Showing papers by "Huijun Gao published in 2010"

State Estimation and Sliding-Mode Control of Markovian Jump Singular Systems

Abstract: This paper is concerned with the state estimation and sliding-mode control problems for continuous-time Markovian jump singular systems with unmeasured states. Firstly, a new necessary and sufficient condition is proposed in terms of strict linear matrix inequality (LMI), which guarantees the stochastic admissibility of the unforced Markovian jump singular system. Then, the sliding-mode control problem is considered by designing an integral sliding surface function. An observer is designed to estimate the system states, and a sliding-mode control scheme is synthesized for the reaching motion based on the state estimates. It is shown that the sliding mode in the estimation space can be attained in a finite time. Some conditions for the stochastic admissibility of the overall closed-loop system are derived. Finally, a numerical example is provided to illustrate the effectiveness of the proposed theory.

New Delay-Dependent Exponential $H_{\infty}$ Synchronization for Uncertain Neural Networks With Mixed Time Delays

Abstract: This paper establishes an exponential H infin synchronization method for a class of uncertain master and slave neural networks (MSNNs) with mixed time delays, where the mixed delays comprise different neutral, discrete, and distributed time delays. The polytopic and the norm-bounded uncertainties are separately taken into consideration. An appropriate discretized Lyapunov-Krasovskii functional and some free-weighting matrices are utilized to establish some delay-dependent sufficient conditions for designing delayed state-feedback control as a synchronization law in terms of linear matrix inequalities under less restrictive conditions. The controller guarantees the exponential H infin synchronization of the two coupled MSNNs regardless of their initial states. Detailed comparisons with existing results are made, and numerical simulations are carried out to demonstrate the effectiveness of the established synchronization laws.

Fuzzy-Model-Based Piecewise ${\mathscr H}_{\infty }$ Static-Output-Feedback Controller Design for Networked Nonlinear Systems

Abstract: This paper investigates the problem of robust H∞ output-feedback control for a class of nonlinear systems under unreliable communication links. The nonlinear plant is represented by a Takagi-Sugeno (T-S) uncertain fuzzy model, and the communication links between the plant and controller are assumed to be imperfect, i.e., data-packet dropouts occur intermittently, which is often the case in a network environment. Stochastic variables that satisfy the Bernoulli random-binary distribution are adopted to characterize the data-missing phenomenon, and the attention is focused on the design of a piecewise static-output-feedback (SOF) controller such that the closed-loop system is stochastically stable with a guaranteed H∞ performance. Based on a piecewise Lyapunov function combined with some novel convexifying techniques, the solutions to the problem are formulated in the form of linear matrix inequalities (LMIs). Finally, simulation examples are also provided to illustrate the effectiveness of the proposed approaches.

Robust Sampled-Data $H_{\infty}$ Control for Vehicle Active Suspension Systems

Abstract: This brief investigates the problem of robust sampled-data H ∞ control for active vehicle suspension systems. By using an input delay approach, the active vehicle suspension system with sampling measurements is transformed into a continuous-time system with a delay in the state. The transformed system contains non-differentiable time-varying state delay and polytopic parameter uncertainties. A Lyapunov functional approach is employed to establish the H ∞ performance, and the controller design is cast into a convex optimization problem with linear matrix inequality (LMI) constraints. A quarter-car model is considered in this brief and the effectiveness of the proposed approach is illustrated by a realistic design example.

Robust $H_{\infty}$ Filtering for a Class of Nonlinear Networked Systems With Multiple Stochastic Communication Delays and Packet Dropouts

Abstract: In this paper, the robust H∞ filtering problem is studied for a class of uncertain nonlinear networked systems with both multiple stochastic time-varying communication delays and multiple packet dropouts. A sequence of random variables, all of which are mutually independent but obey Bernoulli distribution, are introduced to account for the randomly occurred communication delays. The packet dropout phenomenon occurs in a random way and the occurrence probability for each sensor is governed by an individual random variable satisfying a certain probabilistic distribution in the interval. The discrete-time system under consideration is also subject to parameter uncertainties, state-dependent stochastic disturbances and sector-bounded nonlinearities. We aim to design a linear full-order filter such that the estimation error converges to zero exponentially in the mean square while the disturbance rejection attenuation is constrained to a give level by means of the H∞ performance index. Intensive stochastic analysis is carried out to obtain sufficient conditions for ensuring the exponential stability as well as prescribed H∞ performance for the overall filtering error dynamics, in the presence of random delays, random dropouts, nonlinearities, and the parameter uncertainties. These conditions are characterized in terms of the feasibility of a set of linear matrix inequalities (LMIs), and then the explicit expression is given for the desired filter parameters. Simulation results are employed to demonstrate the effectiveness of the proposed filter design technique in this paper.

Robust $H_{\infty }$ Fuzzy Output-Feedback Control With Multiple Probabilistic Delays and Multiple Missing Measurements

Abstract: In this paper, the robust H∞-control problem is investigated for a class of uncertain discrete-time fuzzy systems with both multiple probabilistic delays and multiple missing measurements. A sequence of random variables, all of which are mutually independent but obey the Bernoulli distribution, is introduced to account for the probabilistic communication delays. The measurement-missing phenomenon occurs in a random way. The missing probability for each sensor satisfies a certain probabilistic distribution in the interval. Here, the attention is focused on the analysis and design of H∞ fuzzy output-feedback controllers such that the closed-loop Takagi-Sugeno (T-S) fuzzy-control system is exponentially stable in the mean square. The disturbance-rejection attenuation is constrained to a given level by means of the H∞-performance index. Intensive analysis is carried out to obtain sufficient conditions for the existence of admissible output feedback controllers, which ensures the exponential stability as well as the prescribed H∞ performance. The cone-complementarity-linearization procedure is employed to cast the controller-design problem into a sequential minimization one that is solved by the semi-definite program method. Simulation results are utilized to demonstrate the effectiveness of the proposed design technique in this paper.

New Passivity Analysis for Neural Networks With Discrete and Distributed Delays

Abstract: In this brief, the problem of passivity analysis is investigated for a class of uncertain neural networks (NNs) with both discrete and distributed time-varying delays. By constructing a novel Lyapunov functional and utilizing some advanced techniques, new delay-dependent passivity criteria are established to guarantee the passivity performance of NNs. Essentially different from the available results, when estimating the upper bound of the derivative of Lyapunov functionals, we consider and best utilize the additional useful terms about the distributed delays, which leads to less conservative results. These criteria are expressed in the form of convex optimization problems, which can be efficiently solved via standard numerical software. Numerical examples are provided to illustrate the effectiveness and less conservatism of the proposed results.

Robust ${\cal H}_{\infty}$ Finite-Horizon Control for a Class of Stochastic Nonlinear Time-Varying Systems Subject to Sensor and Actuator Saturations

Abstract: This technical note addresses the robust H∞ finite-horizon output feedback control problem for a class of uncertain discrete stochastic nonlinear time-varying systems with both sensor and actuator saturations. In the system under investigation, all the system parameters are allowed to be time-varying, the parameter uncertainties are assumed to be of the polytopic type, and the stochastic nonlinearities are described by statistical means which can cover several classes of well-studied nonlinearities. The purpose of the problem addressed is to design an output feedback controller, over a given finite-horizon, such that the H∞ disturbance attenuation level is guaranteed for the nonlinear stochastic polytopic system in the presence of saturated sensor and actuator outputs. Sufficient conditions are first established for the robust H∞ performance through intensive stochastic analysis, and then a recursive linear matrix inequality (RLMI) approach is employed to design the desired output feedback controller achieving the prescribed H∞ disturbance rejection level. Simulation results demonstrate the effectiveness of the developed controller design scheme.

Variance-Constrained ${\cal H}_{\infty}$ Filtering for a Class of Nonlinear Time-Varying Systems With Multiple Missing Measurements: The Finite-Horizon Case

Abstract: This paper is concerned with the robust H ∞ finite-horizon filtering problem for a class of uncertain nonlinear discrete time-varying stochastic systems with multiple missing measurements and error variance constraints. All the system parameters are time-varying and the uncertainty enters into the state matrix. The measurement missing phenomenon occurs in a random way, and the missing probability for each sensor is governed by an individual random variable satisfying a certain probabilistic distribution in the interval . The stochastic nonlinearities under consideration here are described by statistical means which can cover several classes of well-studied nonlinearities. Sufficient conditions are derived for a finite-horizon filter to satisfy both the estimation error variance constraints and the prescribed H ∞ performance requirement. These conditions are expressed in terms of the feasibility of a series of recursive linear matrix inequalities (RLMIs). Simulation results demonstrate the effectiveness of the developed filter design scheme.

Robust Sampled-Data Control for Vehicle Active Suspension Systems

Abstract: This brief investigates the problem of robust sampled-data control for active vehicle suspension systems. By using an input delay approach, the active vehicle suspension system with sampling measurements is transformed into a continuous-time system with a delay in the state. The transformed system contains non-differentiable time-varying state delay and polytopic parameter uncertainties. A Lyapunov functional approach is employed to establish the performance, and the controller design is cast into a convex optimization problem with linear matrix inequality (LMI) constraints. A quarter-car model is considered in this brief and the effectiveness of the proposed approach is illustrated by a realistic design example.

Vibration Control of Seat Suspension using H∞ Reliable Control

Abstract: This paper is concerned with the problem of robust H∞ reliable load-dependent control design for a class of semi-active seat suspension systems. A four degree-of-freedom human body model is considered in order to investigate the control strategy more precisely. It is assumed that the human body mass resides in an interval and can be measured online. The load-dependent approach is based on a parameter-dependent Lyapunov function. Thus the proposed method is capable of reducing the conservatism and improving the closed-loop performance. Actuator faults are also considered in the controller design process and the resulting control systems are reliable because they provide guaranteed asymptotic stability and H∞ performance in spite of the possible actuator failures. The usefulness and advantages of the controller design methodology are demonstrated through a design example.

Observer‐based H∞ control for systems with repeated scalar nonlinearities and multiple packet losses

Abstract: This paper is concerned with the H1 control problem for a class of systems with repeated scalar nonlinearities and multiple missing measurements. The nonlinear system is described by a discrete-time state equation involving a repeated scalar nonlinearity which typically appears in recurrent neural networks. The measurement missing phenomenon is assumed to occur, simultaneously, in the communication channels from the sensor to the controller and from the controller to the actuator, where the missing probability for each sensor/actuator is governed by an individual random variable satisfying a certain probabilistic distribution in the interval [0 1]. Attention is focused on the analysis and design of an observer-based feedback controller such that the closed-loop control system is stochastically stable and preserves a guaranteed H1 performance. Sufficient conditions are obtained for the existence of admissible controllers. It is shown that the controller design problem under consideration is solvable if certain linear matrix inequalities (LMIs) are feasible. Three examples are provided to illustrate the effectiveness of the developed theoretical results.

Delay-dependent robust H∞ control for uncertain stochastic time-delay systems

Abstract: This paper investigates the robust H∞ control problem for stochastic systems with a delay in the state. Sufficient delay-dependent conditions for the existence of state-feedback controllers are proposed to guarantee mean-square asymptotic stability as well as the prescribed H∞ performance for the closed-loop systems. Moreover, the results are further extended to the stochastic time-delay systems with parameter uncertainties, which are assumed to be time-varying norm-bounded appearing in both the state and the input matrices. The appealing idea is to partition the delay, which differs greatly from the most existing results and reduces conservatism by thinning the delay partitioning. Numerical examples are provided to show the advantages of the proposed techniques. Copyright © 2009 John Wiley & Sons, Ltd.

Robust orbital transfer for low earth orbit spacecraft with small-thrust

Abstract: This paper studies the problem of robust orbital control for low earth orbit (LEO) spacecraft rendezvous subjects to the parameter uncertainties, the constraints of small-thrust and guaranteed cost during the orbital transfer process In particular, the rendezvous process is divided into in-plane motion and out-plane motion based on C–W equations, and the relative motion models with parameter uncertainties are established By considering the property of null controllable with vanishing energy (NCVE), the problem of orbital transfer control with small thrust and bounded control cost is proposed A new Lyapunov approach is introduced, and the controller design problem is cast into a convex optimization problem subjects to linear matrix inequality (LMI) constraints With the obtained controller, the orbit transfer process can be accomplished with small thrust and the control cost has an upper bound simultaneously Different possible initial states of the transfer orbit are also analyzed for the controller design An illustrative example is provided to show the effectiveness of the proposed control design method, and the different performances caused by different initial states of the transfer orbit are illustrated

Input-Delayed Control of Uncertain Seat Suspension Systems With Human-Body Model

Abstract: This paper deals with the problem of input-delayed robust H? state-feedback controller design for a class of semi-active seat suspension systems with parameter uncertainties and actuator time delays. A vertical vibration model of human body is employed and put together with the plant of the seat suspension system. The controller design is cast into a convex multi-objective optimization problem with linear matrix inequality (LMI) constraints by defining a Lyapunov functional and using the delay partitioning method. The usefulness and advantages of the proposed controller design methodology are demonstrated through a design example.

Multi-Objective Fault-Tolerant Output Tracking Control of a Flexible Air-Breathing Hypersonic Vehicle

Abstract: This paper deals with the problem of multi-objective fault-tolerant output tracking control for the longitudinal model of a flexible air-breathing hypersonic vehicle (FAHV). There exist some challenges for control design for the vehicles due to the inherent couplings between the propulsion system, the airframe dynamics, and the presence of strong flexibility effects. This paper addresses the problem of guaranteed cost fault-tolerant output tracking control with regional pole constraints against actuator faults for the FAHV system. A non-linear longitudinal model is adopted for control design because of the complexity of the FAHV systems. First, a linearized model is established around the trim point including the state of altitude, velocity, angle of attack, pitch angle, and pitch rate, etc. for a non-linear, dynamically coupled simulation model of a FAHV with the aim to address the multi-objective fault-tolerant output tracking control problem. Second, the control objective and models of actuator faults ...

Robust H ∞ control for a class of uncertain mechanical systems

Abstract: In this article, the problem of H ∞ control is investigated for a class of mechanical systems with input delay and parameter uncertainties which appear in all the mass, damping and stiffness matrices. Two approaches, norm-bounded and linear fractional transformation (LFT) uncertainty formulations, are considered. By using a new Lyapunov–Krasovskii functional approach, combined with the advanced techniques for achieving delay dependence, improved robust H ∞ state-feedback controller design methods are developed. The existence condition for admissible controllers is formulated in the form of linear matrix inequalities (LMIs), and the controller design is cast into a convex optimisation problem subject to LMI constraints. If the optimisation problem is solvable, a desired controller can be readily constructed. The result for the norm-bounded uncertainty case improves the existing ones in terms of design conservatism, and that for the LFT uncertainty case represents the first attempt in this direction. An ill...

Monostability and multistability of genetic regulatory networks with different types of regulation functions

Abstract: Monostability and multistability are proven to be two important topics in synthesis biology and system biology. In this paper, both monostability and multistability are analyzed in a unified framework by applying control theory and mathematical tools. The genetic regulatory networks (GRNs) with multiple time-varying delays and different types of regulation functions are considered. By putting forward a general sector-like regulation function and utilizing up-to-date techniques, a novel Lyapunov–Krasovskii functional is introduced for achieving delay dependence to ensure less conservatism. A new condition is then proposed for the general stability of a GRN in the form of linear matrix inequalities (LMIs) that are dependent on the upper and lower bounds of the delays. Our general stability conditions are applicable to several frequently used regulation functions. It is shown that the existing results for monostability of GRNs are special cases of our main results. Five examples are employed to illustrate the applicability and usefulness of the developed theoretical results.

Robust H∞ feedback control for uncertain stochastic delayed genetic regulatory networks with additive and multiplicative noise

Abstract: Noises are ubiquitous in genetic regulatory networks (GRNs). Gene regulation is inherently a stochastic process because of intrinsic and extrinsic noises that cause kinetic parameter variations and basal rate disturbance. Time delays are usually inevitable due to different biochemical reactions in such GRNs. In this paper, a delayed stochastic model with additive and multiplicative noises is utilized to describe stochastic GRNs. A feedback gene controller design scheme is proposed to guarantee that the GRN is mean-square asymptotically stable with noise attenuation, where the structure of the controllers can be specified according to engineering requirements. By applying control theory and mathematical tools, the analytical solution to the control design problem is given, which helps to provide some insight into synthetic biology and systems biology. The control scheme is employed in a three-gene network to illustrate the applicability and usefulness of the design. Copyright © 2010 John Wiley & Sons, Ltd.

On multistability of delayed genetic regulatory networks with multivariable regulation functions.

Abstract: Many genetic regulatory networks (GRNs) have the capacity to reach different stable states. This capacity is defined as multistability which is an important regulation mechanism. Multiple time delays and multivariable regulation functions are usually inevitable in such GRNs. In this paper, multistability of GRNs is analyzed by applying the control theory and mathematical tools. This study is to provide a theoretical tool to facilitate the design of synthetic gene circuit with multistability in the perspective of control theory. By transforming such GRNs into a new and uniform mathematical formulation, we put forward a general sector-like regulation function that is capable of quantifying the regulation effects in a more precise way. By resorting to up-to-date techniques, a novel Lyapunov-Krasovskii functional (LKF) is introduced for achieving delay dependence to ensure less conservatism. New conditions are then proposed to ensure the multistability of a GRN in the form of linear matrix inequalities (LMIs) that are dependent on the delays. Our multistability conditions are applicable to several frequently used regulation functions especially the multivariable ones. Two examples are employed to illustrate the applicability and usefulness of the developed theoretical results.

Sampled-data consensus for multiple agents with discrete second-order dynamics

Abstract: In this paper, the problem of sampled-data consensus is investigated for multiple agents with double-integrator dynamics. Consensus analysis under both fixed and dynamic network topology is conducted from different perspectives. First, a necessary and sufficient condition for the agents under fixed network topology to reach consensus is derived by introducing some assumptions on the sampling period and the velocity damping gain. Next, the consensus problem for agents under dynamic network topology is studied by extending the method developed for agents under fixed network topology. In particular, for agents under a special class of dynamic network topology, an analysis is made of the consensus equilibria, a topic which has received less attention in the existing literature.

Fault detection with network communication

Abstract: This article investigates the problem of fault detection for continuous time systems with network communication links. A network communication channel is assumed to be existing between the plant and the fault detection filter, and three types of incomplete measurements which typically appear in a network environment are simultaneously addressed, including measurement quantisation effect, signal transmission delay and data packet dropout. A mathematical model is presented to account for those issues in a unified form. Based on that, a full-order fault detection filter is designed such that the residual system is asymptotically stable and preserves a guaranteed performance. A sufficient condition of the existence of the fault detection filter is obtained and all the results are formulated in the form of linear matrix inequalities, which can be readily solved via standard numerical software. Finally, a simulation example is provided to illustrate the usefulness of the developed theoretical results.

Dynamics analysis of gene regulatory networks

Abstract: Pioneering theoretical work on gene regulatory networks (GRNs) has anticipated the emergence of postgenomic research and provided a mathematical framework for the current description and analysis o...

Fault-tolerant output tracking control for a flexible air-breathing hypersonic vehicle

Abstract: This paper addresses the problem of guaranteed cost fault-tolerant output tracking control against actuator faults for a flexible air-breathing hypersonic vehicle. Firstly, using the parameters of the trim condition, a linearized model is established around the trim point for a nonlinear, dynamically coupled simulation model. Secondly, the control objective and models of actuator faults are presented. Thirdly, the performance analysis condition is proposed in the frame of convex optimization problems via Lyapunov functional approach. Then, the stand controller and fault-tolerant controller are designed such that the resulting closed-loop system is asymptotically stable and satisfies a prescribed performance cost respectively. Finally, the simulation results are given to show the effectiveness of the proposed control method, which is verified by excellent reference altitude and velocity tracking performance.