Lyapunov-based adaptive control pdf

In control theory, a controllyapunov function is a lyapunov function for a system with control inputs. Adaptive integrated guidance and control for impact angle constrained interception with actuator saturation. Lyapunovbased robust and adaptive control of nonlinear. Reinforcement learning for optimal feedback control develops modelbased and datadriven reinforcement learning methods for solving optimal control problems in nonlinear deterministic dynamical systems. The typical adaptive control methods cannot be applied. This study designs a control of twodegree of freedom lower limb rehabilitation robot llrr for the patient who needs the proper physical therapy after a spinal cord injury sci, stroke, or a surgical operation. Design and applications crc press, boca raton, 2009. At the higher layer of the structure, a lyapunovbased backstepping regulator including adaptive estimation of uncertain parameters and friction force is. This book provides a practical yet rigorous development of nonlinear, lyapunovbased. International journal of adaptive control and signal processing. This thesis presents the theoretical development, simulation study and flight tests of a lyapunovbased control approach for the fault tolerant control ftc of a quadrotor unmanned aerial vehicle uav. For multiinput multioutput mimo linear systems, a complete generalization of the lyapunovbased direct adaptive control has been achieved for the case of the relative degree one 9, 10. Lyapunovbased controller for a class of stochastic. Lyapunovbased robust and adaptive control of nonlinear systems using a novel feedback structure by parag patre august 2009 chair.

A lyapunovbased approach for the control of biomimetic robotic systems with periodic forcing inputs domenico campolo. Mechanical engineering the focus of this research is an examination of the interplay between di. Evaluation of lyapunovbased adaptive observer using low. Lyapunovbased dynamic neural network for adaptive control of complex systems. Adaptive stabilization and aeifs our approach is to replace the problem of adaptive stabilization of 1. Adaptive lyapunovbased control of a robot and massspring. Pdf on the lyapunovbased adaptive control redesign for. He estimationbased approach to adaptive control has been extremely successful in linear systems. Adaptive control and signal processing invited paper for the special issue. Lyapunov based adaptive control of a mems gyroscope. Yields closedloop asymptotic tracking with all remaining. Stability and optimality of feedback dynamical systems 411 chapter 7. A direct adaptive nonlinear control framework for discretetime multivariable nonlinear uncertain systems with exogenous bounded disturbances is developed. Reinforcement learning for optimal feedback control a.

Lyapunovbased adaptive control of mimo systems ramon r. The research is focused on the development and application of a lyapunovbased control methodology, which incorporates the full nonlinear system dynamics in the design and analysis without requiring the solution of the nonlinear equations of motion. Lyapunovbased impact time control guidance laws against stationary targets. This paper proposes a hierarchical lyapunovbased adaptive cascade control scheme for a lowerlimb exoskeleton with control saturation.

November 14, 2003 lyapunovbased distributed control of. A lyapunovbase training algorithm is proposed and used to adjust online the network. Click download or read online button to nonlinearcontrolofengineeringsystems. Arts lab, scuola superiore santanna, pisa, italy department of information engineering, univ. Lyapunovbased control of mechanical systems applied. Lyapunov based adaptive control method for hydraulic servo. Download nonlinearcontrolofengineeringsystemsalyapunovbasedapproachcontrolengineering ebook pdf or read online books in pdf, epub, and mobi format. Huazhong university of science and technology, 2011 a dissertation submitted in partial ful. Robust adaptive control scheme is presented for robotic manipulators. The control strategy is designed in the framework of the lyapunov theory, and adaptive. Since real chaotic systems have undesired randomlike behaviors which have also been deteriorated by environmental noise, chaotic systems are modeled by exciting a deterministic chaotic system with a white noise obtained from derivative of wiener process which. The design of modelreference adaptive control mrac for mimo linear systems has not yet been. Stability theory for nonlinear dynamical systems 5 chapter 4.

A lyapunovbased adaptive control framework for discrete. To the best of our knowledge, lyapunov based model reference adaptive controller design for a class of nonlinear n. This method of developing adaptive laws is based on the direct method of lyapunov and its relationship with positive real. Advances in stability analysis for model reference adaptive control.

A hierarchical lyapunovbased cascade adaptive control scheme. Initiated by butchart and shackcloth 1965, and forcefully articulated by parks 1966, the lyapunovbased adaptive design is one of the early applications of the celebrated strict positive real lemma. Pdf control has been used in the past to control bioreactors in 12, as an alternative to conventional pid controllers. A lyapunovbased adaptive control framework for discretetime nonlinear systems with exogenous disturbances tomohisa hayakaway, wassim m. In this paper, an adaptive neurocontrol structure for complex dynamic system is proposed. Imai a, petar kokotovi c b a department of electrical engineering, coppeufrj, p. Pdf the design of modelreference adaptive control for mimo linear systems has not yet achieved, in spite of significant efforts, the. Lyapunovbased nonlinear missile guidance journal of. International journal of adaptive control and signal processing int. Mppt problems in pv systems a novel and control theoretic alternative to traditional mppt methods.

Melkote, modeling and adaptive nonlinear control of electric motors springerverlag, berlin, 2003. Lyapunovbased adaptive control for the permanent magnet. Dynamical system theory lies at the heart of mathematical sciences and engineering. A recurrent neural network is trainedoffline to learn. Nonlinear dynamical systems and control presents and develops an extensive treatment of stability analysis and control design of nonlinear dynamical systems, with an emphasis on lyapunovbased methods. The ordinary lyapunov function is used to test whether a dynamical system is stable more restrictively, asymptotically stable. The direct adaptive approach is performed after the training process is achieved. The theoretical framework of the proposed adaptive mpc is enlightened by lyapunovbased mpc 4, 20, where control lyapunov function is constructed and regarded as an extra nonlinear constraint. This paper addresses the directional control problem of autonomous air vehicles in order to obtain trajectory tracking capabilities when flying in other than calm conditions. Section 2 describes the extremum seeking control design and our novel lyapunovbased switching strategy. Lyapunovbased robust and adaptive control design for. Lyapunov based model reference adaptive control for aerial. In order to achieve learning under uncertainty, datadriven methods for identifying system models in realtime are also developed.

Lyapunovbased tracking control in the presence of uncertain nonlinear parameterizable friction. Download pdf nonlinearcontrolofengineeringsystemsa. Lyapunovbased adaptive feedback for spacecraft planar. This paper proposes a hierarchical lyapunovbased adaptive cascade control scheme for a lowerlimb exoskeleton. Lyapunovbased nonlinear control networked systems and. Recent advancements in lyapunovbased design and analysis techniques have applications to a broad class of engineering systems, including mechanical, electrical, robotic, aerospace, and underactuated systems.

Lyapunovbased adaptive control of mimo systems request pdf. Nonlinear control of engineering systems a lyapunov. A recurrent neural network is trainedoffline to learn the inverse dynamics of the system from the observation of the inputoutput data. It is well known that every mechanical appliances behavior noticeably depends on environmental changes, functioningmode parameter changes and changes in technical characteristics of internal functional devices. Lyapunovbased model reference adaptive controller design for a. Robust adaptive lyapunovbased robot control springerlink. Although discontinuous impact models with impulsive ve. Lyapunov based optimal control of a class of nonlinear systems by hassan zargarzadeh a dissertation. The effects of parametric and dynamic uncertainties in the robot mathematical model are suppressed by adaptive control scheme which ensures that the stability measure of nominal system will increase in time until there are no transient processes.

Lyapunov based model reference adaptive control for aerial manipulation matko orsag, christopher korpela, stjepan bogdan, and paul oh abstractthis paper presents a control scheme to achieve dynamic stability in an aerial vehicle with dual multidegree of freedom manipulators using a lyapunov based model reference adaptive control. Research in adaptive control of mimo linear systems continues to be active. Request pdf lyapunov based adaptive control of a mems gyroscope we present an adaptive controller to control all modes of a vibrational mems gyroscope. Nonaffine controls excluded from linearizing state feedback. As a result of our design, boundedness of all signals in the closedloop in the presence of parametric uncertainties is guaranteed. Since most practical scenarios require the design of nonlinear controllers to work around uncertainty and measurementrelated issues, the authors use lyapunovs direct method as an effective tool to design and. Lyapunovbased control of robotic systems describes nonlinear control design solutions for problems that arise from robots required to interact with and manipulate their environments. The application of dynamical systems has crossed interdisciplinary boundaries from chemistry to. Lyapunov based robust control for tracking control of. The adaptive nonlinear controller addresses adaptive stabilization, disturbance rejection and adaptive tracking. The proposed framework is lyapunovbased and guarantees partial asymptotic stability of the closedloop system. Lyapunov based optimal control of a class of nonlinear systems. Lyapunovbased switched extremum seeking for photovoltaic. Using the lyapunov stability theory, the controller is proven.

On the lyapunovbased adaptive control redesign for a class of nonlinear sampleddata systems. The proposed approach is composed by two control levels with cascade structure. Lyapunovbased fault tolerant control of quadrotor unmanned aerial vehicles. Dynamical systems and differential equations 9 chapter 3. Lyapunovbased robust and adaptive control design for nonlinear uncertain systems by kun zhang b. The robot manipulator can perform specified passive exercises as well as copy exercise motions and perform them without the physiotherapist. Adaptive control of a spacecraft formation system is considered in 11, 3032. Lyapunovbased robust and adaptive control of nonlinear systems using a novel feedback structure creator. A hierarchical lyapunovbased cascade adaptive control.

The standard lyapunov stability theorem is not enough, and we need to work with a weak. Dupree et al adaptive lyapunovbased control of a robot 1051 developed in 20 that establishes a stable contact and achieves the desired dynamics for contact or noncontact conditions. In con trast to the lyapunovbased approach, which restricts the choice of parameter update laws and controller structures, the estimationbased designs are versatile. Lyapunovbased dynamic neural network for adaptive control. Proceedings of the american control conference chicago, illinois june 2000 optimal lyapunovbased backward horizon adaptive stabilization ravinder venugopal, venkatesh g. Lyapunovbased model reference adaptive controller design. Lyapunov based adaptive observers and the kalman lter are widely used for the estimation of state and parameters. Section 3 discusses a case study of the proposed es method on mppt for pv systems. Lyapunovbased backwardhorizon adaptive stabilization. This study presents a general control law based on lyapunovs direct method for a group of wellknown stochastic chaotic systems. Specifically, the robust adaptive control method, a gradientbased desired compensation adaptation law dcal, and a lyapunovkravoskii lk functionalbased delay control term are utilized to compensate for unknown timedelays, linearly parameterizable uncertainties, and additive bounded disturbances for a general nonlinear system.

Design of adaptive threeterm controllers for unstable. Khalil, nonlinear systems, prenticehall, 2002 third edition. Lyapunovbased adaptive control of mimo systems ieee xplore. Dissipativity theory for nonlinear dynamical systems 325 chapter 6. Adaptive control systems are one of the most significant research directions of modern control theory. To compensate for the uncertainty in the infection parameter of the model an estimator based on a control lyapunov function is designed. A lyapunovbased adaptive control framework for discretetime non. Haddady and alexander leonessaz a direct adaptive nonlinear control framework for discretetime multivariable nonlinear uncertain systems with exogenous bounded disturbances is developed. Pdf in this paper, an adaptive neuro control structure for complex dynamic system is proposed. Except for an additional feedforward term, the proposed control strategy is similar to that reported in 11 and called the pseudoderivative feedback control pdf.

The nonadaptive part of the proposed controller is based on nonlinear dynamic inversion. Lyapunovbased control of mechanical systems is a very valuable addition to the literature on control of mechanical systems, nonlinear control methods, adaptive control, and control of the infinite dimensional systems. Pdf lyapunovbased dynamic neural network for adaptive. Adaptive nonlinear design with controlleridentifier. Lyapunovbased control of robotic systems automation and. Blaschke, the principle of field orientation as applied to the new transvector. The stateofthe art solution presented uses robust and adaptive control design ideas in an integrated.

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