Adaptive fuzzy synergetic control for nonlinear hysteretic systems

Rebai, Aissa; Guesmi, Kamel; Hemici, Boualem

doi:10.1007/s11071-016-3088-3

Cited by 21 publications

(21 citation statements)

References 45 publications

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“…[32][33][34] However, in adaptive control approaches, inefficient adaptation may occur, especially when rapid parameter variations occur in the controlled system, which directly jeopardises the control performance. To enhance the robustness and efficiency of adaptation, many techniques, such as Kalman filters, 3 observers, 35 real-time parameter estimation, 36 fuzzy theory, 37 and a backstepping technique, 38,39 have been proposed. NSBC 11 has recently been developed for controlling nonlinear systems, without requiring detailed information about the nonlinearities in the systems.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear signal‐based control for single‐axis shake tables supporting nonlinear structural systems

Enokida

Kajiwara

2019

Struct Control Health Monit

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Summary Nonlinear signal‐based control (NSBC) is very powerful for controlling structural systems with parameter variations and has the advantage that the controllers can be designed using classical control theory and expressed by transfer functions. This report describes the first application of NSBC to shake table tests with nonlinear specimens and compares the performance of NSBC with that of a basic control approach that relies on the inverse transfer function of the controlled system. NSBC and the basic approach were numerically applied to shake table tests to excite a nonlinear single‐degree‐of‐freedom system with earthquake acceleration motion, considering the nonlinear specimen characteristics and estimation errors associated with the table dynamics. NSBC achieved excellent control with near 100% accuracy, whereas the basic approach provided insufficient control. Although inaccurate estimation of the pure time delay in the controlled system causes instability at the practice of NSBC, proper design of the nonlinear signal feedback controller prevented instability. In experimental examinations, controllers for the two approaches were designed on the basis of the table dynamics with/without a specimen, which were preliminarily identified by performing tests using a random wave with small amplitude excitations. With no specimen present, both approaches yielded the expected acceleration motion on the table with high accuracy. However, with the specimen present, only NSBC successfully achieved excellent control of the shake table with near 100% accuracy, whereas the basic approach did not because of the specimen nonlinearity. These results numerically and experimentally demonstrate the efficiency and practicality of NSBC for shake tables supporting nonlinear structures.

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Section: Introductionmentioning

confidence: 99%

Nonlinear signal‐based control for single‐axis shake tables supporting nonlinear structural systems

Enokida

Kajiwara

2019

Struct Control Health Monit

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“…Inefficient adaptation occurs especially when nonlinear structural systems show rapid parameter variations, directly jeopardising the control performance. To enhance the robustness and the efficiency of the adaptation, many studies have proposed improvements using various additional techniques such as Kalman filters, 2 observers, 40 real-time parameter estimation, 41 fuzzy theory, 42 and a backstepping technique. 43,44 Nonlinear signal-based control (NSBC) has recently been proposed to control nonlinear structural systems.…”

Section: Introductionmentioning

confidence: 99%

Stability of nonlinear signal‐based control for nonlinear structural systems with a pure time delay

Enokida

2019

Struct Control Health Monit

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Nonlinear signal-based control (NSBC) has recently been developed for nonlinear structural systems. NSBC shows high tracking performance in structural systems that display parameter variations during control practice. This control approach is also efficient for substructuring experimentation, an advanced technique based on real-time interaction between physical experiments and numerical simulations. NSBC allows controller design to be based on classical control theory, with the controllers expressed by transfer functions. Without losing this benefit, this study proposes to analyse the stability of NSBC for nonlinear structural systems and a pure time delay by employing the Nyquist stability criterion, which is also classified into classical stability theory.Then stability analysis that regards the nonlinearity as a parameter variation associated with the linear model of the controlled system has been established in this study. The efficiency and practicality of the stability analysis are examined via numerical control practices for various nonlinear single-and multiple-degree-of-freedom (S/MDOF) systems having pure time delay. In the examination, the controlled systems are nonlinear SDOF and 2DOF systems with different types of nonlinear springs. In the numerical simulations, two control practices for NSBC (i.e., the nonlinear signal feedback action with or without the error feedback action) have offered excellent control with near 100% accuracy. Stability analysis of NSBC has accurately provided the stability conditions for the nonlinear controlled systems with a pure time delay.

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“…In nonadaptive controllers, the most used techniques are nonlinear output feedback, synergetic, and sliding mode controllers because of their capabilities in controlling nonlinear systems. Besides the sliding mode control, a synergetic control (SC) technique has recently attracted the attention of many researchers [9][10][11][12][13][14][15][16] since it shares with the SMC the same idea of forcing the closed-loop system to move on a desired manifold, but without the chattering phenomenon. 17 The SC theory was firstly introduced by the Russian researcher Kolesnikov 18 and it has been investigated in hysteretic systems, 9 DC-DC boost converters, 10 robot manipulators, 13 fault tolerant system, 16 and power system stabilizers.…”

Section: Introductionmentioning

confidence: 99%

“…Besides the sliding mode control, a synergetic control (SC) technique has recently attracted the attention of many researchers [9][10][11][12][13][14][15][16] since it shares with the SMC the same idea of forcing the closed-loop system to move on a desired manifold, but without the chattering phenomenon. 17 The SC theory was firstly introduced by the Russian researcher Kolesnikov 18 and it has been investigated in hysteretic systems, 9 DC-DC boost converters, 10 robot manipulators, 13 fault tolerant system, 16 and power system stabilizers. [19][20][21] However, the control design procedures of the SC and most of the proposed techniques in the literature require extensive knowledge of the system parameters and dynamics so that the control law can be designed, ie, the reason why researchers are interested in developing adaptive techniques based on observers and estimators that can deal with systems with unknown (unmodeled) parameters (dynamics).…”

Section: Introductionmentioning

confidence: 99%

“…For example, in the works of Wang et al 22 and Zhou et al, 23 a fuzzy-based adaptive control methods are proposed for nonlinear systems with unmodeled dynamics. In the works of Rebai et al 9 and Bouchama and Harmas, 20 adaptive and optimal adaptive synergetic controllers (ASCs) are proposed under the idea of estimating the unknown system dynamic by using fuzzy logic. In the work of Nechadi et al, 21 a Type-2 fuzzy system to approximate the unknown nonlinear dynamics for the design of an SC is introduced.…”

Section: Introductionmentioning

confidence: 99%

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A passivity‐based simple adaptive synergetic control for a class of nonlinear systems

Mokhtari

Elhadri

Aribi

2019

Adaptive Control & Signal

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For a class of nonlinear systems with the representation {A(x), B(x), C} and where the system parameters and dynamics are unknown, a simple adaptive synergetic controller ensuring the asymptotic convergence of the system to a desired manifold is proposed based on the technique of simple adaptive control (SAC). It is well known that the design of the synergetic control (SC) law requires a thorough knowledge of the system parameters and dynamics. Such problem obstructs the synthesis of the SC law and the designer is prompted to pass through the estimation methods, which, in turn, poses a problem of increasing the computation time of the control algorithm. To cope with this problem, a solution is proposed by modifying the original SC law to develop an SAC-like adaptive SC law without the need of prior knowledge of the system. The stability of the proposed adaptive controller is formally proven via the Lyapunov approach. Experimental application to a quadrotor system is given to validate the theoretical results. KEYWORDSadaptive synergetic control, almost strict passivity, quadrotor system, simple adaptive control

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Adaptive fuzzy synergetic control for nonlinear hysteretic systems

Cited by 21 publications

References 45 publications

Nonlinear signal‐based control for single‐axis shake tables supporting nonlinear structural systems

Nonlinear signal‐based control for single‐axis shake tables supporting nonlinear structural systems

Stability of nonlinear signal‐based control for nonlinear structural systems with a pure time delay

A passivity‐based simple adaptive synergetic control for a class of nonlinear systems

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