Quantized dynamic output feedback control for networked control systems

The problem of the quantized dynamic output feedback controller design for networked control systems is mainly discussed. By using the quantized information of the system measurement output and the control input, a novel networked control system model is described. This model includes many networkinduced features, such as multi-rate sampled-data, quantized signal, time-varying delay and packet dropout. By constructing suitable Lyapunov-Krasovskii functional, a less conservative stabilization criterion is established in terms of linear matrix inequalities. The quantized control strategy involves the updating values of the quantizer parameters μi（i = 1, 2）（μi take on countable sets of values which dependent on the information of the system measurement outputs and the control inputs）. Furthermore, a numerical example is given to illustrate the effectiveness of the proposed method.

Bifurcation suppression of nonlinear systems via dynamic output feedback and its applications to rotating stall control

This paper deals with the problems of bifurcation suppression and bifurcation suppression with stability of nonlinear systems. Necessary conditions and sufficient conditions for bifurcation suppression via dynamic output feedback are presented; Sufficient conditions for bifurcation suppression with stability via dynamic output feedback are obtained. As an application, a dynamic compensator,which guarantees that the bifurcation point of rotating stall in axial flow compressors is stably suppressed, is constructed.

Sampled-Data H_(∞)Dynamic Output Feedback Controller Design for Fuzzy Markovian Jump Systems

This paper considers the issue of H_(∞)dynamic output feedback controller design for T-S fuzzy Markovian jump systems under time-varying sampling with known upper bound on the sampling intervals.The main aim is to realize sampled-data fuzzy dynamic output feedback control so as to demonstrate the stochastic stability and H_(∞)performance index of the closed-loop sampled-data fuzzy Markovian jump systems.Then,by making the most of the information within the sampling interval,a suitable closed-loop function is constructed and the integral terms are handled by using free weighted matrix method and improved integral inequality technique.Numerical example and single-link robot arm are presented to show the effectiveness of the developed method.

Dynamic output feedback stabilization of deterministic finite automata via the semi-tensor product of matrices approach

This paper deals with the dynamic output feedback stabilization problem of deterministic finite automata(DFA).The static form of this problem is defined and solved in previous studies via a set of equivalent conditions.In this paper,the dynamic output feedback(DOF)stabilization of DFAs is defined in which the controller is supposed to be another DFA.The DFA controller will be designed to stabilize the equilibrium point of the main DFA through a set of proposed equivalent conditions.It has been proven that the design problem of DOF stabilization is more feasible than the static output feedback(SOF)stabilization.Three simulation examples are provided to illustrate the results of this paper in more details.The first example considers an instance DFA and develops SOF and DOF controllers for it.The example explains the concepts of the DOF controller and how it will be implemented in the closed-loop DFA.In the second example,a special DFA is provided in which the DOF stabilization is feasible,whereas the SOF stabilization is not.The final example compares the feasibility performance of the SOF and DOF stabilizations through applying them to one hundred random-generated DFAs.The results reveal the superiority of the DOF stabilization.

Analysis and design of output feedback control systems with actuator saturation

A dynamic output feedback controller design approach based on cone complementary linearisation procedure is proposed for linear time-invariant （LTI） systems with actuator saturation. First, the estimation of the domain of attraction is given. Then, a design method to find a larger estimation of the domain of attraction is presented. In the process of design, nonconvex conditions are obtained, so a cone complementary linearisation procedure is exploited to solve the nonconvex feasibility problem. Two examples are given to illustrate the efficiency of the design method.

Output Feedback Control of Discrete-Time T-S Fuzzy Affine Systems Using Quantized Measurements

This paper investigates the problem of robust H!fixed-order dynamic output feedback( DOF)controller design for a class of Takagi-Sugeno( T-S) fuzzy affine systems using quantized measurements.Through a state-input augmentation method,some sufficient conditions for controller synthesis are developed based upon piecewise quadratic Lyapunov functions( PQLFs) in terms of LMIs. Two illustrative studies are conducted to verify the effectiveness of the proposed controller synthesis approach.

Dynamic Consensus of High-order Multi-agent Systems and Its Application in the Motion Control of Multiple Mobile Robots

In this paper, the leader-following consensus problem for multi-agent linear dynamic systems is considered. All agents and leader have identical multi-input multi-output （MIMO） linear dynamics that can be of any order, and only the output information of each agent is delivered throughout the communication network. When the interaction topology is fixed, the leader-following consensus is attained by Ho~ dynamic output feedback control, and the sufficient condition of robust controllers is equal to the solvability of linear matrix inequality （LMI）. The whole analysis is based on spectral decomposition and an equivalent decoupled structure achieved, and the stability of the system is proved. Finally, we extended the theoretical results to the case that the interaction topology is switching. The simulation results for multiple mobile robots show the effectiveness of the devised methods.

Optimal injection attack strategy for cyber-physical systems:a dynamic feedback approach

This paper investigates the system security problem of cyber-physical systems(CPSs),which is not only more practical but also more significant to deal with than the detecting faults problem.The purpose of this paper is to find an optimal attack strat-egy that maximizes the output error of the attacked system with low energy consumption.Based on a general model of linear time-invariant systems and a key technical lemma,a new optimal attack strategy for the meticulously designed false data injection attack is constructed.It is worth mentioning that compared with the existing model-based attack strategies,the designed one is more general and the corresponding attack strategy is more easily implemented when system states and external input are inaccessible.Key to overcom-ing the inaccessible information,a dynamic observer in the form of Luenberger is constructed.Finally,a networked magnetic levitation steel ball movement system is applied to illustrate the effectiveness of the proposed scheme.

Robust H_∞ control for aseismic structures with uncertainties in model parameters

This paper presents a robust H∞ output feedback control approach for structural systems with uncertainties in model parameters by using available acceleration measurements and proposes conditions for the existence of such a robust output feedback controller. The uncertainties of structural stiffness, damping and mass parameters are assumed to be norm-bounded. The proposed control approach is formulated within the framework of linear matrix inequalities, for which existing convex optimization techniques, such as the LM1 toolbox in MATLAB, can be used effectively and conveniently. To illustrate the effectiveness of the proposed robust H∞ strategy, a six-story building was subjected both to the 1940 E1 Centro earthquake record and to a suddenly applied Kanai-Tajimi filtered white noise random excitation. The results show that the proposed robust H∞ controller provides satisfactory results with or without variation of the structural stiffness, damping and mass parameters.

Robust H_∞ control for neutral stochastic uncertain systems with time-varying delay

The problem of robust H_∞ control for uncertain neutral stochastic systems with time-varying delay is discussed.The parameter uncertaintie is assumed to be time varying norm-bounded.First,the stochastic robust stabilization of the stochastic system without disturbance input is investigated by nonlinear matrix inequality method.Then,a full-order stochastic dynamic output feedback controller is designed by solving a bilinear matrix inequality（BMI）,which ensures a prescribed stochastic robust H_∞ performance level for the resulting closed-loop system with nonzero disturbance input and for all admissible uncertainties.An illustrative example is provided to show the feasibility of the controller and the potential of the proposed technique.

Optimal injection attack strategy for cyber-physical systems:a dynamic feedback approach

This paper investigates the system security problem of cyber-physical systems(CPSs),which is not only more practical but also more signi cant to deal with than the detecting faults problem.The purpose of this paper is to nd an optimal attack strategy that maximizes the output error of the attacked system with low energy consumption.Based on a general model of linear time-invariant systems and a key technical lemma,a new optimal attack strategy for the meticulously designed false data injection attack is constructed.It is worth mentioning that compared with the existing model-based attack strategies,the designed one is more general and the corresponding attack strategy is more easily implemented when system states and external input are inaccessible.Key to overcoming the inaccessible information,a dynamic observer in the form of Luenberger is constructed.Finally,a networked magnetic levitation steel ball movement system is applied to illustrate the e ectiveness of the proposed scheme.

Quadratic stabilization for uncertain stochastic systems

This paper discusses the robust quadratic stabilization control problem for stochastic uncertain systems, where the uncertain matrix is norm bounded, and the external disturbance is a stocbastic process, Two kinds of controllers are designed, which include state feedback case and output feedback case. The conditions for the robust quadratic stabilization of stochastic uncertain systems are given via linear matrix inequalities. The detailed design methods are presented. Numerical examples show the effectiveness of our results.