Non-fragile robust optimal guaranteed cost control of uncertain 2-D discrete state-delayed systems

This paper is concerned with the problem of non-fragile robust optimal guaranteed cost control for a class of uncertain two-dimensional (2-D) discrete state-delayed systems described by the general model with norm-bounded uncertainties. Our attention is focused on the design of non-fragile state feedback controllers such that the resulting closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound for all admissible parameter uncertainties and controller gain variations. A sufficient condition for the existence of such controllers is established under the linear matrix inequality framework. Moreover, a convex optimisation problem is proposed to select a non-fragile robust optimal guaranteed cost controller stabilising the 2-D discrete state-delayed system as well as achieving the least guaranteed cost for the resulting closed-loop system. The proposed method is compared with the previously reported criterion. Finally, illustrative examples are given to show the potential of the proposed technique.     

Guaranteed cost repetitive control for uncertain discrete-time systems

This paper considers the problem of guaranteed cost repetitive control for uncertain discrete-time systems. The uncertainty in the system is assumed to be norm-bounded and time-varying. The objective is to develop a novel design method for the repetitive control systems by introducing a robust output feedback controller so that the closed-loop system is quadratically stable and a certain bound of performance index is guaranteed for all admissible uncertainties. Necessary and sufficient conditions for the existence of such controllers are derived in terms of linear matrix inequality (LMI). A suboptimal guaranteed cost controller is obtained by solving an optimization problem with LMI constraints. Finally, a simulation example is provided to illustrate the validity of the proposed method.     

Robust Control System Design for an Uncertain Nonlinear System Using Minimax LQG Design Method

A systematic approach to design a nonlinear controller using minimax linear quadratic Gaussian regulator (LQG) control is proposed for a class of multi‐input multi‐output nonlinear uncertain systems. In this approach, a robust feedback linearization method and a notion of uncertain diffeomorphism are used to obtain an uncertain linearized model for the corresponding uncertain nonlinear system. A robust minimax LQG controller is then proposed for reference command tracking and stabilization of the nonlinear system in the presence of uncertain parameters. The uncertainties are assumed to satisfy a certain integral quadratic constraint condition. In this method, conventional feedback linearization is used to cancel nominal nonlinear terms and the uncertain nonlinear terms are linearized in a robust way. To demonstrate the effectiveness of the proposed approach, a minimax LQG‐based robust controller is designed for a nonlinear uncertain model of an air‐breathing hypersonic flight vehicle (AHFV) with flexibility and input coupling. Here, the problem of constructing a guaranteed cost controller which minimizes a guaranteed cost bound has been considered and the tracking of velocity and altitude is achieved under inertial and aerodynamic uncertainties.     

Non-monotonic robust H2 fuzzy observer-based control for discrete time nonlinear systems with parametric uncertainties

A non-monotonic Lyapunov function (NMLF) is deployed to design a robust H₂ fuzzy observer-based control problem for discrete-time nonlinear systems in the presence of parametric uncertainties. The uncertain nonlinear system is presented as a Takagi and Sugeno (T–S) fuzzy model with norm-bounded uncertainties. The states of the fuzzy system are estimated by a fuzzy observer and the control design is established based on a parallel distributed compensation scheme. In order to derive a sufficient condition to establish the global asymptotic stability of the proposed closed-loop fuzzy system, an NMLF is adopted and an upper bound on the quadratic cost function is provided. The existence of a robust H₂ fuzzy observer-based controller is expressed as a sufficient condition in the form of linear matrix inequalities (LMIs) and a sub-optimal fuzzy observer-based controller in the sense of cost bound minimization is obtained by utilising the aforementioned LMI optimisation techniques. Finally, the effectiveness of the proposed scheme is shown through an example.     

Information fusion robust guaranteed cost Kalman estimators with uncertain noise variances and missing measurements

ABSTRACT

For multisensor systems with uncertain noise variances and missing measurements, it can be converted into one only with uncertain noise variances by introducing fictitious measurement white noises. According to the minimax robust estimation principle and parameterisation representation of perturbances of uncertain noise variances, based on the worst-case system with conservative upper bounds of uncertain noise variances, the two classes of guaranteed cost robust weighted fusion Kalman estimators with matrix weights, diagonal matrix weights, scalar weights, and covariance intersection fusion matrix weights are presented. One class is the construction of a maximal perturbance region of uncertain noise variances, in which for all admissible perturbances, the accuracy deviations are guaranteed to remain within the prescribed range. The other class is the finding of minimal upper bound and maximal lower bound of accuracy deviations over the given perturbance region of uncertain noise variances. Two problems can be converted into the optimisation problems with constraints. Their optimal analytical solutions can simply be found respectively by the Lagrange multiplier method and the linear programme method. The guaranteed cost robustness is proved by the Lyapunov equation approach. A simulation example applied to the mass-spring system is provided to demonstrate the correctness and effectiveness of the proposed results.     

Robust reliability method for non-fragile guaranteed cost control of parametric uncertain systems

The problem of non-fragile guaranteed cost control of uncertain systems is studied from a new point of view of reliability against uncertainties. An efficient robust reliability method for the analysis and design of non-fragile guaranteed cost controller of parametric uncertain systems is presented systematically. By the method, a robust reliability measure of an uncertain control system satisfying required robust performance can be obtained, and the robustness bounds of uncertain parameters such that the control cost of a system is guaranteed can be provided. The optimal non-fragile guaranteed cost controller obtained in the paper may possess optimal guaranteed cost performance satisfying the precondition that the system is robustly reliable with respect to uncertainties occurring in both the controlled plant and controller gain. The presented formulations are in the framework of linear matrix inequality and thus can be carried out conveniently. The presented method provides an essential basis for the tradeoff between reliability and control cost in controller design of uncertain systems. Two numerical examples are provided to demonstrate the efficiency and feasibility of the presented method. It is shown that the coordination and simultaneous realization of the system performance, control cost, and robust reliability in control design of uncertain systems are significant.     

Robust Output Feedback Consensus of High-order Multi-agent Systems with Nonlinear Uncertainties

In this paper, the output feedback consensus problem of high-order multi-agent systems with nonlinear uncertainties is researched by the robust control method. By the dimensional extension of the observation matrix, the consensus control problem is transformed into a stability problem. Then the robust controller is designed by combining the nominal controller and the robust compensator. The nominal controller can obtain desired nominal performance based on the output informations. The robust compensator, which relys on robust signal compensation technology, is order to suppress the nonlinear uncertainties. According to the proposed method, output consensus error can be guaranteed as small as desired. Finally, simulation results are given to illustrate the effectiveness of this control method.     

不确定状态滞后系统时滞相关鲁棒H∞控制

研究了不确定状态滞后系统的鲁棒H∞控制问题,假定参数不确定性时变未知但有 界.基于LMI方法,提出了一种新的鲁棒无记忆状态反馈H∞,控制器的设计方法,得出的结 论与时滞大小有关,相对于时滞无关的结论具有较少的保守性.     

多电机驱动系统的保性能鲁棒Funnel控制

本文针对含参数不确定性的多电机驱动系统,提出一种基于最优保性能鲁棒的Funnel控制方法实现系统的规定跟踪性能.该控制方法通过构造Funnel函数对误差系统进行变换,并设计自适应反步控制器保证变换后系统的稳定性即可使跟踪误差的瞬态和稳态响应均被限制在给定的Funnel边界内.然而由于系统中存在的参数不确定性会影响系统的规定控制性能,本文在Funnel控制基础上又设计了最优保性能鲁棒控制器.它是通过将参数不确定性系统的保性能鲁棒控制问题转化为标称系统的最优控制问题,并求解新的黎卡提方程而得到的.因此所设计的控制器不但消除了参数不确定性对系统的影响并且能够使系统的性能指标达到一确定的上界.最后,对四电机驱动系统进行了仿真和实验验证,说明所提出控制方法的有效性.     

Robust reliable guaranteed cost control of positive interval systems with multiple time delays and actuator failure

This paper addresses the robust reliable guaranteed cost control problem of positive interval systems with multiple time delays and actuator failure for a given quadratic cost function. Through constructing a Lyapunov–Krasovskii functional, a sufficient condition for the existence of robust reliable guaranteed cost controllers is established such that the closed-loop system is positive and asymptotically stable, and the cost function is guaranteed to be no more than a certain upper bound. Based on the linear matrix inequality method, a criterion for the design of robust reliable guaranteed cost controllers is derived which can tolerate all admissible uncertainties as well as actuator failure. Moreover, a convex optimisation problem with linear matrix inequality constraints is formulated to design the optimal robust reliable guaranteed cost controller which minimises the upper bound of the closed-loop system cost. A numerical example is given to show the effectiveness of the proposed methods.     

p‐Times differentiable unbounded functions for robust control of uncertain switched nonlinear systems with tracking constraints

This paper investigates the problem of robust controller design for output‐constrained and state‐constrained uncertain switched nonlinear systems. By using the idea of p‐times differentiable unbounded functions and the backstepping technique, a constructive method is proposed to design effective controllers such that the output of a class of uncertain switched nonlinear systems in lower triangular form can asymptotically track a constant reference signal without violation of the output tracking error constraint. Furthermore, the explored method is applied to the state‐constrained robust stabilization problem for a class of general uncertain switched nonlinear systems. Finally, a simulation example is provided to demonstrate the effectiveness of the developed results. Copyright © 2014 John Wiley & Sons, Ltd.     

Worst-Case Simulation of Discrete Linear Time-Invariant Interval Dynamic Systems

In this paper, a new approach to worst-case simulation of discrete linear time- invariant interval dynamic systems is proposed. For stable systems, the new approach solves the problem of worst-case simulation by determining the interval hull enclosing the system states region at every iteration through optimisation. The originality of this approach is that it maintains time-invariant parametric uncertainties during the simulation process. Several previous algorithms have considered the case of parametric time-varying uncertainties (El Ghauoi, L., Calafiore, G.: Worst-Case Simulation of Uncertain Systems, in: Garulli, A., Tesi, A., and Vicino, A. (eds), Robustness in Identification and Control, Springer, London, 1999). However, Cuguer' o (Avoiding Possible Instability in Robust Simulation of Stable Parametric Uncertain Time-Invariant Systems, in: Proceedings of 40th Conference on Decision and Control, Florida, 2001) has presented possible instability problems when simulating a time-invariant uncertain system as if it were time-varying, this result being the motivation for the approach proposed in this paper. The optimisation problem associated with the approach proposed must be solved globally in order to guarantee that the minimum volume box enclosing the region of system states has been derived. In this paper, a global optimisation algorithm based on an interval branch and bound strategy is proposed. Finally, two real application examples are used to test the performance of the approach proposed.     

Global output feedback regulation of uncertain nonlinear systems with unknown time delay

This paper investigates the problem of global output feedback regulation for a class of nonlinear systems with unknown time delay. It is also allowed to contain uncertain functions of all the states and input as long as the uncertainties satisfying certain bounded condition for the considered systems. In this paper, a constructive control technique has been proposed for controlling the systems. By using dynamic high-gain scaling approach and choosing an appropriate Lyapunov-Krasovskii functional, a delay-independent robust adaptive output feedback controller is constructed such that the states of the considered systems achieve global regulation. Two simulation examples are provided to demonstrate the effectiveness of the proposed design scheme.     

Robust decentralised observer based guaranteed cost control for nonlinear uncertain interconnected systems. Application to multi-machine power systems

This article addresses the problem of a robust decentralised observer based guaranteed cost control for nonlinear interconnected systems with norm bounded time varying parameter uncertainties.

Sufficient conditions for the robust stabilisation and the guaranteed cost control performances of the closed-loop system are formulated in an optimisation problem in terms of linear matrix inequalities. Moreover, the designed problem is solved by a proposed iterative algorithm to compute the observer and the control gain matrices, to minimise the upper bound of a prescribed performance index and to maximise the nonlinearity domain, which leave the augmented system stable, despite the emerged uncertainties on the subsystems and on the interconnections between them. An extensive application example of a power system with three interconnected machines is discussed to demonstrate the reliability of the proposed control approach.     

Robust adaptive fault estimation and fault tolerant control for quadrotor attitude systems

ABSTRACT

This paper addresses the problem of fault estimation and fault tolerant control for quadrotor unmanned aerial vehicle. Firstly, a robust adaptive fault estimation observer (AFEO) is proposed to achieve fault estimation of quadrotor with actuator fault in the presence of external disturbances and parameter uncertainties. Furthermore, based on the estimation of fault, a dynamic output feedback fault tolerant controller (DOFFTC) is designed to stabilise the closed-loop system with faults and uncertainties. Sufficient conditions for the existence of both AFEO and DOFFTC are given in terms of linear matrix inequalities. Finally, simulation results are presented to illustrate the effectiveness of the proposed strategy.     

不确定线性系统保代价控制的鲁棒性分析

研究不确定线性系统保代价控制的鲁棒性分析问题.提出了不确定线性系统保代价控制鲁棒界概念,给出了不确定线性系统保代价控制的一种鲁棒性分析方法,并建立了不确定线性系统的参数可变保代价控制鲁棒界.针对一类结构不确定线性系统,进一步给出了保代价控制鲁棒界的一种优化算法,并用实例加以验证.     

Design of robust H ∞ controller for a half-vehicle active suspension system with input delay

This article is concerned with the problem of robust H _∞ control for a half-vehicle active suspension system with input delay. The delay is assumed to be interval time-varying delay with unknown derivative. The vehicle front sprung mass and the rear unsprung mass are assumed to be varying due to vehicle load variation and may result in parameter uncertainties being modelled by polytopic uncertainty. First of all, regarding the heave and pitch accelerations as the optimisation objectives, and suspension deflection and relative tire load constraints as the output constraints, we build the corresponding suspension systems. Then, by constructing a novel Lyapunov functional involved with the lower and upper bounds of the delay, sufficient condition for the existence of robust H _∞ controller is given to ensure robust asymptotical stability of the closed-loop system and also guarantee the constrained performance. The condition can be converted into convex optimisation problem and verified easily by means of standard software. Finally, a design example is exploited to demonstrate the effectiveness of the proposed design method.     

Non-fragile observer-based output feedback control for polytopic uncertain system under distributed model predictive control approach

In this paper, a non-fragile observer-based output feedback control problem for the polytopic uncertain system under distributed model predictive control (MPC) approach is discussed. By decomposing the global system into some subsystems, the computation complexity is reduced, so it follows that the online designing time can be saved.Moreover, an observer-based output feedback control algorithm is proposed in the framework of distributed MPC to deal with the difficulties in obtaining the states measurements. In this way, the presented observer-based output-feedback MPC strategy is more flexible and applicable in practice than the traditional state-feedback one. What is more, the non-fragility of the controller has been taken into consideration in favour of increasing the robustness of the polytopic uncertain system. After that, a sufficient stability criterion is presented by using Lyapunov-like functional approach, meanwhile, the corresponding control law and the upper bound of the quadratic cost function are derived by solving an optimisation subject to convex constraints. Finally, some simulation examples are employed to show the effectiveness of the method.     

Recursive scaling design for robust global nonlinear stabilization via output feedback

This paper proposes a novel approach to robust backstepping for global stabilization of uncertain nonlinear systems via output feedback. The design procedure developed in this paper is based on the concept of state‐dependent scaling, which handles output‐feedback stabilization problems of strict‐feedback systems with various structures of uncertainties in a unified way. The proposed method is suitable for numerical computation. The theory of the method employs the Schur complements formula instead of Young's inequality and completing the squares. This paper shows a condition of allowable uncertainty size under which an uncertain system is globally stabilized by output feedback. A class of systems is shown to be always globally stabilizable for arbitrarily large nonlinear size of uncertainties. A recursive procedure of robust observer design for such a class of uncertain systems is presented. Copyright © 2000 John Wiley & Sons, Ltd.     

H∞control of interconnected nonlinear sampled-data systems with parametric uncertainty

This paper studies the problem of robust control design for a class of interconnected uncertain systems under sampled measurements. The class of system under consideration is described by a state space model containing unknown cone bounded nonlinear interaction and time-varying norm-bounded parameter uncertainties in both state and output equations. Our attention is focused on the design of linear dynamic output feedback controllers using sampled measurements. We address the problem of robust H_∞ control in which both robust stability and a prescribed H_∞ performance are required to be achieved irrespective of the uncertainties and nonlinearities. The H_∞ performance measure involves both continuous-time and discrete-time signals. It has been shown that the above problems can be recast into H_∞ syntheses for related N decoupled linear sampled-data systems without parameter uncertainties and unknown nonlinearities, which can be solved in terms of Riccati differential equations with finite discrete jumps. A numerical example is given to show the potential of the proposed technique.