints is presented based on the simplified triangular model.Only one parameter in the algorithm needs identifying on line and the inverse matrix needs not to be computed,which reduces amounts of computation greatly.Moreover,with inputs and their increment constraints,by adjusting the reference output of the controlled system,the algorithm reduces the amount of constraints to one and guarantees that the close-loop system is asymptotically stable and globally convergent.Simulation results show that the algorithm is effective.