摘要
PID(proportional integral derivative)控制器广泛应用于各种工业过程,但实际被控对象的机理、复杂程度和环境条件各不相同,常规整定方法很难维持满意的效果。为了增强控制系统的鲁棒性和稳定性,先进的PID控制算法得到了广泛的关注。针对常见的带积分受控自回归滑动平均(CARIMA)模型提出了一类基于预测的自适应控制算法,使得PID参数能够随着对象模型参数的变化而变化,实现在线整定。该递推算法是通过在给定时域内极小化性能指标函数而得到的,其中性能指标函数考虑了某一给定范围内给定输入和预测输出的二次偏差以及控制量,在线辨识阶段则采用递推最小二乘算法。仿真结果证实该方法有很好的自适应力和鲁棒性。
The PID controller has been widely used in various industrial processes. However, for real practical control plants, their mechanisms, structures and operation conditions are different, and conventional tuning methods cannot always work in a desirable state. In order to improve the robustness and the stability of the control systems, advanced PID control algorithms have been attracted much attention. A prediction based adaptive control algorithm is proposed for CARIMA models, where the PID parameters can be tuned adaptively according to the parameters of the control plant. The key is minimizing a performance index which considers the quadratic predicted output, over the set point, as well as the control efforts, over a time horizon. For the online identification step, the recursive extended least squares estimation technique is implemented. The adaptability and the robustness of the proposed algorithm are validated by simulation results.
出处
《系统仿真学报》
CAS
CSCD
北大核心
2015年第11期2778-2783 2790,2790,共7页
Journal of System Simulation
基金
国家自然科学基金(61304138
61473136)
江苏省自然科学基金(BK20130163)
