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This paper is concerned with the problem of robust exponential stability for discrete-time BAM neural networks with mode-dependent time delays and Markovian jump parameters, by utilizing the Lyapunov functional and combining with the linear matrix inequality (LMI) approach, the global exponential stability is investigated. The time delay varies in an interval and depends on the mode of operation....
This paper deals with the problem of delay dependent stability for the master-slave networked control system with time-varying state delays. Based on Lyapunov stability theory combined with linear matrix inequalities (LMIs) and a stabilizing feedback controller is designed techniques, one new delay dependent stability criteria in terms of LMIs are derived by taking the relationship between the terms...
This paper investigates the problem of robust stability for a class of uncertain discrete-time stochastic recurrent neural networks (RNNs) with Markovian jumping parameters and mode-dependent delays. Stochastic item is nonlinear, and jumping parameters are considered as discrete time, discrete-state Markov process. We can get novel robust stability conditions in terms of linear matrix inequality (LMI)...
The proposed controller design algorithm in this paper can take into account independently both the magnitude and rate constraints on actuator dynamics. The control law is constructed in terms of linear matrix inequalities. A suitable chosen initial state condition, which can represent the desired set of tracking commands, is treated as a parameter for the controller design algorithm. By the example...
This paper proposes a controller for a generally linearized TCP/AQM network congestion-avoiding model with different delay times in the system state and control input. In order to deal with the delay times varying in the network, the controller does not employ the delay times directly. At the same time, an input constraint is considered in the controller design.
In this paper, diagnosis of actuator/component faults for a class of networked control nonlinear systems based on fuzzy T-S model using adaptive observer techniques is investigated. At first, under certain conditions, a stable adaptive fault diagnosis observer is proposed. Then based on the fault estimation information, a fault tolerant control is designed to recover the system performance using LMI...
The object of this paper is to design a LMI-based fuzzy controller for a MIMO two-link robot arm using quantum evolutionary algorithms. The Takagi-Sugeno (T-S) fuzzy approach is utilized to represent the equation of motion of two-link robot arm. The stability of the fuzzy system is guaranteed by linear matrix inequality (LMI) from Lyapunov stability approach. The quantum evolutionary algorithms (QEA)...
The problem of robust control for a class of networked uncertain switching fuzzy system is investigated, based on the single-packet condition. A state feedback controller is designed via Parallel Distributed Compensation. The matrice inequalities condition of system stability and a switching law are given via multiple Lyapunov function. Simulation examples show the effectiveness of the results.
This paper proposed the design of T-S fuzzy control for magnetic levitation systems. The maglev systems are linearized at the equilibrium point first. Then the error state equations are derived and the proportional integral (PI) controller is applied to eliminate the steady-state tracking error. The nonlinear dynamic equations of the magnetic levitation systems are represented by a T-S fuzzy model...
The problems of robust stability and stabilization of a class of linear neutral systems with norm-bounded uncertainties are studied in this paper. We focus on the delay dependent robust stability and stabilization problem with respect to the uncertainty (i.e., finding robust stability conditions containing delay information). Some sufficient conditions on stability and stabilization are derived in...
A synthesis approach of constrained robust model predictive control (SCRMPC) for systems with polytopic description is proposed. This proposal uses time-varying sequences of models in a polytope to forecast the model uncertainties and optimizes the terminal constrained set, the local controller and the terminal cost on-line. Using standard techniques, the problem is reduced to a convex optimization...
This paper is concerned with the problem of fault tolerant H?? controller design for polytopic uncertain systems against actuator faults. The type of fault mode describes as a more general and practical continuous fault model. A sufficient condition for the existence of fault tolerant controller is given by parameter-dependent Lyapunov function approach, which guarantees the closed loop system is...
It has been reported in the literature that cellular neural networks (CNN) are effective as associative memories and they have been applied to many kinds of pattern recognition tasks. Flexibility of their design can be increased by expanding the output function from being 2-valued to being multi-valued. As a design method for associative memories, SVD (singular value decomposition) is popular, but...
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