3,445 research outputs found

    Quantized output feedback stabilization by Luenberger observers

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    We study a stabilization problem for systems with quantized output feedback. The state estimate from a Luenberger observer is used for control inputs and quantization centers. First we consider the case when only the output is quantized and provide data-rate conditions for stabilization. We next generalize the results to the case where both of the plant input and output are quantized and where controllers send the quantized estimate of the plant output to encoders as quantization centers. Finally, we present the numerical comparison of the derived data-rate conditions with those in the earlier studies and a time response of an inverted pendulum.Comment: 8 pages, 5 figures, to appear in Proc. IFAC WC 201

    Stabilization of discrete-time piecewise affine systems with quantized signals

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    This paper studies quantized control for discrete-time piecewise affine systems. For given stabilizing feedback controllers, we propose an encoding strategy for local stability. If the quantized state is near the boundaries of quantization regions, then the controller can recompute a better quantization value. For the design of quantized feedback controllers, we also consider the stabilization of piecewise affine systems with bounded disturbances. In order to derive a less conservative design method with low computational cost, we investigate a region to which the state belong in the next step.Comment: To be presented at IEEE CDC 201

    Stabilization of continuous-time switched linear systems with quantized output feedback

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    In this paper, we study the problem of stabilizing continuous-time switched linear systems with quantized output feedback. We assume that the observer and the control gain are given for each mode. Also, the plant mode is known to the controller and the quantizer. Extending the result in the non-switched case, we develop an update rule of the quantizer to achieve asymptotic stability of the closed-loop system under the average dwell-time assumption. To avoid quantizer saturation, we adjust the quantizer at every switching time.Comment: This journal-version paper is based on the conference paper (arXiv:1403.4670

    A Characterization of the Minimal Average Data Rate that Guarantees a Given Closed-Loop Performance Level

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    This paper studies networked control systems closed over noiseless digital channels. By focusing on noisy LTI plants with scalar-valued control inputs and sensor outputs, we derive an absolute lower bound on the minimal average data rate that allows one to achieve a prescribed level of stationary performance under Gaussianity assumptions. We also present a simple coding scheme that allows one to achieve average data rates that are at most 1.254 bits away from the derived lower bound, while satisfying the performance constraint. Our results are given in terms of the solution to a stationary signal-to-noise ratio minimization problem and builds upon a recently proposed framework to deal with average data rate constraints in feedback systems. A numerical example is presented to illustrate our findings.Comment: Submitted to IEEE Transactions on Automatic Control on December 26, 201

    Parametrization of completeness in symbolic abstraction of bounded input linear systems

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    A good state-time quantized symbolic abstraction of an already input quantized control system would satisfy three conditions: proximity, soundness and completeness. Extant approaches for symbolic abstraction of unstable systems limit to satisfying proximity and soundness but not completeness. Instability of systems is an impediment to constructing fully complete state-time quantized symbolic models for bounded and quantized input unstable systems, even using supervisory feedback. Therefore, in this paper we come up with a way of parametrization of completeness of the symbolic model through the quintessential notion of Trimmed-Input Approximate Bisimulation which is introduced in the paper. The amount of completeness is specified by a parameter called trimming of the set of input trajectories. We subsequently discuss a procedure of constructing state-time quantized symbolic models which are near-complete in addition to being sound and proximate with respect to the time quantized models

    Stabilization of uncertain systems using quantized and lossy observations and uncertain control inputs

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    In this paper, we consider a stabilization problem of an uncertain system in a networked control setting. Due to the network, the measurements are quantized to finite-bit signals and may be randomly lost in the communication. We study uncertain autoregressive systems whose state and input parameters vary within given intervals. We derive conditions for making the plant output to be mean square stable, characterizing limitations on data rate, packet loss probabilities, and magnitudes of uncertainty. It is shown that a specific class of nonuniform quantizers can achieve stability with a lower data rate compared with the common uniform one

    Stability analysis of sampled-data switched systems with quantization

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    We propose a stability analysis method for sampled-data switched linear systems with finite-level static quantizers. In the closed-loop system, information on the active mode of the plant is transmitted to the controller only at each sampling time. This limitation of switching information leads to a mode mismatch between the plant and the controller, and the system may become unstable. A mode mismatch also makes it difficult to find an attractor set to which the state trajectory converges. A switching condition for stability is characterized by the total time when the modes of the plant and the controller are different. Under the condition, we derive an ultimate bound on the state trajectories by using a common Lyapunov function computed from a randomized algorithm. The switching condition can be reduced to a dwell-time condition.Comment: This journal-version paper is based on the conference paper (arXiv:1403.4691

    Stabilization of Networked Control Systems under DoS Attacks and Output Quantization

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    This paper addresses quantized output feedback stabilization under Denial-of-Service (DoS) attacks. First, assuming that the duration and frequency of DoS attacks are averagely bounded and that an initial bound of the plant state is known, we propose an output encoding scheme that achieves exponential convergence with finite data rates. Next we show that a suitable state transformation allows us to remove the assumption on the DoS frequency. Finally, we discuss the derivation of state bounds under DoS attacks and obtain sufficient conditions on the bounds of DoS duration and frequency for achieving Lyapunov stability of the closed-loop system.Comment: We have added new results in Sections 3.6 and

    Disturbance-to-State Stabilization and Quantized Control for Linear Hyperbolic Systems

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    We consider a system of linear hyperbolic PDEs where the state at one of the boundary points is controlled using the measurements of another boundary point. Because of the disturbances in the measurement, the problem of designing dynamic controllers is considered so that the closed-loop system is robust with respect to measurement errors. Assuming that the disturbance is a locally essentially bounded measurable function of time, we derive a disturbance-to-state estimate which provides an upper bound on the maximum norm of the state (with respect to the spatial variable) at each time in terms of L∞\mathcal{L}^\infty-norm of the disturbance up to that time. The analysis is based on constructing a Lyapunov function for the closed-loop system, which leads to controller synthesis and the conditions on system dynamics required for stability. As an application of this stability notion, the problem of quantized control for hyperbolic PDEs is considered where the measurements sent to the controller are communicated using a quantizer of finite length. The presence of quantizer yields practical stability only, and the ultimate bounds on the norm of the state trajectory are also derived.Comment: Some minor errors in the derivations have been corrected, and the references have been update

    Coordination Over Multi-Agent Networks With Unmeasurable States and Finite-Level Quantization

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    In this note, the coordination of linear discrete-time multi-agent systems over digital networks is investigated with unmeasurable states in agents' dynamics. The quantized-observer based communication protocols and Certainty Equivalence principle based control protocols are proposed to characterize the inter-agent communication and the cooperative control in an integrative framework. By investigating the structural and asymptotic properties of the equations of stabilization and estimation errors nonlinearly coupled by the finite-level quantization scheme, some necessary conditions and sufficient conditions are given for the existence of such communication and control protocols to ensure the inter-agent state observation and cooperative stabilization. It is shown that these conditions come down to the simultaneous stabilizability and the detectability of the dynamics of agents and the structure of the communication network.Comment: 10 pages, 2 figure
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