The robust H∞ control for networked control systems with both stochastic network-induced delay and data packet dropout is studied. When data are transmitted over network, the stochastic data packet dropout process ca...The robust H∞ control for networked control systems with both stochastic network-induced delay and data packet dropout is studied. When data are transmitted over network, the stochastic data packet dropout process can be described by a two-state Markov chain. The networked control systems with stochastic network-induced delay and data packet dropout are modeled as a discrete time Markov jump linear system with two operation modes. The sufficient condition of robust H∞ control for networked control systems stabilized by state feedback controller is presented in terms of linear matrix inequality. The state feedback controller can be constructed via the solution of a set of linear matrix inequalities. An example is given to verify the effectiveness of the method proposed.展开更多
实际工业过程中,量测数据除了在线仪表采集的快速率数据,还有离线化验等慢速率辅助量测数据.为了更好地利用离线化验数据,增加在线估计的精度,针对随机跳变系统,引入迁移学习思想,提出迁移交互多模型估计(Transfer interacting multiple...实际工业过程中,量测数据除了在线仪表采集的快速率数据,还有离线化验等慢速率辅助量测数据.为了更好地利用离线化验数据,增加在线估计的精度,针对随机跳变系统,引入迁移学习思想,提出迁移交互多模型估计(Transfer interacting multiple model state estimator,IMM-TF)新策略.首先,将离线化验数据的边缘分布作为可以迁移的知识,迁移到贝叶斯后验分布,实现辅助量测数据的充分利用.其次,利用KL(Kullback-Leibler)散度度量知识迁移前后任务间的差异性,求解最优的贝叶斯迁移估计器.同时,结合慢速率量测,利用平滑策略获取待迁移的估计值,解决多率量测下的迁移估计难题.然后,利用影响力函数构建辅助量测数据与估计性能之间的解析关系,从而对迁移效果进行定量评价.最后,通过在目标跟踪实例中的应用,表明所提方法的有效性及优越性.展开更多
Receding horizon H∞ control scheme which can deal with both the H∞ disturbance attenuation and mean square stability is proposed for a class of discrete-time Markovian jump linear systems when minimizing a given qua...Receding horizon H∞ control scheme which can deal with both the H∞ disturbance attenuation and mean square stability is proposed for a class of discrete-time Markovian jump linear systems when minimizing a given quadratic performance criteria. First, a control law is established for jump systems based on pontryagin’s minimum principle and it can be constructed through numerical solution of iterative equations. The aim of this control strategy is to obtain an optimal control which can minimize the cost function under the worst disturbance at every sampling time. Due to the difficulty of the assurance of stability, then the above mentioned approach is improved by determining terminal weighting matrix which satisfies cost monotonicity condition. The control move which is calculated by using this type of terminal weighting matrix as boundary condition naturally guarantees the mean square stability of the closed-loop system. A sufficient condition for the existence of the terminal weighting matrix is presented in linear matrix inequality （LMI） form which can be solved efficiently by available software toolbox. Finally, a numerical example is given to illustrate the feasibility and effectiveness of the proposed method.展开更多
In this paper,the problem of guaranteed cost control for a class of uncertain discrete-time Markovian jump linear systems with mode-dependent time-delays and a given quadratic cost function are investigated. Attention...In this paper,the problem of guaranteed cost control for a class of uncertain discrete-time Markovian jump linear systems with mode-dependent time-delays and a given quadratic cost function are investigated. Attention is focused on designing a memoryless state feedback control law such that the closed-loop system is robust stochastically stable and the closed-loop cost function value is not more than a specified upper bound,for all admissible uncertainties. The key features of the approach include the introduction of a new type of suitable stochastic Lyapunov functional and free weighting matrices techniques. Sufficient conditions for the existence of such controller are obtained in terms of a set of linear matrix inequalities. A numerical example is given to illustrate the less conservatism of the proposed techniques.展开更多
This paper is concerned with the problems of H-two filtering for discrete-time Markovian jump linear systems subject to logarithmic quantization. We assume that only the output of the system is available, and therefor...This paper is concerned with the problems of H-two filtering for discrete-time Markovian jump linear systems subject to logarithmic quantization. We assume that only the output of the system is available, and therefore the mode information is nonaccessible. In this paper, a mode-independent quantized H-two filter is designed such that filter error system is stochastically stable. To this end, sufficient conditions for the existence of an upper bound of H-two norm are presented in terms of linear matrix inequalities. Considering uncertainty of system matrices, a robust H-two filter is designed. The proposed method is also applicable to cover the case where the transition probability matrix is not exactly known but belongs to a given polytope. Finally, numerical examples are provided to demonstrate the effectiveness of the proposed approach.展开更多
基金the National Science and the Technology Pursuit Project of China (2001BA204B01)
文摘The robust H∞ control for networked control systems with both stochastic network-induced delay and data packet dropout is studied. When data are transmitted over network, the stochastic data packet dropout process can be described by a two-state Markov chain. The networked control systems with stochastic network-induced delay and data packet dropout are modeled as a discrete time Markov jump linear system with two operation modes. The sufficient condition of robust H∞ control for networked control systems stabilized by state feedback controller is presented in terms of linear matrix inequality. The state feedback controller can be constructed via the solution of a set of linear matrix inequalities. An example is given to verify the effectiveness of the method proposed.
文摘实际工业过程中,量测数据除了在线仪表采集的快速率数据,还有离线化验等慢速率辅助量测数据.为了更好地利用离线化验数据,增加在线估计的精度,针对随机跳变系统,引入迁移学习思想,提出迁移交互多模型估计(Transfer interacting multiple model state estimator,IMM-TF)新策略.首先,将离线化验数据的边缘分布作为可以迁移的知识,迁移到贝叶斯后验分布,实现辅助量测数据的充分利用.其次,利用KL(Kullback-Leibler)散度度量知识迁移前后任务间的差异性,求解最优的贝叶斯迁移估计器.同时,结合慢速率量测,利用平滑策略获取待迁移的估计值,解决多率量测下的迁移估计难题.然后,利用影响力函数构建辅助量测数据与估计性能之间的解析关系,从而对迁移效果进行定量评价.最后,通过在目标跟踪实例中的应用,表明所提方法的有效性及优越性.
基金supported by the National Natural Science Foundation of China (60974001)Jiangsu "Six Personnel Peak" Talent-Funded Projects
文摘Receding horizon H∞ control scheme which can deal with both the H∞ disturbance attenuation and mean square stability is proposed for a class of discrete-time Markovian jump linear systems when minimizing a given quadratic performance criteria. First, a control law is established for jump systems based on pontryagin’s minimum principle and it can be constructed through numerical solution of iterative equations. The aim of this control strategy is to obtain an optimal control which can minimize the cost function under the worst disturbance at every sampling time. Due to the difficulty of the assurance of stability, then the above mentioned approach is improved by determining terminal weighting matrix which satisfies cost monotonicity condition. The control move which is calculated by using this type of terminal weighting matrix as boundary condition naturally guarantees the mean square stability of the closed-loop system. A sufficient condition for the existence of the terminal weighting matrix is presented in linear matrix inequality （LMI） form which can be solved efficiently by available software toolbox. Finally, a numerical example is given to illustrate the feasibility and effectiveness of the proposed method.
基金Sponsored by the National Defense Basic Research Foundation of China (Grant No. 9140A17030207HT01)
文摘In this paper,the problem of guaranteed cost control for a class of uncertain discrete-time Markovian jump linear systems with mode-dependent time-delays and a given quadratic cost function are investigated. Attention is focused on designing a memoryless state feedback control law such that the closed-loop system is robust stochastically stable and the closed-loop cost function value is not more than a specified upper bound,for all admissible uncertainties. The key features of the approach include the introduction of a new type of suitable stochastic Lyapunov functional and free weighting matrices techniques. Sufficient conditions for the existence of such controller are obtained in terms of a set of linear matrix inequalities. A numerical example is given to illustrate the less conservatism of the proposed techniques.
基金partly supported by the Program of the International Science and Technology Cooperation (No. 2007DFA10600)the National High Technology Research and Development Program of China (863 Program) (No. 2009AA043001)+1 种基金the National Natural Science Foundation of China (No. 60904015)‘Chen Guang’Project supported by Shanghai Municipal Education Commission and Shanghai Education Development Foundation (No. 09CG17)
文摘This paper is concerned with the problems of H-two filtering for discrete-time Markovian jump linear systems subject to logarithmic quantization. We assume that only the output of the system is available, and therefore the mode information is nonaccessible. In this paper, a mode-independent quantized H-two filter is designed such that filter error system is stochastically stable. To this end, sufficient conditions for the existence of an upper bound of H-two norm are presented in terms of linear matrix inequalities. Considering uncertainty of system matrices, a robust H-two filter is designed. The proposed method is also applicable to cover the case where the transition probability matrix is not exactly known but belongs to a given polytope. Finally, numerical examples are provided to demonstrate the effectiveness of the proposed approach.
