Delay-dependent Linear Matrix Inequality Research Articles

A new approach for dynamic output feedback control design of time-delayed nonlinear systems

This paper introduces a full-order dynamic output-feedback (DOF) controller for discrete-time nonlinear systems with time-varying delays represented by Linear Parameter-Varying (LPV) systems. The controller design is carried out by developing delay-dependent Linear Matrix Inequality based conditions using Lyapunov–Krasovskii stability arguments. A notable characteristic of the proposed approach is that the dynamic controller gains are directly obtained, without the need for variable transformations, equality constraints, or iterative algorithms. This feature sets it apart from many existing approaches in the literature and simplifies the design process. Furthermore, the proposed approach guarantees the local asymptotic stability of the origin of the closed-loop system and provides an estimated admissible initial condition region. The correct operation of the system is ensured once the state trajectories initiated within the admissible initial condition region remain enclosed in the validity domain of the LPV model. Numerical examples are provided to illustrate the potential and effectiveness of the proposed conditions.

Non-fragile output-feedback synchronization for delayed discrete-time complex-valued neural networks with randomly occurring uncertainties

This paper is step forward to establish an exponential synchronization criterion for discrete-time complex-valued neural networks (CVNNs) having time-varying delays subject to randomly occurring uncertain weighting parameters, in order to overcome the fluctuation when the output-feedback controller imposes on its dynamics. To achieve this, Jensen’s weighted summation inequalities (WSIs) and an extended reciprocal convex matrix inequality (ERCMI) are extended into the domain of complex field. By introducing some augmented vectors, a Lyapunov–Krasovskii functional (LKF) is constructed to attain an improved delay-dependent linear matrix inequalities (LMIs) constraint for the exponential synchronization phenomenon of the desired master–slave neuronal system model. For instance, the upper bound of the quadratic summation terms occurred in the finite difference of the LKF have been obtained from its linearization that has been made by the developed complex-valued WSIs and complex-valued ERCMI. The proposed results are less restrictive with the minimum number of decision variables than those obtained using existing inequalities. The designed output-feedback control gain has been determined by solving a set of complex-valued LMIs and it has been enforced with a prescribed exponential decay rate. Finally, in sight of MATLAB software, the established results have been examined via a numerical example supported by the simulation results.

Vehicle lateral motion control via robust delay-dependent Takagi-Sugeno strategy

Presented in this research paper is an integrated direct yaw moment control (DYC) and active front steering (AFS) for an uncertain vehicle lateral dynamics model considering network-induced communication delay, which is a time-varying continuous function with a known upper bound. Firstly, we consider tire cornering stiffness as a non-linear norm-bounded uncertain system that is modeled by fuzzy membership functions, and then vehicle lateral dynamics model is expressed by a set of linear Takagi-Sugeno (T-S) uncertain fuzzy models. Secondly, since the network-induced communication delay in vehicle control system is an inherent reason for stability and performance degradation, we derive a robust delay-dependent [Formula: see text] control methodology via the Lyapunov-Krasovskii functional for stability and performance conditions of the closed-loop system. For the synthesis, the robust control method is employed within the T-S fuzzy-model-based analysis framework and formulations are performed based on the solution of delay-dependent linear matrix inequalities (LMIs). The simulation study is presented using MATLAB/Simulink to show the achieved improvements in tracking variables via the designed robust fuzzy [Formula: see text] state-feedback controller. The proposed fuzzy robust delay-dependent controller is compared with a linear robust delay-dependent controller to clearly show the tracking improvements for different road conditions. Moreover, a performance-based analysis is carried out to demonstrate the advantage of the design with respect to different delay values. It is confirmed from the analysis results that the proposed fuzzy controller can successfully stabilize and possess improved tracking performance for vehicle lateral motion control.

Distributed Consensus Tracking of Multi-Agent Systems with Time-varying Input/Output Delays and Mismatched Disturbances

This paper investigates the distributed consensus tracking control problem for general linear multi-agent systems (MASs) with bounded time-varying input/output delays and mismatched disturbances under a directed communication graph containing a spanning tree. First, a part of the mismatched disturbances is transformed into the input channel as the matched disturbance, that allows the deployment of a predictive extended state observer (ESO) in order to estimate the consensus tracking error and transformed matched disturbance simultaneously. Subsequently, the ESO is used for designing a controller. The stability of the closed-loop system is guaranteed via a Lyapunov-Krasovskii functional with sufficient conditions in terms of delay-dependent linear matrix inequalities (LMIs). An additional LMI is proposed which, in conjunction with the rest of LMIs, results in a solution with a larger upper bound on delays than what would be feasible without it. The efficacy of the proposed scheme is demonstrated via simple numerical examples.

Gain‐scheduled control for discrete‐time non‐linear parameter‐varying systems with time‐varying delays

This study addresses the gain-scheduled control problem for discrete-time delayed non-linear parameter-varying (NLPV) and linear parameter-varying (LPV) systems. First, by constructing the parameter-dependent Lyapunov–Krasovskii functional and employing multiple auxiliary functions, delay-dependent reciprocally convex inequality, and selecting a suitable augmented vector, novel delay-dependent linear matrix inequality conditions for the static output-feedback control design and state-feedback control design for delayed NLPV are provided. Second, the results obtained for discrete-time delayed NLPV systems are modified in a simple way to deal with discrete-time delayed LPV systems. Finally, the effectiveness of the proposed methods is illustrated by numerical examples.

Passivity Analysis of Non-autonomous Discrete-Time Inertial Neural Networks with Time-Varying Delays

This paper addresses the passivity problem for delayed non-autonomous discrete-time inertial neural networks (NDINN), including the discrete-time switched inertial neural networks (DSINN) with state-dependent discontinuous right-hand side as its special case. First, we take a linear transformation to transform the original network into first-order difference equations. Second, by utilizing the Lyapunov direct method and with the help of the property of maximum singular value, we present a passivity criterion for the NDINN with delay-dependent linear matrix inequalities. Combining with the characteristic function method, the proposed analytical approach for NDINN is further extended to the DSINN. Finally, two simulation examples validate the efficacy of the analytical results.

Extended dissipativity stabilization and synchronization of uncertain stochastic reaction-diffusion neural networks via intermittent non-fragile control

This paper mainly studies the problem of extended dissipativity stabilization and synchronization of a class of uncertain stochastic reaction-diffusion neural networks with discrete and distributed time-varying delays via intermittent non-fragile control strategies. A novel stabilization and synchronization criteria and extended dissipative analysis is obtained by combining a switching time dependent Lyapunov functional method with Wirtinger’s inequality technique. Then, by solving a set of delay dependent linear matrix inequalities, we obtain the desired intermittent non-fragile controller, which can be used to satisfies the prescribed level of extended dissipativity behaviors, including H∞ behavior, passivity action, (Q, S, R)-dissipative performance, and L2−L∞ performance. Finally, two numerical examples are adopted to verify the validity of the stabilization and synchronization results.

Improved Results on Reachable Set Estimation of Linear Systems

In this study, we investigate the reachable set estimation for linear systems with discrete delay and distributed delay as well as disturbances. Based on the reciprocally convex combination lemma, free-weighting matrix approach and convex analysis technique, improved delay-dependent linear matrix inequalities (LMIs) criteria are derived for finding an ellipsoid to bound the reachable sets of such systems. Moreover, this result is extended to the one for linear systems with discrete delay, distributed delay and disturbances as well as polytopic-type uncertainties. In addition, the proposed results include some existing ones as special cases since the initial conditions of the systems are not required to be zero. Finally, two numerical examples are provided to show that our results have less conservative.

Constrained H∞ control for a half-car model of an active suspension system with actuator time delay by predictor feedback

In this paper, constrained memory state-feedback H∝ control for a half-car model of an active vehicle suspension system with input time-delay in the presence of external disturbance has been investigated. Its prime goal is to improve the inherent trade-offs among power consumption, handling performance, ride quality, and suspension travel. The tire deflections and the suspension deflections are constrained by their peak response values in time domain using the generalized H2 (GH∝) norm (energy-to-peak) performance, while the ride comfort performance of the suspension system is optimized by notion of the H∝ control (energy-to-energy) to measure the body accelerations including both the heaving and the pitching motions. Similar to the well-known prediction-based methods, the prediction vector of the system is achieved to construct the memory state-feedback controller. Using the prediction vector, sufficient conditions guaranteeing closed-loop system stability as well as disturbance attenuation are obtained as some delay-dependent linear matrix inequalities (LMIs). In addition, some LMIs are added to limit the gain of the controller. In the case of feasibility, obtained LMIs provide the stabilizing gain of the memory controller. The proposed approach is applied to a half-car model of an active suspension system considering the actuator time-delay to illustrate the effectiveness of the proposed method.

Robust Observer-based Control Design for Singular Systems with Delays in States

In this paper, the robust observer-based control problem for uncertain singular time delay systems is investigated. The approach is based on using Finsler's lemma. First, delay-dependent linear matrix inequality (LMI) conditions are obtained which, guarantee that the nominal unforced system is regular, impulse free, and stable. Then, with the help of obtained admissibility criterion, an observer-based controller is given by solving a set of LMIs. Finally, some simulations are provided to demonstrate the effectiveness of the obtained results.

Robust Stabilization of Delayed Neural Networks: Dissipativity-Learning Approach.

This paper examines the robust stabilization problem of continuous-time delayed neural networks via the dissipativity-learning approach. A new learning algorithm is established to guarantee the asymptotic stability as well as the (Q,S,R) - α -dissipativity of the considered neural networks. The developed result encompasses some existing results, such as H∞ and passivity performances, in a unified framework. With the introduction of a Lyapunov-Krasovskii functional together with the Legendre polynomial, a novel delay-dependent linear matrix inequality (LMI) condition and a learning algorithm for robust stabilization are presented. Demonstrative examples are given to show the usefulness of the established learning algorithm.

Robust guaranteed cost control for continuous-time uncertain Markov switching singular systems with mode-dependent time delays

The guaranteed cost control problem for mode-dependent time-delay Markov switching singular systems with norm-bounded uncertain parameters is discussed. Based on delay-dependent linear matrix inequalities, sufficient conditions which ensure the nominal Markov switching singular system to be regular, non-impulsive and stochastically stable are derived by quoting a mode-dependent Lyapunov functional and applying Moon’s inequality for cross terms. The sufficient conditions involve two cases. Case 1: the time delays are known; Case 2: the time delays are unknown, but the difference of the largest and the smallest time delay is known. Then, the problem is solved to design a state-feedback control law such that the closed-loop system is stochastically stable and the corresponding cost function value is not bigger than a specified upper bound for all the admissible uncertainties. Finally, optimization algorithms are given to find the optimal performance indexes.

A New Global Robust Exponential Stability Criterion for H∞ Control of Uncertain Stochastic Neutral-type Neural Networks with Both Timevarying Delays

This paper mainly focuses on a novel H∞ control design to handle the global robust exponential stability problem for uncertain stochastic neutral-type neural networks (USNNNs) with mixed time-varying delays. Here the delays are assumed to be both discrete and distributed, which means that the lower and upper bounds can be derived. Firstly, we draw a control law for stabilized and stability of the neutral-type neural networks (NNNs). Secondly, by employing the Lyapunov-Krasovskii functional(LKF) theory, Jensen’s integral inequality, new required sufficient conditions for the global robust exponential stability of the given neural networks (NNs) are established in terms of delay-dependent linear matrix inequalities (LMIs), which can be easily checked in practice. The conditions obtained are expressed in terms of LMIs whose feasibility can be verified easily by MATLAB LMI control toolbox. Moreover, we have compared our work with previous one in the existing literature and showed that it reduces conservatism. Finally, one numerical example with their simulations is given to validate the effectiveness of our proposed theoretical results.

Design of state estimator for BAM fuzzy cellular neural networks with leakage and unbounded distributed delays

In this paper, the state estimation problem is studied for the bidirectional associative memory (BAM) fuzzy cellular neural networks (FCNNs) with delays, where the delays include leakage and unbounded distributed delays. The problem addressed is to estimate the neuron states, through available output measurements, such that for all admissible leakage and unbounded distributed delays, the dynamics of the estimation error is globally asymptotically stable. A delay-dependent linear matrix inequality (LMI) criterion for the existence of the estimator is proposed by using the Lyapunov–Krasovskii functional method. In addition, the unknown gain matrix is determined by solving a delay-dependent LMI. Finally, numerical examples and simulations are provided to illustrate the effectiveness of the theoretical results.

Robust control of heterogeneous vehicular platoon with uncertain dynamics and communication delay

Platoon formation of highway vehicles has the potential to significantly enhance road safety, improve highway utility, and increase traffic efficiency. However, various uncertainties and disturbances that are present in real-world driving conditions make the implementation of vehicular platoon a challenging problem. This study presents an H-infinity control method for a platoon of heterogeneous vehicles with uncertain vehicle dynamics and uniform communication delay. The requirements of string stability, robustness and tracking performance are systematically measured by the H-infinity norm, and explicitly satisfied by casting into the linear fractional transformation format. A delay-dependent linear matrix inequality is derived to numerically solve the distributed controllers for each vehicle. The performances of the controlled platoon are theoretically analysed by using a delay-dependent Lyapunov function which includes a linear quadratic function of states during the delay period. Simulations with a platoon of heterogeneous vehicles are conducted to demonstrate the effectiveness of the proposed method under random parameters and external disturbances.

Improved reachable set bounding for linear time-delay systems with disturbances

In this paper, we reconsider the problem of reachable set bounding for linear time-delay systems with disturbances. Generalized reachable sets for dynamical systems are proposed where initial points are taken into account. Meanwhile, a novel lemma is given which shows an extended criterion that the reachable sets are bounded. Then, based on this lemma and the Lyapunov–Krasovskii functional (LKF) as well as the free-weighting matrix techniques, improved delay-dependent linear matrix inequality (LMI) criteria are obtained for finding an ellipsoid to bound the reachable sets of linear time-delay systems with disturbances. Two numerical examples are finally provided to substantiate the efficiency and merits of our theoretical results.

Robust exponential stability and memory state feedback control for uncertain singular time‐delay systems with saturating actuators

This study is concerned with delay-dependent H ∞ robust exponential stability and memory state feedback stabilisation of singular time-delay systems with saturating actuators. First, a delay-dependent linear matrix inequality condition is obtained, which guarantees that the uncertain singular time-delay systems subject to actuator saturation are not only robustly exponential admissible, but also satisfy H ∞ performance γ via a tighter integral inequality and the method of free-weighting matrices. Then, using the conditions, the estimation of stability region and the controller with memory state feedback are given by solving a convex optimisation problem. Finally, some numerical examples are provided to demonstrate the merit of the obtained results.

Observer-basedH∞control for uncertain singular time-delay systems with actuator saturation

Summary In this paper, the observer-based H∞ control problem for uncertain singular time-delay systems with actuator saturation is concerned. First, a delay-dependent linear matrix inequality (LMI) condition is obtained which, guarantees that the uncertain singular time-delay systems with actuator saturation are regular, impulse free, and asymptotically stable with H∞ performance condition. Then, with this condition, the estimation of stability region and the design method of observer-based H∞ controller are given by solving LMIs and convex optimization problem. Finally, some numerical examples are provided to demonstrate the merit of the obtained results. Copyright © 2015 John Wiley & Sons, Ltd.

New admissibility analysis for discrete singular systems with time-varying delay

In this paper, the issue of admissibility for discrete singular systems with time-varying delay is addressed. The main contribution of this paper is to reduce the conservatism of the considered system by adopting an improved reciprocally convex combination approach to bound the forward difference of the double summation term, and utilizing the reciprocally convex combination approach to bound the forward difference of the triple summation term in the Lyapunov function. Without employing decomposition and equivalent transformation of the considered system, a strict delay-dependent linear matrix inequality (LMI) criterion is built to guarantee the considered system to be regular, causal and stable. A numerical example is given to illustrate the effectiveness of this proposed method.

State Estimation for Discrete-Time Takagi-Sugeno Fuzzy Systems with Time-Varying Delays

The state estimation problem is investigated for discrete-time Takagi-Sugeno fuzzy systems with time-varying delays. By constructing appropriate Lyapunov-Krasovskii functionals and employing matrix inequality technique, a delay-dependent linear matrix inequalities (LMIs) criterion is developed to estimate the systems state with some observed output measurements such that the error-state system is globally asymptotically stable. An example with simulations is given to show the effectiveness of the proposed criterion.