Robust stability bounds for multi-delay networked control systems

In this paper, the robust stability of a perturbed linear continuous-time system is examined when controlled using a sampled-data networked control system (NCS) framework. Three new robust stability bounds on the time-invariant perturbations to the original continuous-time plant matrix are presented guaranteeing stability for the corresponding discrete closed-loop augmented delay-free system (ADFS) with multiple time-varying sensor and actuator delays. The bounds are differentiated from previous work by accounting for the sampled-data nature of the NCS and for separate communication delays for each sensor and actuator, not a single delay. Therefore, this paper expands the knowledge base in multiple inputs multiple outputs (MIMO) sampled-data time delay systems. Bounds are presented for unstructured, semi-structured, and structured perturbations.     

On input-to-state stability of min–max nonlinear model predictive control

In this paper we consider discrete-time nonlinear systems that are affected, possibly simultaneously, by parametric uncertainties and other disturbance inputs. The min–max model predictive control (MPC) methodology is employed to obtain a controller that robustly steers the state of the system towards a desired equilibrium. The aim is to provide a priori sufficient conditions for robust stability of the resulting closed-loop system using the input-to-state stability (ISS) framework. First, we show that only input-to-state practical stability can be ensured in general for closed-loop min–max MPC systems; and we provide explicit bounds on the evolution of the closed-loop system state. Then, we derive new conditions for guaranteeing ISS of min–max MPC closed-loop systems, using a dual-mode approach. An example illustrates the presented theory.     

Computation of robust stability bounds for time-delay systems with nonlinear time-varying perturbations

This paper is concerned with the computation of robust stability bounds for time-delay systems with nonlinear time-varying perturbations. Firstly, a delay-independent condition on the robust stability is presented and a method to determine the maximum upper bound of robust stability is given. Then, a delay-dependent robust stability condition is provided. All results are given in terms of linear matrix inequalities where efficient solution procedures are available. Numerical examples have shown that the results are less conservative than some previous established bounds.     

Robust identification/invalidation in an LPV framework

A robust linear parameter varying (LPV) identification/invalidation method is presented. Starting from a given initial model, the proposed method modifies it and produces an LPV model consistent with the assumed uncertainty/noise bounds and the experimental information. This procedure may complement existing nominal LPV identification algorithms, by adding the uncertainty and noise bounds which produces a set of models consistent with the experimental evidence. Unlike standard invalidation results, the proposed method allows the computation of the necessary changes to the initial model in order to place it within the consistency set. Similar to previous LPV identification procedures, the initial parameter dependency is fixed in advance, but here a methodology to modify this dependency is presented. In addition, all calculations are made on state‐space matrices which simplifies further controller design computations. The application of the proposed method to the identification of nonlinear systems is also discussed. Copyright © 2009 John Wiley & Sons, Ltd.     

Robust Stable Fuzzy Control via Fuzzy Modeling and Feedback Linearization with Its Applications to Controlling Uncertain Single-link Flexible Joint Manipulators

In this paper, a robust stable fuzzy control design based on feedback linearization is presented. Takagi–Sugeno fuzzy model is used as representing the nonlinear plant model and uncertainty is assumed to be included in the model structure with known bounds. For this structured uncertainty, the closed system can be analyzed by applying the perturbation system stability analysis to the fuzzy feedback linearization systems and a sufficient condition is derived to guarantee the stability of the closed-loop system with bounded parameter uncertainties. Based on the developed analysis method, we can design a robust fuzzy controller by choosing the control parameters satisfying the robust stability condition.     

Robust identification of strongly stabilizable systems

For strongly stabilizable systems for which a strongly stabilizing controller is known approximately, the authors consider system identification in the graph, gap, and chordal metrics using robust H _∞ identification of the closed-loop transfer function in the framework proposed by A.J. Helmicki et al. (1990). Error bounds are derived showing that robust convergence is guaranteed and that the identification can be satisfactorily combined with a model reduction step. Two notions of robust identification of stable systems are compared, and an alternative robust identification technique based on smoothing, which can be used to yield polynomial models directly, is developed     

An efficient methodology for robust control of dynamic systems with interval matrix uncertainties

Interval models are frequently used for dealing with uncertainties of control systems. However, it is well known that direct analysis and synthesis of a controlled dynamic system with interval matrix uncertainties may be a NP-hard problem. In this work, an efficient methodology for robustness analysis and robust control design of dynamic systems with interval matrix uncertainties is presented systematically, in which the uncertainties appearing in the controlled plant and controller realisation are taken into account simultaneously in an integrated framework. The fundamental problems, such as quadratic stability, guaranteed cost control and H_∞ control of uncertain systems are taken as examples to show the methodology. Necessary and sufficient conditions for linear dynamic systems with interval matrices are derived by transforming all the interval matrices into some more tractable forms. The whole reasoning process is logical and rigorous, and NP-hard problem is successfully avoided. The presented formulations are within the framework of linear matrix inequality and can be implemented conveniently. In contrast to existing vertex-set methods, in which the vertices of interval matrices need to be constructed and checked, the presented methods are more efficient. Three numerical examples are investigated to demonstrate the effectiveness and feasibility of the presented method.     

Lyapunov functionals in complex /spl mu/ analysis

Conditions for robust stability of linear time-invariant systems subject to structured linear time-invariant uncertainties can be derived in the complex /spl mu/ framework, or, equivalently, in the framework of integral quadratic constraints. These conditions can be checked numerically with linear matrix inequality (LMI)-based convex optimization using the Kalman-Yakubovich-Popov lemma. We show how LMI tests also yield a convex parametrization of (a subset of) Lyapunov functionals that prove robust stability of such uncertain systems. We show that for uncertainties that are pure delays, the Lyapunov functionals reduce to the standard Lyapunov-Krasovksii functionals that are encountered in the stability analysis of delay systems. We demonstrate the practical utility of the Lyapunov functional parametrization by deriving bounds for a number of measures of robust performance (beyond the usual H/sub /spl infin// performance); these bounds can be efficiently computed using convex optimization over linear matrix inequalities.     

Fixed-structure robust controller synthesis via decentralized static output feedback

This paper describes and illustrates a unified methodology for robust, fixed-structure controller synthesis. The approach is based upon direct fixed-structure controller synthesis using a decentralized static output feedback formulation as a general framework for representing a large class of controller structures. Scaled Popov bounds for the real structured singular value are used to account for real parameter uncertainty and provide the means for optimizing a worst-case ℋ︁₂ cost bound with respect to the free parameters of the controller. Quasi-Newton optimization algorithms are used to solve the resulting numerical optimization problem. Initial stability multiplier and scaling matrices needed in scaled Popov synthesis are obtained by solving an LMI feasibility problem. Using both centralized and decentralized controller structures, numerical results are obtained for a 16th-order acoustic duct model with uncertain damped natural frequencies and for a two-dimensional beam-spring model with uncertain actuator locations. © 1998 John Wiley & Sons, Ltd.     

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.     

Stability of Local On‐Ramp Metering Control Laws

A framework for stability analysis of local on‐ramp metering control strategies based on the cell transmission model is presented. Within this framework, it is possible to formulate Lyapunov and input‐state stability results for on‐ramp metering control strategies in an open section of highway with on‐ramps. Using this analysis, recommendations for the design of on‐ramp metering control laws set points are derived. Two examples on the use of such analysis are presented. One deals with the stability analysis of a local on‐ramp metering control law and the other with the design of a disturbance observer that, used in combination with the local on‐ramp metering control law, provides a more robust response to traffic regulation. Simulation results are included that confirm the possibility of using this framework to test the impact of local on‐ramp metering control strategies.     

Performance lower bounds in stochastic robust and adaptive control

The fundamental issues of capability of robust and adaptive control in dealing with uncertainty are investigated in stochastic systems. It is revealed that to capture the intrinsic limitations of adaptive control, it is necessary to use sup_t types of transient and persistent performance, rather than lim sup_t types which reflect only asymptotic behavior of a system. For clarity and technical tractability, a simple first-order linear time-varying system is employed as a vehicle to explore performance lower bounds of robust and adaptive control. Optimal performances of nominal, robust and adaptive control are explicitly derived and their implications are discussed in an information framework. An adaptive strategy is scrutinized for its achievable performance bounds. The results indicate that intimate interaction and inherent conflict between identification and control result in a certain performance lower bound which does not approach the nominal performance even when the system varies very slowly. Explicit lower bounds are obtained when disturbances are either normally or uniformly distributed     

一类不确定时滞系统的自适应滑模控制

讨论了不确定时滞系统的鲁棒控制器设计问题。利用自适应滑模控制策略,直接克服系统不确定性的影响,保证了从任意初始位置出发的系统在有限时间内到滑模面;基于时滞系统鲁棒稳定控制的结论,导出了时滞依赖滑模控制的新结论。仿真实验证明了所提方法的有效性。     

A model reference quantitative feedback design theory with application to turbomachinery

A new decentralized robust control design framework, model reference quantitative feedback design (MRQFD), is developed for the design of the MIMO parametric uncertain control systems. An internal model reference loop is proposed to obtain the achievement of generalized diagonal dominance (GDD) and the reduction of uncertainty in the resultant compensated internal loop system. Based on nonnegative matrix theory, a useful design guide is derived to achieve the GDD condition for the internal model reference loop. Then a sensitivity-based quantitative feedback design (QFD) method is developed and used to solve the resulting series of single-loop QFD problems. The MIMO quantitative specifications are guaranteed to be satisfied by the proposed design framework for largely uncertain systems. A successful application to the design of a robust multivariable controller for the Allison PD-514 aircraft turbine engine is presented to demonstrate the effectiveness of the methodology developed here.     

A tool to analyze robust stability for constrained nonlinear MPC

A sufficient condition for robust asymptotic stability of nonlinear constrained model predictive control (MPC) is derived with respect to plant/model mismatch. This work is an extension of a previous study on the unconstrained nonlinear MPC problem, and is based on nonlinear programming sensitivity concepts. It addresses the discrete time state feedback problem with all states measured. A strategy to estimate bounds on the plant/model mismatch is proposed that can be used off-line as a tool to assess the extent of model mismatch that can be tolerated to guarantee robust stability.     

不确定时滞系统的保代价H∞鲁棒可靠控制

针对一类不确定时滞受扰系统,研究了在执行器发生故障情况下系统具有保代价的H_∞鲁棒可靠控制器设计问题。根据Lyapunov稳定性理论,得到了系统存在保代价H_∞鲁棒可靠控制器应满足的一个矩阵不等式,进一步将这个矩阵不等式转化为线性矩阵不等式（LMI）,并给出了系统状态反馈控制器的设计方法。利用论文方法设计的鲁棒可靠控制器能够使得时滞系统对于任意允许的不确定量以及一个预先指定执行器子集中任意执行器失效不仅具有鲁棒容错性,并且使系统存在保成本上界以及具有指定H∞范数的干扰抑制能力。仿真结果表明了该可靠控制器设计方法的有效性。     

Decentralised robust flow controller design for networks with multiple bottlenecks

Decentralised rate-based flow controller design in multi-bottleneck data-communication networks is considered. An ?^∞ problem is formulated to find decentralised controllers which can be implemented locally at the bottleneck nodes. A suboptimal solution to this problem is found and the implementation of the decentralised controllers is presented. The controllers are robust to time-varying uncertain multiple time-delays in different channels. They also satisfy tracking and weighted fairness requirements. Lower bounds on the actual stability margins are derived and their relation to the design parameters is analysed. A number of simulations are also included to illustrate the time-domain performance of the proposed controllers.     

Nonlinear robust H-infinity filtering for a class of uncertain systems via convex optimization

A new approach for robust H-infinity filtering for a class of Lipschitz nonlinear systems with time-varying uncertainties both in the linear and nonlinear parts of the system is proposed in an LMI framework. The admissible Lipschitz constant of the system and the disturbance attenuation level are maximized simultaneously through convex multi-objective optimization. The resulting H-infinity filter guarantees asymptotic stability of the estimation error dynamics with exponential convergence and is robust against nonlinear additive uncertainty and time-varying parametric uncertainties. Explicit bounds on the nonlinear uncertainty are derived based on norm-wise and element-wise robustness analysis.     

Asymptotic moving object tracking with trajectory tracking extension: A homography‐based approach

In this paper, a homography‐based visual servo controller is developed for a rigid body to track a moving object in three‐dimensional space with a fixed relative pose. Specifically, a monocular camera is mounted on the rigid body, and the desired relative pose is expressed by a pre‐recorded reference image. Homography is exploited to obtain the orientation and scaled position for controller design. Considering the unknown moving object's velocities and distance information, a continuous nonlinear visual controller is developed using the robust integral of the signum of the error methodology. To facilitate the stability analysis, the system uncertainties regarding the moving object's velocities and distance information are divided into the error‐unrelated system uncertainties and the error‐related system uncertainties. After that, the upper bounds of the error‐related system uncertainties are derived with composited system errors. An asymptotic tracking of the leading object is proved based on the Lyapunov methods and the derived upper bounds. In addition, the proposed controller is extended to address the trajectory tracking problem. Simulation results validate the effectiveness of the proposed approach. Copyright © 2017 John Wiley & Sons, Ltd.