模型预测控制
滑模控制
控制理论(社会学)
模式(计算机接口)
计算机科学
控制工程
芯(光纤)
控制(管理)
工程类
非线性系统
人工智能
物理
电信
量子力学
操作系统
作者
Huili Xiao,Dongya Zhao,Shouli Gao,Sarah K. Spurgeon
标识
DOI:10.1016/j.arcontrol.2022.07.003
摘要
This paper reviews the development and application of sliding mode predictive control (SMPC) in a tutorial manner. Two core design paradigms are revealed in the combination of sliding mode control (SMC) and model predictive control (MPC). In the first case, MPC is used in the reaching phase to ensure a sliding mode is attained. In the second case, MPC is used to solve the existence problem and define the required performance in the sliding mode. The two approaches are discussed in detail from the perspectives of both theory and application. Finally, some future challenges and opportunities in the area of SMPC are summarized.
科研通智能强力驱动
Strongly Powered by AbleSci AI