1,721,058 research outputs found
Output feedback stabilization of nonlinear MIMO systems having uncertain high-frequency gain matrix
No full textThe purpose of this paper is to provide a method for (semi-global) asymptotic stabilization of a nonlinear minimum-phase MIMO system, under a mild hypothesis of the so-called "high-frequency gain" matrix. This result is based on a non-trivial extension, to the MIMO setting, of the approach based on the use of extended observers. As a byproduct, a dynamic output feedback control is obtained, that asymptotically stabilizes the equilibrium of the closed-loop system, in spite of uncertainties in the high-frequency gain matrix. © 2015 Elsevier B.V. All rights reserved
Nonlinear Output Regulation for Invertible Nonlinear MIMO Systems
No full textIn this paper, we address the problem of output regulation for a broad class of multi-input multi-output (MIMO) nonlinear systems. Specifically, we consider input–affine systems, which are invertible and input–output linearizable. This class includes, as a trivial special case, the class of MIMO systems which possess a well-defined vector relative degree. It is shown that if a system in this class is strongly minimum phase, in a sense specified in the paper, the problem of output regulation can be solved via partial-state feedback or via (dynamic) output feedback. The result substantially broadens the class of nonlinear MIMO systems for which the problem in question is known to be possibl
Optimal estimation in UDP-like networked control systems with intermittent inputs: stability analysis and suboptimal filter design
No full textWe investigate the optimal estimation problem in lossy networked control systems where the control packets are randomly dropped without acknowledgment to the estimator. Most existing results for this setup are concerned with the design of controller, while the optimal estimation and its performance evaluation have been rarely treated. In this paper, we show that, unlike many other cases such as intermittent observations or TCP-like systems, the system state follows a Gaussian mixture distribution with exponentially increasing terms, which leads to a Gaussian sum filter-based optimal estimation. We develop an auxiliary estimator method to establish necessary and sufficient conditions for the stability of the mean estimation error covariance matrices. It is revealed that the stability is independent of the packet loss rate, and is not affected by the lack of acknowledgment. A suboptimal filtering algorithm with improved computational efficiency is then developed. Numerical examples and simulations are employed to illustrate the theoretical results
Passivity-based non-fragile control for Markovian jump systems with aperiodic sampling
No full textIn this paper, the problem of non-fragile passive control for Markovian jump systems with aperiodic sampling is investigated. The considered controller is assumed to have either additive or multiplicative norm-bounded uncertainties. A time-dependent Lyapunov functional capturing the available information of the sampling pattern is constructed to derive a sufficient condition for non-fragile stochastic passivity of the resultant closed-loop system. Based on the condition, a mode-independent state feedback sampled-data controller is designed such that for all admissible uncertainties the closed-loop system is robustly stochastically passive. Two illustrative examples are included to demonstrate the effectiveness and merits of the proposed techniques
Stabilization by output feedback of multivariable invertible nonlinear systems
No full textIn this paper, the problem of global stabilization of a rather general class of MIMO nonlinear systems is addressed. The systems considered in the paper are invertible, have a trivial zero dynamics and possess a "normal form" in which certain multipliers are functions of the state vector of a special kind. While special structural dependence of such multipliers on the components state vector has been exploited before in the context of achieving stabilization (via full-state feedback, though), the novelty in the approach of this paper is that a peculiar structure is identified which happens to be intimately related to the property of uniform complete observability (thus making the design of observers possible) and to the property of uniform invertibility, relations never established before in the literature. As a result, for this class of MIMO nonlinear systems, a dynamic output feedback law can be designed, yielding semiglobal (and even global, under appropriate assumptions) asymptotic stability
Optimal estimation for networked control systems with intermittent inputs without acknowledgement
No full textThis paper investigates the optimal estimation problem for networked control systems, where the control packets are randomly dropped without acknowledgement to the estimator. Most existing results for this setup are concerned with the design of controller, while the optimal estimation and its performance evaluation have not been fully studied. This paper shows, unlike many other cases such as intermittent observations or TCP-like systems, the system state follows a Gaussian mixture distribution with exponentially increasing terms. The optimal estimation is obtained by Gaussian sum filtering, while the computation is time consuming. By constructing an auxiliary estimator, a fast and stable filtering algorithm is proposed to improve computational efficiency
Codiagnosability Analysis of Bounded Petri Nets
No full textIn this paper, we propose a novel approach to perform codiagnosability analysis of labeled bounded Petri nets. A set of sites observe the system evolution, each one with its own observation mask. Sites do not exchange information with each other but communicate with a coordinator. The coordinator is able to detect a fault if and only if at least one site is able to do that. In a previous work by some of us, it has been proven that a necessary and sufficient condition for codiagnosability under such a framework is the absence of sequences that are “ambiguous” with respect to all sites and whose length may grow indefinitely after the occurrence of some fault. The novelties of the approach consist in using the notion of basis markings to avoid exhaustive enumeration of the set of reachable markings, and in the construction of an automaton, called Verifier, that allows one to detect the presence of ambiguous sequences. Finally, we introduce the notion of K-codiagnosability: a system is K-codiagnosable if and only if faults can be detected in the above framework within at most K observations after their occurrence. An algorithm is provided to compute the smallest value of K such that the system is K-codiagnosable
High-gain observers with limited gain power for systems with observability canonical form
No full textInternational audienceWe consider the problem of state observation for systems having a well-defined observability canonical form (Gauthier and Kupka (2004)) by means of high-gain observers. The main goal is to show that, for this class of systems, observers can be designed with the high-gain parameter powered just up to the order 2 regardless the dimension of the state system. In this way we substantially overtake the main limitations of standard design procedures in which the high-gain parameter is powered up to the order of the system. The observer structure, which generalizes the ideas presented in Astolfi and Marconi (2015), can be used in all those contexts where fast state observation is required, such as in the design of output feedback stabilizers by means of the nonlinear separation principle that is also specifically addressed in the paper
H_infinity control for 2D Markov jump systems in Roesser model
No full textThis paper considers the problem of asynchronous H_infinity control for two-dimensional (2D) Markov jump systems. The underlying system is described based upon Roesser model. Specially, the hidden Markov model is employed when dealing with the asynchronization between controlled system and controller, and the relation between them is constructed through a conditional probability matrix. Based on Lyapunov function technique, the asymptotic mean square stability and H_infinity noise attenuation performance are investigated for the closed-loop 2D system. Moreover, the controller gain can be obtained by solving a convex optimization problem. An example is presented to show the effectiveness and potential of the proposed new design technique.</p
Optimal estimation and control for lossy network: stability, convergence, and performance
No full textIn this paper, we study the problems of optimal estimation and control, i.e., the linear quadratic Gaussian (LQG) control, for systems with packet losses but without acknowledgment. Such acknowledgment is a signal sent by the actuator to inform the estimator of the incidence of control packet losses. For such system, which is usually called as a user datagram protocol (UDP)-like system, the optimal estimation is nonlinear and its calculation is time-consuming, making its corresponding optimal LQG problem complicated. We first propose two conditions: 1) the sensor has some computation abilities; and 2) the control command, exerted to the plant, is known to the sensor. For a UDP-like system satisfying these two conditions, we derive the optimal estimation. By constructing the finite and infinite product probability measure spaces for the estimation error covariances (EEC), we give the stability condition for the expected EEC, and show the existence of a measurable function to which the EEC converges in distribution, and propose some practical methods to evaluate the estimation performance. Finally, the LQG controllers are derived, and the conditions for the mean square stability of the closed-loop system are established
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