摘要
针对目前大多数自适应离散变结构滑模控制存在的对受控系统数学模型依赖性和未建模动态问题,提出一类离散时间非线性系统的无模型自适应滑模控制,并对其控制律进行改进。该控制策略本质上属于一种数据驱动控制方法,控制器的设计仅依赖于系统的输入输出数据,不需要任何被控系统模型信息。理论分析表明:该控制算法提高了伪偏导数估计值信息的利用率,加快了系统收敛速度,并通过严格数学推导验证了控制系统的稳定性。通过对直线电机位置和速度信息跟踪的仿真结果表明,该无模型自适应滑模控制具有较好的控制性能,跟踪精度大大提高,鲁棒性增强。
This paper presents a class of discrete-time nonlinear systems model-free adaptive sliding mode con- trol algorithm to solve the mathematical model dependency and model-free dynamics of the controlled system, and improved its control law. This control strategy belongs to a kind of data-driven control method in essence, and which controller designing depends on the system input and output data without any controlled system mod- el information. Theoretical analysis showed that this proposed control algorithm enhanced the utilization of pseudo partial derivative estimate information and accelerated the convergence＇ s velocity, and the stability of control system was verified by strict mathematical deduction. This proposed model-free adaptive sliding mode control algorithm has obtained better control performance through the simulations for linear motor position and speed information tracking, which has achieved accurate traceability and strong robustness.
出处
《河南理工大学学报（自然科学版）》
CAS
北大核心
2015年第2期242-248,共7页
Journal of Henan Polytechnic University（Natural Science）
基金
河南省重点科技攻关项目(102102210197)
河南省高等学校矿山信息化重点学科开放实验室开放基金
河南理工大学博士基金资助项目(B2010-23)
关键词
非线性系统
无模型自适应控制
滑模控制
伪偏导数
nonlinear system
model-free adaptive control
sliding mode control
pseudo partial derivative
