On Feedback Control Techniques of Nonlinear Analytic Systems

Elloumi, Salwa; Braïek, Naceur Benhadj

doi:10.1016/s1665-6423(14)71630-x

Cited by 16 publications

(3 citation statements)

References 28 publications

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“…Furthermore, Q( Xt ) and R( Xt ) not only are constants, but also can be varying functions of state. In this way, different behavior patterns can be applied in different regions of the system's state space [29,30].…”

Section: Control Problem Formulationmentioning

confidence: 99%

Nonlinear Optimal Feedback Control of the Two-Level Open Non-Markovian Stochastic Quantum System

Qamar

Cong

et al. 2021

Open Syst. Inf. Dyn.

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In this paper, a nonlinear optimal feedback control based on the nonlinear state estimator for a two-level open non-Markovian stochastic quantum system is proposed. The proposed nonlinear state estimator is designed by using the state-dependent differential Riccati equation and constructed to optimally estimate the state. The estimated state is updated by the output data of continuous weak measurement of the controlled quantum system and used to design the nonlinear state feedback controller to track the output of the reference model. The output state of reference model is chosen as the desired performance. The numerical simulation results verify the achievability of the proposed state feedback control strategy, and the capability to steer the state of system from any arbitrary initial state to the final reference target state with high state transfer success rate.

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Section: Control Problem Formulationmentioning

confidence: 99%

Nonlinear Optimal Feedback Control of the Two-Level Open Non-Markovian Stochastic Quantum System

Qamar

Cong

et al. 2021

Open Syst. Inf. Dyn.

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“…The stability of SDRE systems is still an open issue (Elloumi and Benhadj Braiek, 2014; Elloumi et al, 2012; Feydi et al, 2016). Local stability results are presented by Adhyaru et al (2009) and Heydari and Balakrishnan (2015) for the case where the closed-loop coefficient matrix is assumed to have a special structure.…”

Section: Stability Studymentioning

confidence: 99%

Decentralized finite-horizon suboptimal control for nonlinear interconnected dynamic systems using SDRE approach

Feydi

Elloumi

Jammazi

et al. 2019

Transactions of the Institute of Measurement and Control

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This paper introduces a new approach to ensure the decentralized horizon suboptimal control of interconnected nonlinear systems based on the decentralized finite-state-dependent Riccati equation. This approach is, in fact, a new extension of the state-dependent Riccati equation technique with a finite horizon for the case of large-scale nonlinear systems, which are characterized by the interconnection of n subsystems. The main finding in this work is the use of the Lyapunov direct method of stability analysis, associated with a quadratic function, in order to determine a new sufficient condition to guarantee the global asymptotic stability of the studied systems. We conducted advanced simulations of this new control method on three interconnected inverted pendulums. Our results demonstrate its efficiency and the sufficiency of the new stability conditions.

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“…Modeling, stability analysis, and control of nonlinear and complex systems is one of the most important problems that have attracted the attention of researchers (Benhadj, 1995; Bouzaouache and Benhadj, 2008; Elloumi and Benhadj, 2014; Elloumi et al, 2016; Lakshmikantham et al, 1991; Loussifi et al, 2016; Ortega et al, 1998; Phulpin et al, 2011). The resolution of such problems should take into account several factors.…”

Section: Introductionmentioning

confidence: 99%

Development of a decentralized nonlinear controller for a class of uncertain polynomial interconnected systems: Application for a large scale power system

Rtibi

Elloumi

Braïek

2018

Transactions of the Institute of Measurement and Control

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This paper presents a new robust decentralized control of nonlinear interconnected systems, which is applied and validated on a large scale power system. Our work is performed in three steps. Firstly, we have developed the polynomial description of the nonlinear uncertain and interconnected system using odd Kronecker power of state vectors, which is an easy-manipulation model for such complex systems. Then we applied Lyapunov’s direct method of stability analysis, associated with a quadratic function, in order to determine a sufficient condition for global asymptotic stability by applying a nonlinear, decentralized and optimal polynomial control. Finally, we carried out a simulation study on a nonlinear uncertain power system with three interconnected machines. We considered different cases of perturbations on its state variables as well as different cases of fault locations. We prove via advanced simulations, the effectiveness of the proposed control technique which is able to mitigate the successive amplitudes of the oscillations, to limit the control actions and to enhance the power system transient stability.

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On Feedback Control Techniques of Nonlinear Analytic Systems

Abstract: How to citeComplete issue More information about this article Journal's homepage in redalyc.org Scientific Information System Network of Scientific Journals from Latin America, the Caribbean, Spain and Portugal Non-profit academic project, developed under the open access initiative

Cited by 16 publications

References 28 publications

Nonlinear Optimal Feedback Control of the Two-Level Open Non-Markovian Stochastic Quantum System

Nonlinear Optimal Feedback Control of the Two-Level Open Non-Markovian Stochastic Quantum System

Decentralized finite-horizon suboptimal control for nonlinear interconnected dynamic systems using SDRE approach

Development of a decentralized nonlinear controller for a class of uncertain polynomial interconnected systems: Application for a large scale power system

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