Suppr超能文献

基于事件的带加性干扰的非线性系统模型预测控制:一种拟微分类型方法

Event-Based MPC for Nonlinear Systems with Additive Disturbances: A Quasi-Differential Type Approach.

作者信息

Xu Zhongxian, He Ning, He Lile, Ma Kai

机构信息

School of Mechanical and Electrical Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China.

School of Mechanical and Electrical Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China; Ministry of Education Key Laboratory for Intelligent Networks and Network Security, Xi'an Jiaotong University, Xi'an 710049, China.

出版信息

ISA Trans. 2022 Sep;128(Pt B):136-143. doi: 10.1016/j.isatra.2021.11.009. Epub 2021 Nov 23.

Abstract

By integrating the event-based mechanism and the model predictive control (MPC) method, an improved event-based MPC framework is constructed for the nonlinear control problem subject to disturbances. Firstly, a new event-triggering condition is suggested, which is constructed on the basis of the gradients of the differences between the optimal state prediction and the actual one at two consecutive sample times. Then, an event-based MPC algorithm is further proposed, in which the dual-mode control technique is incorporated to handle the nonlinear perturbed system. Furthermore, it is strictly demonstrated that the proposed algorithm will ensure the feasibility of the MPC method and the stability of the considered system, while significantly decreasing the number of solving optimization problems, based on which resources for information transfer can be effectively saved. Finally, simulations and comparisons are shown to verify the efficacy of the proposed framework.

摘要

通过整合基于事件的机制和模型预测控制(MPC)方法,针对受干扰的非线性控制问题构建了一种改进的基于事件的MPC框架。首先,提出了一种新的事件触发条件,该条件基于两个连续采样时刻最优状态预测与实际状态之间差异的梯度构建。然后,进一步提出了一种基于事件的MPC算法,其中融入了双模控制技术来处理非线性摄动系统。此外,严格证明了所提出的算法将确保MPC方法的可行性和所考虑系统的稳定性,同时显著减少求解优化问题的次数,在此基础上可以有效节省信息传输资源。最后,通过仿真和比较验证了所提出框架的有效性。

相似文献

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验