The receding horizon control（RHC） problem is considered for nonlinear Markov jump systems which can be represented by Takagi-Sugeno fuzzy models subject to constraints both on control inputs and on observe outputs.I...The receding horizon control（RHC） problem is considered for nonlinear Markov jump systems which can be represented by Takagi-Sugeno fuzzy models subject to constraints both on control inputs and on observe outputs.In the given receding horizon,for each mode sequence of the T-S modeled nonlinear system with Markov jump parameter,the cost function is optimized by constraints on state trajectories,so that the optimization control input sequences are obtained in order to make the state into a terminal invariant set.Out of the receding horizon,the stability is guaranteed by searching a state feedback control law.Based on such stability analysis,a linear matrix inequality approach for designing receding horizon predictive controller for nonlinear systems subject to constraints both on the inputs and on the outputs is developed.The simulation shows the validity of this method.展开更多
Day by day, networked control system（NCS） methods have been promoted for distributed closed-loop control systems.Interestingly, the integration of control and computing theories enhanced the development of networked...Day by day, networked control system（NCS） methods have been promoted for distributed closed-loop control systems.Interestingly, the integration of control and computing theories enhanced the development of networked control systems through remote control for wide applications employing the internet. Two further directions to networked control technology are LeaderFollower systems and model predictive control systems. Cloud control system is looked at an extension of networked control systems（NCS） using internet of things（IOT） methodologies. In this paper, a comprehensive literature survey of the new technology of control systems application performed on cloud computing is presented.展开更多
基金supported by the National Natural Science Foundation of China (6097400160904045)+1 种基金National Natural Science Foundation of Jiangsu Province (BK2009068)Six Projects Sponsoring Talent Summits of Jiangsu Province
文摘The receding horizon control（RHC） problem is considered for nonlinear Markov jump systems which can be represented by Takagi-Sugeno fuzzy models subject to constraints both on control inputs and on observe outputs.In the given receding horizon,for each mode sequence of the T-S modeled nonlinear system with Markov jump parameter,the cost function is optimized by constraints on state trajectories,so that the optimization control input sequences are obtained in order to make the state into a terminal invariant set.Out of the receding horizon,the stability is guaranteed by searching a state feedback control law.Based on such stability analysis,a linear matrix inequality approach for designing receding horizon predictive controller for nonlinear systems subject to constraints both on the inputs and on the outputs is developed.The simulation shows the validity of this method.
基金supported by the deanship of scientific research(DSR) at KFUPM through distinguished professorship research project(No.IN141003)
文摘Day by day, networked control system（NCS） methods have been promoted for distributed closed-loop control systems.Interestingly, the integration of control and computing theories enhanced the development of networked control systems through remote control for wide applications employing the internet. Two further directions to networked control technology are LeaderFollower systems and model predictive control systems. Cloud control system is looked at an extension of networked control systems（NCS） using internet of things（IOT） methodologies. In this paper, a comprehensive literature survey of the new technology of control systems application performed on cloud computing is presented.
