Intelligent robust control design of a precise positioning system

This paper addresses an intelligent uncertainty function to improve the robust stability and performance of H _∞ controlled system in terms of reduced conservatism. The system is identified, output performance and control signal requirements are controlled by proper selection of performance and control weighting functions. Adaptive Neuro Fuzzy Inference System (ANFIS) learns the uncertainty bounds of model uncertainty that results from unmodeled dynamics and parameter variations, then the developed uncertainty weighting function will be included in the synthesis of the H _∞ controller. ν-gap measure is utilized to validate the intelligent identified uncertainty bounds and measure the stability of the designed H _∞ controlled system as well. Experimental results on a servo motion system reveal the advantages of combining intelligent uncertainty identification and robust control. Improved performance is achieved. The proposed approach also allows for iterative experiment design.     

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.     

MODEL SET IDENTIFICATION IN FREQUENCY-DOMAIN AND ITS APPLICATION TO JOINT DESIGN WITH ROBUST CONTROL

In this paper, we propose a new model set identification method for robust control, which determines both nominal models and uncertainty bounds in frequency-domain using periodgrams obtained from experimental data. This method also gives less conservative model sets when we have more experimental data, which is one of the distinguished features compared with the existing model set identification methods. To this end, first, we construct a new noise model set in terms of periodgrams, which consists of hard-bounded (or deterministic) noises but takes account of a low correlation property of noise signals, simultaneously. Then, based on the noise model, we show how to compute the nominal models and the upper bounds of modeling error via convex optimization, which minimize given cost functions. Furthermore, by introducing a weighting function compatible with control performance criterion into the identification cost function, we consider a joint design method of the proposed model set identification and H_∞ control. Numerical examples show the effectiveness of the proposed method.     

Static output-feedback of state-multiplicative systems with application to altitude control

A linear parameter dependent approach for designing a constant output-feedback controller for a linear time-invariant system with stochastic multiplicative Wiener-type noise, that achieves a minimum bound on either the stochastic H ₂ or the H _∞ performance level is introduced. A solution is achieved also for the case where in addition to the stochastic parameters, the system matrices reside in a given polytope. In this case, a parameter dependent Lyapunov function is introduced which enables the derivation of the required constant gain via a solution of a set of linear matrix inequalities that corresponds to the vertices of the uncertainty polytope.

The stochastic uncertainties appear in both the dynamic and the measurement matrices of the system. The problems are solved using the expected value of the standard performance index over the stochastic parameters. The theory developed is applied to an altitude control example.     

Robust H 2 Filtering for Discrete‐Time Markovian Jump Linear Systems

This paper studies the problems of H₂ filtering for discrete‐time Markovian jump linear systems with non‐accessible mode information. The objective is to design a less‐conservative mode‐independent H₂ filter such that the filtering error system is stochastically stable. To this end, sufficient conditions for the existence of an upper bound of H₂ norm are given in terms of linear matrix inequalities. With the introduction of a slack variable, a less‐conservative filter is derived. The proposed robust H₂ filter design method is also applicable to cover the cases where the system matrices are subject to polytopic uncertainty, as well as the case where the transition probability matrix is subject to a given polytopic uncertainty. Application of the proposed method to three examples from the literature demonstrates the favorable performance of the proposed solution to existing approaches.     

Iterative identification and control design with optimal excitation signals based on <Emphasis Type="Italic">υ</Emphasis>-gap

An iterative identification and control design method based on υ-gap is given to ensure the stability of closed-loop system and control performance improvement. The whole iterative procedure includes three parts: the optimal excitation signals design, the uncertainty model set identification and the stable controller design. Firstly the worst case υ-gap is used as the criterion of the optimal excitation signals design, and the design is performed via the power spectrum optimization. And then, an uncertainty model set is attained by system identification on the basis of the measure signals. The controller is designed to ensure the stability of closed-loop system and the closed-loop performance improvement. Simulation result shows that the proposed method has good convergence and closed-loop control performance. Supported by the National Natural Science Foundation of China (Grant Nos. 60574055, 60874073), the Specialized Research Fund for Doctoral Program of Higher Education of China (Grant No. 20050056037), and the Tianjin Science and Technology Keystone Project (Grant No. 08ZCKFJC27900)     

Static and output-feedback of discrete-time LTI systems with state multiplicative noise

A parameter dependent approach for designing static output-feedback controller for linear time-invariant systems with state-multiplicative noise is introduced which achieves a minimum bound on either the stochastic H₂ or the H_∞ performance levels. A solution is obtained also for the case where, in addition to the stochastic parameters, the system matrices reside in a given polytope. In this case, a parameter dependent Lyapunov function is described which enables the derivation of the required constant feedback gain via a solution of a set of linear matrix inequalities that correspond to the vertices of the uncertainty polytope.The stochastic parameters appear in both the dynamics and the input matrices of the state space model of the system. The problems are solved using the expected value of the standard performance indices over the stochastic parameters. The theory developed is demonstrated by a simple example.     

Robust H∞ control for uncertain discrete singular systems with pole placement in a disk

This paper addresses the design of robust H_∞ controllers for uncertain discrete singular systems with time-invariant uncertainty in both the state and measurement matrices. The singular system to be controlled is not assumed to be regular. A regular dynamic output feedback controller is designed such that a prescribed H_∞ performance condition is satisfied and the closed-loop poles are placed in a specified disk while the regularity, causality and stability of the closed-loop system can be guaranteed for all admissible uncertainties. The desired controller can be obtained by solving a set of matrix inequalities. A numerical example is given to demonstrate the application of the proposed method.     

LMI optimization approach to robust H∞ observer design and static output feedback stabilization for discrete‐time nonlinear uncertain systems

A new approach for the design of robust H_∞ observers for a class of Lipschitz nonlinear systems with time‐varying uncertainties is proposed based on linear matrix inequalities (LMIs). The admissible Lipschitz constant of the system and the disturbance attenuation level are maximized simultaneously through convex multiobjective optimization. The resulting H_∞ observer guarantees asymptotic stability of the estimation error dynamics and is robust against nonlinear additive uncertainty and time‐varying parametric uncertainties. Explicit norm‐wise and element‐wise bounds on the tolerable nonlinear uncertainty are derived. Also, a new method for the robust output feedback stabilization with H_∞ performance for a class of uncertain nonlinear systems is proposed. Our solution is based on a noniterative LMI optimization and is less restrictive than the existing solutions. The bounds on the nonlinear uncertainty and multiobjective optimization obtained for the observer are also applicable to the proposed static output feedback stabilizing controller. Copyright © 2008 John Wiley & Sons, Ltd.     

Robust H2/H∞ control for time‐delay systems with polytopic uncertainty

In this paper, new separated H_∞ and H₂ performance criteria are derived for a class of time‐delay systems. When used in robust performance analysis and synthesis for real polytopic uncertainty and in multiobjective controller synthesis, they can partially rule out the technical restriction of using a single Lyapunov function, and therefore, lead to potentially less conservative linear matrix inequality (LMI) characterizations. Based on the criteria, robust multiobjective H₂/H_∞ controller is designed for time‐delay systems with polytopic uncertainty. All the conditions are given in terms of LMIs. Numerical examples are given to illustrate the proposed method. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

H∞ fuzzy control of semi-Markov jump nonlinear systems under σ-error mean square stability

This paper is concerned with the problem of time-varying H_∞ fuzzy control for a class of semi-Markov jump nonlinear systems in the sense of σ-error mean square stability. The nonlinear plant is described via the Takagi–Sugeno fuzzy model. By defining a time-varying mode-dependent Lyapunov function, a set of sufficient stability and stabilisation criteria for non-disturbance case is first derived and then applied to the investigation of H_∞ performance analysis and H_∞ fuzzy controller design problems of semi-Markov jump nonlinear systems. Different from the traditional stochastic switching system framework, the probability density function of sojourn time is exploited to circumvent the complex computation of transition probabilities. The derived conditions can cover the time-invariant mode-dependent and time-invariant mode-independent H_∞ fuzzy control schemes as special cases. A classic cart-pendulum system is presented to demonstrate the effectiveness and advantages of the proposed theoretical results.     

H∞ bumpless transfer for switched LPV systems and its application

In this paper, the approach of the control bumps limitation is generalised and applied to the problem of H _∞ bumpless transfer for a class of switched linear parameter-varying (LPV) systems. The H _∞ bumpless transfer problem is to design a controller with the amplitude limitation and a parameter and modes-dependent switching law to reduce control bumps of the switched LPV systems and satisfy an H _∞ performance index. The key point is to guarantee the bumps limitation constraint of the switched LPV systems by dual design of controllers and a switching law, even though the constraint for each subsystem is unsatisfied. First, a set of switching signals depending on parameters and modes are designed, and a family of switched LPV controllers with the bumps limitation objective are developed via multiple parameter-dependent Lyapunov functions. Then, a sufficient condition ensuring the H _∞ bumpless transfer performance for a switched LPV system is presented in the format of numerically tractable conditions. Finally, the effectiveness of the proposed control design scheme is illustrated by its application to the control design of an aero-engine.     

Sensor fault diagnosis of singular delayed LPV systems with inexact parameters: an uncertain system approach

In this paper, sensor fault diagnosis of a singular delayed linear parameter varying (LPV) system is considered. In the considered system, the model matrices are dependent on some parameters which are real-time measurable. The case of inexact parameter measurements is considered which is close to real situations. Fault diagnosis in this system is achieved via fault estimation. For this purpose, an augmented system is created by including sensor faults as additional system states. Then, an unknown input observer (UIO) is designed which estimates both the system states and the faults in the presence of measurement noise, disturbances and uncertainty induced by inexact measured parameters. Error dynamics and the original system constitute an uncertain system due to inconsistencies between real and measured values of the parameters. Then, the robust estimation of the system states and the faults are achieved with H_∞ performance and formulated with a set of linear matrix inequalities (LMIs). The designed UIO is also applicable for fault diagnosis of singular delayed LPV systems with unmeasurable scheduling variables. The efficiency of the proposed approach is illustrated with an example.     

Robust filtering for a class of discrete-time uncertain nonlinear systems: An H∞ approach

This paper deals with the H_∞ filtering problem for a class of discrete-time nonlinear systems with or without real time-varying parameter uncertainty and unknown initial state. For the case when there is no parametric uncertainty in the system, we are concerned with designing a nonlinear H_∞ filter such that the induced l₂ norm of the mapping from the noise signal to the estimation error is within a specified bound. It is shown that this problem can be solved via one Riccati equation. We also consider the design of nonlinear filters which guarantee a prescribed H_∞ performance in the presence of parametric uncertainties. In this situation, a solution is obtained in terms of two Riccati equations.     

Robust Analysis of Discrete‐Time Lur'e Systems with Slope Restrictions Using Convex Optimization

This paper considers robust stability and robust performance analysis for discrete‐time linear systems subject to nonlinear uncertainty. The uncertainty set is described by memoryless, time‐invariant, sector bounded, and slope restricted nonlinearities. We first give an overview of the absolute stability criterion based on the Lur'e‐Postkinov Lyapunov function, along with a frequency domain condition. Subsequently, we derive sufficient conditions to compute the upper bounds of the worst case H₂ and worst case H∞ performance. For both robust stability testing and robust performance computation, we show that these sufficient conditions can be readily and efficiently determined by performing convex optimization over linear matrix inequalities.     

Sojourn-probability-dependent H∞ control for networked switched systems under asynchronous switching

This paper considers H_∞ controller design for a class of networked switched discrete systems under asynchronous switching. The sojourn probability information – the probability of the switched systems staying in each subsystem – is first used to rebuild the networked switched systems. Also, a time-varying lag, depending on both the network-induced delays and switching signals, is taken into consideration between the switching instants of the controllers and systems model. By considering both sojourn probability information and asynchronous switching, a new kind of networked switched system model is proposed, wherein a set of random variables are proposed to describe the sojourn probabilities of the subsystems. Then, stability analysis and H_∞ performance analysis under asynchronous switching are derived. It should be noted that the system performance depends not only on the time-varying lag, but also on the sojourn probabilities. Finally, an example is given to illustrate the effectiveness of the proposed approach.     

Takagi–Sugeno Fuzzy Hopfield Neural Networks for $${\mathcal{H}_{\infty}}$$ Nonlinear System Identification

In this paper, we propose a new H_￥{\mathcal H_\infty} weight learning algorithm (HWLA) for nonlinear system identification via Takagi–Sugeno (T–S) fuzzy Hopfield neural networks with time-delay. Based on Lyapunov stability theory, for the first time, the HWLA for nonlinear system identification is presented to reduce the effect of disturbance to an H_￥{\mathcal{H}_{\infty }} norm constraint. The HWLA can be obtained by solving a convex optimization problem which is represented in terms of linear matrix inequality (LMI). An illustrative example is given to demonstrate the effectiveness of the proposed identification scheme.     

Robust H∞ dynamic output feedback control for spacecraft rendezvous with poles and input constraint

This paper is concerned with the output feedback control problem for spacecraft rendezvous subject to target angular velocity uncertainty and controller uncertainty, external disturbance and input constraint. A general full-order dynamic output feedback (DOF) controller is proposed. As a stepping-stone, the H_∞ performance requirement, poles and input constraint are analysed separately via linear matrix inequalities (LMIs). Then, with the obtained results, the controller design problem is cast into a convex problem subject to a set of LMI constraints through a critical change of controller variables. Furthermore, when the system states are all available, a reduced sufficient condition of the non-fragile state feedback controller is given. Compared with existing results, the designed controller has overcome the disadvantage of strictly proper DOF controller, where the initial value of the control input is zero. Besides, the constraint on poles placement is relaxed. A numerical simulation is performed to verify the effectiveness of the proposed method.     

H∞ output tracking control for a class of switched LPV systems and its application to an aero‐engine model

This paper aims to investigate the problem of H_∞ output tracking control for a class of switched linear parameter‐varying (LPV) systems. A sufficient condition ensuring the H_∞ output tracking performance for a switched LPV system is firstly presented in the format of linear matrix inequalities. Then, a set of parameter and mode‐dependent switching signals are designed, and a family of switched LPV controllers are developed via multiple parameter‐dependent Lyapunov functions to enhance control design flexibility. Even though the H_∞ output tracking control problem for each subsystem might be unsolvable, the problem for switched LPV systems is still solved by the designed controllers and the designed switching law. Finally, the effectiveness of the proposed control design scheme is illustrated by its application to an H_∞ speed adjustment problem of an aero‐engine. Copyright © 2016 John Wiley & Sons, Ltd.