Robust Output Feedback Controller Design Research Articles

Identification and robust control for systems with ellipsoidal parametric uncertainty by convex optimization

In this paper, sufficient conditions for robust output feedback controller design for systems with ellipsoidal parametric uncertainty are given in terms of solutions to a set of linear matrix inequalities (LMIs) Performance specifications are in terms of combined pole placement with sensitivity function shaping in the H2 or H∞ norm. Furthermore, an optimal input design technique for parameter estimation that is integrated into the robust control design is employed in this paper. This means that performance specifications on the closed-loop transfer functions are translated into the requirements on the input signal spectrum. The simulation results show the effectiveness of the proposed method. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society

Fixed-order robust H∞ control and control-oriented uncertainty set shaping for systems with ellipsoidal parametric uncertainty

In this paper, sufficient conditions for robust output feedback controller design for systems with ellipsoidal parametric uncertainty are given in terms of solutions to a set of linear matrix inequalities. A polynomial method is employed to design a fixed-order controller that assigns closed-loop poles within a given region of the complex plane and that satisfies an H∞ performance specification. The main feature of the proposed method is that it can be extended easily for control-oriented uncertainty set shaping using a standard input design approach. Consequently, the results can be extended to joint robust control/input design procedure whose controller structure and performance specifications are translated into the requirements on the input signal spectrum used in system identification. This way, model uncertainty set can be tuned for the robust control design procedure. The simulation results show the effectiveness of the proposed method. Copyright © 2010 John Wiley & Sons, Ltd.

Robust Output-Feedback MPC With Integral Action

In this paper, we propose a robust output-feedback model predictive control (MPC) design for a class of open-loop stable systems, having non-vanishing output disturbances, hard constraints and linear-time invariant model uncertainty. Integral action is included in the proposed design by utilizing a linear estimator for both the output disturbance and the system state. The main distinction from previous work on robust MPC design (with integral action) is that we establish robust convergence in the face of both imperfect state information and dynamic model uncertainty.

ROBUST OUTPUT FEEDBACK CONTROLLER DESIGN WITH COVARIANCE AND DISC CLOSED-LOOP POLE CONSTRAINTS

This paper is concerned with the problem of robust output feedback controller design for a class of linear discrete-time systems with normbounded uncertainty. The objective is to design a controller such that the closed-loop poles are assigned within a specified disc and the steady regulated output covariance is guaranteed to be less than a given upper bound. Using a linear matrix inequality (LMI) approach, the existence conditions of such controllers are derived, and a parametrized characterization of a set of desired controllers (if they exist) is presented in terms of the feasible solutions to a set of LMIs. A procedure is given to select a suitable output feedback controller that minimizes the desired control effort.

Robust adaptive control of uncertain non-linear systems using neural networks

This paper presents a robust adaptive output feedback control design method for uncertain non-affine non-linear systems, which does not rely on state estimation. The approach is applicable to systems with unknown but bounded dimensions and with known relative degree. A neural network is employed to approximate the unknown modelling error. In fact, a neural network is considered to approximate and adaptively make ineffective unknown plant non-linearities. An adaptive law for the weights in the hidden layer and the output layer of the neural network are also established so that the entire closed-loop system is stable in the sense of Lyapunov. Moreover, the robustness of the system against the approximation error of neural network is achieved with the aid of an additional adaptive robustifying control term. In addition, the tracking error is guaranteed to be uniformly and asymptotically stable, rather than uniformly ultimately bounded, by using this additional control term. The proposed control algorithm is relatively straightforward and no restrictive conditions on the design parameters for achieving the systems stability are required. The effectiveness of the proposed scheme is shown through simulations of a non-affine non-linear system with unmodelled dynamics, and is compared with a second-sliding mode controller.

Robust Output-Feedback MPC with Soft State Constraints

In this paper, we present a robust output-feedback model predictive control (MPC) design for a class of open-loop stable systems with hard input- and soft state constraints. The proposed output-feedback design is based on a linear state estimator and a novel parameterization of the soft state constraints that has the advantage of leading to optimization problems of prescribable size. Robustness against unstructured model uncertainty is obtained by choosing the cost function parameters so as to satisfy a linear matrix inequality condition. The robust output-feedback design incorporates a novel state-feedback design, which may be seen as a generalization of a previous proposal.

ROBUST OUTPUT FEEDBACK AFFINE QUADRATIC CONTROLLER DESIGN

The paper deals with the robust output feedback controller design with guaranteed cost and affine quadratic stability for linear continuous time systems. The proposed approach leads to an iterative LMI based algorithm. Numerical examples are studied to verify effectiveness of the proposed method. The obtained results are compared with some other design procedures for robust affine quadratic controller design and robust parameter-dependent quadratic stability.

Robust Output Feedback Control Synthesis: LMI Approach

The paper addresses the problem of robust output feedback controller design with a guaranteed cost and parameter dependent Lyapunov function quadratic stability for linear continuous time polytopic systems. The proposed design methods lead to a non-iterative LMI based algorithm. Numerical example is given to illustrate the design procedure.

Affine Robust Controller Design for Linear Parametric Uncertain Systems with Output Feedback

The paper deals with a new procedure for robust output feedback controller design providing affine quadratic stability. The developed procedure leads to a noniterative LMI based algorithm. The proposed affine robust controller applied to a plant consisting of two co-operating DC servomotors was evaluated using affine quadratic and quadratic stability test.

Robust Output Feedback Controller Design: LMI Approach

The paper addresses the problem of robust output feedback controller design with a guaranteed cost and quadratic, and parameter dependent Lyapunov function quadratic stability for linear continuous time affine systems. The proposed design methods lead to a non-iterative LMI based algorithm. Numerical examples are given to illustrate the design procedure.

DESIGN OF ROBUST OUTPUT AFFINE QUADRATIC CONTROLLER

The paper addresses the problem robust output feedback controller design with guaranteed cost and affine quadratic stability for linear continuous time affine systems. The proposed design method leads to a non-iterative LMI based algorithm. A numerical example is given to illustrate the design procedure.

Robust near-optimal output feedback control of non-linear systems

This work proposes a robust near-optimal non-linear output feedback controller design for a broad class of non-linear systems with time-varying bounded uncertain variables. Both vanishing and non-vanishing uncertainties are considered. Under the assumptions of input-to-state stable (ISS) inverse dynamics and vanishing uncertainty, a robust dynamic output feedback controller is constructed through combination of a high-gain observer with a robust optimal state feedback controller synthesized via Lyapunov's direct method and the inverse optimal approach. The controller enforces exponential stability and robust asymptotic output tracking with arbitrary degree of attenuation of the effect of the uncertain variables on the output of the closed-loop system, for initial conditions and uncertainty in arbitrarily large compact sets, provided that the observer gain is sufficiently large. Utilizing the inverse optimal control approach and singular perturbation techniques, the controller is shown to be near-optimal in the sense that its performance can be made arbitrarily close to the optimal performance of the robust optimal state feedback controller on the infinite time-interval by selecting the observer gain to be sufficiently large. For systems with non-vanishing uncertainties, the same controller is shown to ensure boundedness of the states, uncertainty attenuation and near-optimality on a finite time-interval. The developed controller is successfully applied to a chemical reactor example.

Robust controller design for uncertain systems with time delays: LMI approach

We present a robust output feedback controller design method for linear systems with norm-bounded time-varying parameter uncertainties and time-varying delays in both states and controls. And sufficient conditions for the existence of the robust output feedback controller of any order are given in terms of three linear matrix inequalities (LMIs). Furthermore, we provide a parameterization of all robust controllers from the positive-definite solutions of the LMIs.

Robust Output Feedback Control for Uncertain Dynamical Systems with Unknown Time Delays

This paper investigates robust output feedback controller design for a class of uncertain dynamical systems with unknown time delays. The uncertainties considered in this paper contain parametric uncertainties, unknown nonlinear functions, unknown time delays and unknown nonlinear functions. The problems of robust stabilization and robust H∞ performance are addressed. It is shown that the solutions to the above problems can be obtained from the solutions to algebraic Riccati inequalities. A numerical example indicates that the proposed robust controller can ensure the stability of the overall system.