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The robust sliding mode control for Markov jump systems with parameter uncertainties and an unknown nonlinear function is discussed. Based on a descriptor system approach and linear matrix inequality (LMI), a sufficient condition which guarantees the existence of linear switching surface and the stochastic stability of sliding mode dynamics is given. A sliding mode controller is designed such that...
In this paper, the problem of Hinfin control for a class of Markov jump linear system (MJLS) with timevarying transition rates (TRs) is investigated. The time-varying character of TRs is considered as finite piecewise homogeneous and the variations of TR matrices in the finite set are considered as two types: arbitrary variation and stochastic variation. The latter means that the variations are subject...
In this paper, we deal with the problem of quantized control strategy design for a class of discrete time Markovian jump linear systems with limited communication capacity. We generalize the static Quantizer design method of Elia and Mitter to stochastic system with Markovian jump parameter. The concept of mode-dependent logarithmic quantizer is presented firstly in this paper, which is employed to...
In this paper, we investigate coevolution of strategy and structure in Prisoner's Dilemma. We concentrate on the noise effect in the topological evolution on cooperation. We assume individuals can either update their strategies by imitating their partners or adjust their social ties. At each time in the strategy evolution, pairwise comparison is employed. While at each time in the topological evolution,...
This paper investigates stability analysis for linear systems with Markovian jumping parameters and state delays. Based on delay subinterval decomposition approach, a new Lyapunov-Krasovskii functional is proposed to develop the delay-dependent stochastic stability conditions for both nominal and uncertain time-delay Markovian systems. The results are formulated in terms of linear matrix inequalities...
In practical applications, it is often encountered that the jump modes of a Markovian jump linear system may not be fully accessible to the filter, and thus designing a filter which partially or totally independent of the jump modes becomes significant. In this paper, by virtue of a new stability and Hinfin performance characterization, a novel necessary and sufficient condition for the existence...
This paper investigates the problem of robust Hinfin control for Markovian jump systems with polytopic uncertain parameters and mode-dependent distributed delays. In terms of linear matrix inequalities, a sufficient condition for robust stochastic stability is proposed. A state feedback controller is designed such that the closed-loop system is stochastically stable and a prescribed Hinfin performance...
A model reduction method to match the coefficient of the transfer function G(s) of descriptor system is presented to obtain reduced order descriptor system. By projecting G(s) to the transfer function of discrete time system, the model reduction problem for the descriptor system is transformed to Markov parameters matching model reduction problem of the corresponding discrete time normal systems....
In this paper, a new robust Iterative Learning Control (ILC) algorithm has been proposed for linear systems in the presence of iteration-varying parametric uncertainties. The robust ILC design is formulated as a min-max problem using a quadratic performance criterion subject to constraints of the control input update. An upper bound of the maximization problem is derived, then, the solution of the...
In this paper, we propose a behavior selection scheme between a reactive motion control combined with a global path planning algorithm and combined with a trajectory tracking algorithm. We design two navigation behaviors. One is a plan-based reactive navigation behavior, the AutoMovereactive, which exploits the conventional Dynamic Window Approach (DWA) as the reactive motion controller. The other...
Due to the large economic and environmental impact and pervasive application, engine maintenance policy optimization has attracted the research interest in the past several decades. Markov decision process (MDP) provides a general framework for this problem, but the large state space makes it difficult to apply the traditional value iteration and policy iteration in practice. How to approximate the...
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