This paper considers the consensus problem of a group of homogeneous agents. These agents are governed by a general linear system and can only directly measure the output, instead of the state. In order to achieve the...This paper considers the consensus problem of a group of homogeneous agents. These agents are governed by a general linear system and can only directly measure the output, instead of the state. In order to achieve the consensus goal, each agent estimates its state through a Luenberger observer, exchanges its estimated state with neighbors, and constructs the control input with the estimated states of its own and neighbors. Due to the existence of observation and process noises, only practical consensus, instead of asymptotical consensus, can be achieved in such multi-agent systems. The performance of the achieved practical consensus can be measured by the ultimate mean square deviation of the states of agents. That performance is closely related to the observation gains of the state observers and the control gains of agents. This paper proposes a method to optimize such performance with respect to the concerned observation and control gains. That method starts with a set of feasible observation and control gains and formulates a group of linear matrix inequalities （LMIs）. Solving these LMIs gives some intermediate matrix variables. By perturbing observation and control gains, and the intermediate matrix variables, the original LMIs yield another group of LMIs, which can be solved to provide a descent direction of observation and control gains. Moving along that descent direction, observation and control gains can be improved to yield better performance and work as the starting point of the next iteration. By iteratively repeating this procedure, we can hopefully improve the consensus performance of the concerned multi-agent system. Simulations are done to demonstrate the effectiveness of the proposed method.展开更多
For a class of value-bounded uncertain descriptor large-scale interconnected systems, the decentralized robust H∞ descriptor output feedback control problem is investigated. A design method based on the bounded real ...For a class of value-bounded uncertain descriptor large-scale interconnected systems, the decentralized robust H∞ descriptor output feedback control problem is investigated. A design method based on the bounded real lemma is developed for a decentralized descriptor dynamic output feedback controller, which is reduced to a feasibility problem for a nonlinear matrix inequality （NLMI）. It is proposed to solve the NLMI iteratively by the idea of homotopy, where some of the variables are fixed alternately at each iteration to reduce the NLMI to a linear matrix inequality （LMI）. A given example shows the efficiency of this method .展开更多
When a feedback system has components described by non-rational transfer functions, a standard practice in designing such a system is to replace the non-rational functions with rational approximants and then carry out...When a feedback system has components described by non-rational transfer functions, a standard practice in designing such a system is to replace the non-rational functions with rational approximants and then carry out the design with the approximants by means of a method that copes with rational systems. In order to ensure that the design carried out with the approximants still provides satisfactory results for the original system, a criterion of approximation should be explicitly taken into account in the design formulation. This paper derives such a criterion for multi-input multi-output（MIMO） feedback systems whose design objective is to ensure that the absolute values of every error and every controller output components always stay within prescribed bounds whenever the inputs satisfy certain bounding conditions. The obtained criterion generalizes a known result which was derived for single-input single-output（SISO） systems; furthermore, for a given rational approximant matrix, it is expressed as a set of inequalities that can be solved in practice. Finally, a controller for a binary distillation column is designed by using the criterion in conjunction with the method of inequalities. The numerical results clearly demonstrate that the usefulness of the criterion in obtaining a design solution for the original system.展开更多
In this paper, the discrete-time static output feedback control design problem is con- sidered. A nonlinear conjugate gradient method is analyzed and studied for solving an unconstrained matrix optimization problem th...In this paper, the discrete-time static output feedback control design problem is con- sidered. A nonlinear conjugate gradient method is analyzed and studied for solving an unconstrained matrix optimization problem that results from this optimal control prob- lem. In addition, through certain parametrization to the optimization problem an initial stabilizing static output feedback gain matrix is not required to start the conjugate gradi- ent method. Finally, the proposed algorithms are tested numerically through several test problems from the benchmark collection.展开更多
基金The work of W. Zheng and Q. Ling was partially supported by the National Natural Science Foundation of China （No. 61273112） and the National Key Research and Development Project （No. 2016YFC0201003）. The work of H. Lin was partially supported by the National Science Foundation （Nos. NSF-CNS-1239222, NSF-CNS-1446288, NSF-EECS-1253488）.
文摘This paper considers the consensus problem of a group of homogeneous agents. These agents are governed by a general linear system and can only directly measure the output, instead of the state. In order to achieve the consensus goal, each agent estimates its state through a Luenberger observer, exchanges its estimated state with neighbors, and constructs the control input with the estimated states of its own and neighbors. Due to the existence of observation and process noises, only practical consensus, instead of asymptotical consensus, can be achieved in such multi-agent systems. The performance of the achieved practical consensus can be measured by the ultimate mean square deviation of the states of agents. That performance is closely related to the observation gains of the state observers and the control gains of agents. This paper proposes a method to optimize such performance with respect to the concerned observation and control gains. That method starts with a set of feasible observation and control gains and formulates a group of linear matrix inequalities （LMIs）. Solving these LMIs gives some intermediate matrix variables. By perturbing observation and control gains, and the intermediate matrix variables, the original LMIs yield another group of LMIs, which can be solved to provide a descent direction of observation and control gains. Moving along that descent direction, observation and control gains can be improved to yield better performance and work as the starting point of the next iteration. By iteratively repeating this procedure, we can hopefully improve the consensus performance of the concerned multi-agent system. Simulations are done to demonstrate the effectiveness of the proposed method.
基金This work was supported by the National Natural Science Foundation of China (No.60474003) the Doctor Subject Foundation of China (No.20050533028).
文摘For a class of value-bounded uncertain descriptor large-scale interconnected systems, the decentralized robust H∞ descriptor output feedback control problem is investigated. A design method based on the bounded real lemma is developed for a decentralized descriptor dynamic output feedback controller, which is reduced to a feasibility problem for a nonlinear matrix inequality （NLMI）. It is proposed to solve the NLMI iteratively by the idea of homotopy, where some of the variables are fixed alternately at each iteration to reduce the NLMI to a linear matrix inequality （LMI）. A given example shows the efficiency of this method .
基金financial support from the honour program of the Department of Electrical Engineering,Faculty of Engineering,Chulalongkorn University
文摘When a feedback system has components described by non-rational transfer functions, a standard practice in designing such a system is to replace the non-rational functions with rational approximants and then carry out the design with the approximants by means of a method that copes with rational systems. In order to ensure that the design carried out with the approximants still provides satisfactory results for the original system, a criterion of approximation should be explicitly taken into account in the design formulation. This paper derives such a criterion for multi-input multi-output（MIMO） feedback systems whose design objective is to ensure that the absolute values of every error and every controller output components always stay within prescribed bounds whenever the inputs satisfy certain bounding conditions. The obtained criterion generalizes a known result which was derived for single-input single-output（SISO） systems; furthermore, for a given rational approximant matrix, it is expressed as a set of inequalities that can be solved in practice. Finally, a controller for a binary distillation column is designed by using the criterion in conjunction with the method of inequalities. The numerical results clearly demonstrate that the usefulness of the criterion in obtaining a design solution for the original system.
文摘In this paper, the discrete-time static output feedback control design problem is con- sidered. A nonlinear conjugate gradient method is analyzed and studied for solving an unconstrained matrix optimization problem that results from this optimal control prob- lem. In addition, through certain parametrization to the optimization problem an initial stabilizing static output feedback gain matrix is not required to start the conjugate gradi- ent method. Finally, the proposed algorithms are tested numerically through several test problems from the benchmark collection.
