107 research outputs found

    Verifiable Adaptive Control with Analytical Stability Margins by Optimal Control Modification

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    This paper presents a verifiable model-reference adaptive control method based on an optimal control formulation for linear uncertain systems. A predictor model is formulated to enable a parameter estimation of the system parametric uncertainty. The adaptation is based on both the tracking error and predictor error. Using a singular perturbation argument, it can be shown that the closed-loop system tends to a linear time invariant model asymptotically under an assumption of fast adaptation. A stability margin analysis is given to estimate a lower bound of the time delay margin using a matrix measure method. Using this analytical method, the free design parameter n of the optimal control modification adaptive law can be determined to meet a specification of stability margin for verification purposes

    Regression Filtration with Resetting to Provide Exponential Convergence of MRAC for Plants with Jump Change of Unknown Parameters

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    This paper proposes a new method to provide the exponential convergence of both the parameter and tracking errors of the composite adaptive control system without the requirement of the regressor persistent excitation (PE). Instead, the composite adaptation law obtained in this paper requires the regressor to be finitely exciting (FE) to guarantee the above-mentioned properties. Unlike known solutions, not only does it relax the PE requirement, but also it functions effectively under the condition of a jump change of the plant uncertainty parameters. To derive such an adaptation law, an integral filter of regressor with damping and resetting is proposed. It provides the required properties of the control system, and its output signal is bounded even when its input is subjected to noise and disturbances. A rigorous analytical proof of all mentioned properties of the developed adaptation law is presented. Such law is compared with the known composite ones relaxing the PE requirement. The wing-rock problem is used for the modeling of the developed composite MRAC system. The obtained results fully support the theoretical analysis and demonstrate the advantages of the proposed method.Comment: 12 pages, 3 figure

    M-MRAC With Normalization

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    This paper presents a normalization based modified reference model adaptive control method for multi-input multi-output (MIMO) uncertain systems in the presence of bounded external disturbances. It has been shown that desired tracking performance can be achieved for the system's output and input signals with the proper choice of design parameters. The resulting adaptive control signal satisfies a second order linear time invariant (LTI) system, which is the effect of the normalization term in the adaptive laws. This LTI system provides the guideline for the design parameter selection. The theoretical findings are confirmed via a simulation example

    Adaptive control design for nonlinear systems via successive approximations

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    The paper presents an approach to the Model Reference Adaptive Control (MRAC) design for nonlinear dynamical systems. A nonlinear reference system is considered such that its response is designed to be stable via Successive Approximation Approach (SAA). Having designed the stable reference model through the SAA, MRAC is then formulated for nonlinear plant dynamics with a new adaptation rule to guarantee the convergence of the nonlinear plant response to that of the response of the nonlinear reference model. The proposed design methodology is illustrated with examples for different case studies. Copyright © 2017 ASME

    Automatic Flight Control Systems

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    The history of flight control is inseparably linked to the history of aviation itself. Since the early days, the concept of automatic flight control systems has evolved from mechanical control systems to highly advanced automatic fly-by-wire flight control systems which can be found nowadays in military jets and civil airliners. Even today, many research efforts are made for the further development of these flight control systems in various aspects. Recent new developments in this field focus on a wealth of different aspects. This book focuses on a selection of key research areas, such as inertial navigation, control of unmanned aircraft and helicopters, trajectory control of an unmanned space re-entry vehicle, aeroservoelastic control, adaptive flight control, and fault tolerant flight control. This book consists of two major sections. The first section focuses on a literature review and some recent theoretical developments in flight control systems. The second section discusses some concepts of adaptive and fault-tolerant flight control systems. Each technique discussed in this book is illustrated by a relevant example

    A Robust Nonlinear Model Reference Adaptive Control for Disturbed Linear Systems: An LMI Approach

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    International audienceIn this paper a robust nonlinear Model Reference Adaptive Control (MRAC) is proposed for disturbed linear systems, i.e., linear systems with parameter uncertainties, and external time-dependent perturbations or nonlinear unmodeled dynamics matched with the control input. The proposed nonlinear control law is composed of two nonlinear adaptive gains. Such adaptive gains allow the control to counteract the effects of some perturbations and nonlinear unmodeled dynamics ensuring asymptotic convergence of the tracking error to zero, and the boundedness of the adaptive gains. The nonlinear controller synthesis is given by a constructive method based on the solution of Linear Matrix Inequalities (LMIs). Besides, the simulation results show that, due to the nonlinearities, the rate of convergence of the proposed algorithm is faster than the provided by a classic MRAC
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