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Dive into the research topics where Shuping He is active.

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Featured researches published by Shuping He.


Neurocomputing | 2013

Letters: Finite-time boundedness of uncertain time-delayed neural network with Markovian jumping parameters

Shuping He; Fei Liu

The stochastic finite-time boundedness (FTB) problem is considered for a class of Markovian jumping neural networks (MJNNs) with time delay and uncertainties. By selecting the appropriate stochastic Lyapunov-Krasovskii functional, sufficient conditions of stochastic FTB of MJNNs are presented and proved. The FTB criteria are formulated in the form of linear matrix inequalities. Simulation results illustrate the effectiveness of the developed approaches.


Applied Mathematics and Computation | 2010

Observer-based finite-time control of time-delayed jump systems

Shuping He; Fei Liu

Abstract This paper provides the observer-based finite-time control problem of time-delayed Markov jump systems that possess randomly jumping parameters. The transition of the jumping parameters is governed by a finite-state Markov process. The observer-based finite-time H∞ controller via state feedback is proposed to guarantee the stochastic finite-time boundedness and stochastic finite-time stabilization of the resulting closed-loop system for all admissible disturbances and unknown time-delays. Based on stochastic finite-time stability analysis, sufficient conditions that ensure stochastic robust control performance of time-delay jump systems are derived. The control criterion is formulated in the form of linear matrix inequalities and the designed finite-time stabilization controller is described as an optimization one. The presented results are extended to time-varying delayed MJSs. Simulation results illustrate the effectiveness of the developed approaches.


Applied Mathematics and Computation | 2008

Unbiased H∞ filtering for neutral Markov jump systems

Shuping He; Fei Liu

Abstract The unbiased H ∞ filtering problem is studied for stochastic Markov jump system with constant and neutral time-delays. By re-constructing the system, the dynamic filtering error characteristics of unknown inputs and time-delays are obtained. A sufficient condition is initially established on the existence of mode-dependent unbiased H ∞ filter of constant time-delay system using stochastic Lyapunov–Krasovskii function. Then, the unbiased H ∞ filter is also designed for the jump system with constant and neutral time-delays. The design criterions are presented in the form of linear matrix inequality. Finally, the unbiased H ∞ filtering problems are described as optimization algorithms. Numerical examples illustrate the effectiveness of the developed techniques.


Fuzzy Sets and Systems | 2011

Filtering-based robust fault detection of fuzzy jump systems

Shuping He; Fei Liu

This paper studies the robust fault detection filter (RFDF) design problems for uncertain nonlinear Markov jump systems with state delays and parameter uncertainties. By means of Takagi-Sugeno fuzzy models, the dynamics of filtering error generator and the fuzzy RFDF system are constructed. With the aid of the selected weighting matrix function, the design objective is to find an optimal RFDF which results in a minimal difference between the reference model (ideal solution) and the RFDF (real solution) to be designed. A sufficient condition is firstly established on the stochastic stability by using stochastic Lyapunov-Krasovskii functional approach. Then in terms of linear matrix inequalities techniques, sufficient conditions on the existence of fuzzy RFDF are presented and proved. Finally, the design problem is formulated as an optimization algorithm. Simulation results illustrate that the proposed RFDF can detect the faults shortly after the occurrences.


Signal Processing | 2011

Robust stabilization of stochastic Markovian jumping systems via proportional-integral control

Shuping He; Fei Liu

This paper studied the proportional-integral (PI) control problems of stochastic Markovian jump systems (MJSs) with uncertain parameters. Under complete access to the system states, the PI controller design procedure turns to static output feedback control problem that make the closed-loop dynamics of this class of uncertain MJSs be robustly stochastically stable. A sufficient condition on the existence of PI controller is presented and proved by means of linear matrix inequality techniques. The presented results are extended to the case when the system states are not accessible. In order to make the relative equations approximate with a satisfactory precision, we described the problem as a semidefinite programming one via disciplined convex optimization. Simulation results illustrate the validity of the proposed algorithms.


Neurocomputing | 2015

Finite-time robust passive control for a class of uncertain Lipschitz nonlinear systems with time-delays

Jun Song; Shuping He

The finite-time passive control for a class of nonlinear uncertain systems with time-delays and uncertainties is studied. The nonlinear parameters are satisfied Lipschitz conditions. An optimal robust passive controller with respect to the finite-time interval is designed while the exogenous disturbances are unknown but energy bounded. Based on passive control theory, the sufficient condition for the existence of finite-time robust passive controller is given. This condition such that the resulting closed-loop system is finite-time boundedness (FTB) for all admissible uncertainties and satisfies the given passive control index. By using the constructed Lyapunov function, and applying linear matrix inequalities techniques (LMIs), the design method of the finite-time optimal passive controller is derived and can be obtained. Simulation results demonstrate the validity of the proposed approach.


Neurocomputing | 2015

Non-fragile passive controller design for nonlinear Markovian jumping systems via observer-based controls

Shuping He

Abstract The paper deals with the problem of non-fragile observer-based passive control for a class of Markovian jumping systems (MJSs) subjected to uncertainties, nonlinearities and time-delays. Based on the Takagi–Sugeno fuzzy models, the dynamics of mode-dependent non-fragile state observer and feedback controller system and the combined closed-loop fuzzy dynamic MJSs are constructed. A sufficient condition for passivity and stochastic stability of the combined system is derived and proved by means of the Lyapunov–Krasovskii functional methods and linear matrix inequalities (LMIs) techniques. The non-fragile passive controller and observer parameters can be solved directly by using the existing LMIs optimization techniques. Finally, a numerical simulation is given to illustrate the performance of the proposed approach.


Journal of Dynamic Systems Measurement and Control-transactions of The Asme | 2010

Stochastic Finite-Time Stabilization for Uncertain Jump Systems via State Feedback

Shuping He; Fei Liu

The stochastic finite-time stabilization problem is considered for a class of linear uncertain Markov jump systems that possess randomly jumping parameters. The transition of the jumping parameters is governed by a finite-state Markov process. By using the appropriate stochastic Lyapunov-Krasovskii functional approach, sufficient conditions are proposed for the design of stochastic finite-time stabilization controller. The stabilization criteria are formulated in the form of linear matrix inequalities and the designed finite-time stabilization controller is described as an optimization one. The designed finite-time stabilized controller makes the stochastic MJSs stochastic finite-time bounded and stochastic finite-time stabilizable for all admissible unknown external disturbances and uncertain parameters. Simulation results illustrate the effectiveness of the developed approaches.


Journal of The Franklin Institute-engineering and Applied Mathematics | 2014

Optimal finite-time passive controller design for uncertain nonlinear Markovian jumping systems

Shuping He; Fei Liu

Abstract This paper studies the optimal finite-time passive control problem for a class of uncertain nonlinear Markovian jumping systems (MJSs). The Takagi and Sugeno (T–S) fuzzy model is employed to represent the nonlinear system with Markovian jump parameters and norm-bounded uncertainties. By selecting an appropriate Lyapunov-Krasovskii functional, it gives a sufficient condition for the existence of finite-time passive controller such that the uncertain nonlinear MJSs is stochastically finite-time bounded for all admissible uncertainties and satisfies the given passive control index in a finite time-interval. The sufficient condition on the existence of optimal finite-time fuzzy passive controller is formulated in the form of linear matrix inequalities and the designed algorithm is described as an optimization one. A numerical example is given at last to illustrate the effectiveness of the proposed design approach.


Journal of The Franklin Institute-engineering and Applied Mathematics | 2015

Robust finite-time H∞ control for one-sided Lipschitz nonlinear systems via state feedback and output feedback

Jun Song; Shuping He

Abstract Robust finite-time H ∞ control of a class of continuous-time nonlinear system with parameter uncertainties and disturbance input is discussed in this note. The nonlinear function is considered to satisfy the one-sided Lipschitz condition, which has less conservative than the well-known global Lipschitz nonlinear condition. By means of linear matrix inequality (LMI) techniques, both design algorithms of state-feedback controller and static output-feedback controller are developed. The designed controllers are proved to guarantee the corresponding closed-loop systems that are finite-time boundedness (FTB) with a desired H ∞ performance index. And the best scalars selection criterion is used to determine the finite-time scalars such that the LMI-based conditions with the best feasibility in the global field. Finally, a numerical example is included to verify the efficiency of the proposed methods.

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Zhengtao Ding

University of Manchester

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