Robust controller design for uncertain systems with time delays: LMI approach

Jeung, Eun Tae; Oh, Do Chang; Kim, Jong Hae; Park, Hong Bae

doi:10.1016/0005-1098(96)00055-6

Cited by 118 publications

(37 citation statements)

References 6 publications

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“…In this section, a numerical example is presented to validate the performance and effectiveness of the nonlinear discrete-time system proposed in Equation (4). Consider the set of parameters for the given system 0.8 0.4 0.14 0.1…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Its implementation by a digital system requires sampling interval which leads to chattering. Over the past few decades, considerable attention has been reported to the stability analysis of continuous time delay systems by using different approaches [4]- [10]. In [4], robust controller has been designed for continuous time delay system using Ricacati equation approach.…”

Section: Introductionmentioning

confidence: 99%

“…Over the past few decades, considerable attention has been reported to the stability analysis of continuous time delay systems by using different approaches [4]- [10]. In [4], robust controller has been designed for continuous time delay system using Ricacati equation approach. Considerable, attention has been given using LMI approach for stabilization of continuous time delay systems [5]- [8].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Robust Sliding Mode Control for Nonlinear Discrete-Time Delayed Systems Based on Neural Network

Goyal¹,

Deolia²,

Sharma³

2015

ICA

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This paper presents a robust sliding mode controller for a class of unknown nonlinear discretetime systems in the presence of fixed time delay. A neural-network approximation and the Lyapunov-Krasovskii functional theory into the sliding-mode technique is used and a neural-network based sliding mode control scheme is proposed. Because of the novality of Chebyshev Neural Networks (CNNs), that it requires much less computation time as compare to multi layer neural network (MLNN), is preferred to approximate the unknown system functions. By means of linear matrix inequalities, a sufficient condition is derived to ensure the asymptotic stability such that the sliding mode dynamics is restricted to the defined sliding surface. The proposed sliding mode control technique guarantees the system state trajectory to the designed sliding surface. Finally, simulation results illustrate the main characteristics and performance of the proposed approach.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Robust Sliding Mode Control for Nonlinear Discrete-Time Delayed Systems Based on Neural Network

Goyal¹,

Deolia²,

Sharma³

2015

ICA

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“…Because time delays are frequently encountered in chemical processes, e.g., long transmission lines in pneumatic, hydraulic, rolling mill systems, and other engineering systems, time-delay systems have been studied; some results on the analysis and synthesis for such systems have been presented [2], [5], [8], [9], [10], [13]. In recent years, much interest has been focused on the problems of robust H ∞ filtering for uncertain delay systems.…”

Section: Introductionmentioning

confidence: 99%

Robust H∞ Filtering for Uncertain Discrete Stochastic Systems with Time Delays

Lam

Gao

et al. 2005

Circuits Syst Signal Process

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This paper considers the problem of robust H ∞ filtering for uncertain discretetime stochastic systems with time-varying delays. The parameter uncertainties are assumed to be real time-varying norm-bounded in both the state and measurement equations. The problem to be addressed is the design of a stable filter that guarantees stochastic stability and a prescribed H ∞ performance level of the filtering error system for all admissible uncertainties and time delays. A sufficient condition for the existence of such filters is obtained in terms of a linear matrix inequality (LMI). For the case when this LMI is feasible, an explicit expression for a desired filter is given. An illustrative example is also provided to demonstrate the effectiveness and applicability of the proposed method.

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“…The problem of stabilizing uncertain systems with (1) constant delay [3], [11]; (2) time-varying delay [5], [11]; (3) constant delay and parameter uncertainty [10], [13]; and (4) time-varying delay and parameter uncertainty [1], [7], [8] has attracted much interest in recent years. A summary of the existing literature on robust stability bounds for continuous uncertain systems is given in Yedavalli et al [15].…”

Section: Introductionmentioning

confidence: 99%

Robust Output-Feedback Control for Linear Continuous Uncertain State Delayed Systems with Unknown Time Delay

Shieh

2002

Circuits Syst Signal Process

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The state-delayed time often is unknown and independent of other variables in most real physical systems. In this paper, a new stability criterion for uncertain systems with a state time-varying delay is proposed. Then, a robust observer-based control law based on this criterion is constructed via the sequential quadratic programming method. We also develop a separation property so that the state feedback control law and observer can be independently designed and maintain closed-loop system stability. An example illustrates the availability of the proposed design method.

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Robust controller design for uncertain systems with time delays: LMI approach

Cited by 118 publications

References 6 publications

Robust Sliding Mode Control for Nonlinear Discrete-Time Delayed Systems Based on Neural Network

Robust Sliding Mode Control for Nonlinear Discrete-Time Delayed Systems Based on Neural Network

Robust H∞ Filtering for Uncertain Discrete Stochastic Systems with Time Delays

Robust Output-Feedback Control for Linear Continuous Uncertain State Delayed Systems with Unknown Time Delay

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