Output feedback adaptive fuzzy control of uncertain MIMO nonlinear systems with unknown input nonlinearities

Shahnazi, Reza

doi:10.1016/j.isatra.2014.07.006

Cited by 29 publications

(11 citation statements)

References 42 publications

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“…, y p −ŷ p ] T and α is a non-zero small constant. Based on discussion in [19,41] the control law does not have singularity problem and is well-defined in cases whenĜ(x|(θ Lg ,θ Rg )) is not invertible, with ε is a small positive design parameter. Consider matrix equality BB T εI p + BB T −1 =…”

Section: The Proposed Observer-based Methodsmentioning

confidence: 99%

“…In order to analyze stability of the closed-loop system and derive adaptive laws, since onlyẽ y in (30) is measurable, we use the strictly positive real (SPR) Lyapunov design method [41][42][43]. Due to discussion in (13), the observation error dynamics (30) can be written as…”

Section: The Proposed Observer-based Methodsmentioning

confidence: 99%

“…Clearly, the transfer matrix H(s) is not SPR [41][42][43]. In order to have an SPR transfer matrix and thus using SPR-Lyapunov synthesis approach, (32) is written as…”

Section: The Proposed Observer-based Methodsmentioning

confidence: 99%

“…Since H(s)L(s) is SPR there exist symmetric positive-definite matrices P 2 and Q 2 such that [41][42][43] …”

Section: The Proposed Observer-based Methodsmentioning

confidence: 99%

“…On the other hand, in many nonlinear models the gain of saturation is not constant and usually is function of states and the upper and lower bounds of input saturation are unknown. Besides, many mechanical, electrical and chemical systems are MIMO nonlinear systems [40,41]. Therefore, it is essential to propose an output feedback method to control uncertain MIMO nonlinear systems with unknown states and unknown asymmetric saturation actuators whose gains are unknown nonlinear functions.…”

Section: Introductionmentioning

confidence: 99%

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Observer-based adaptive interval type-2 fuzzy control of uncertain MIMO nonlinear systems with unknown asymmetric saturation actuators

Shahnazi

2016

Neurocomputing

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Section: The Proposed Observer-based Methodsmentioning

confidence: 99%

Section: The Proposed Observer-based Methodsmentioning

confidence: 99%

“…Clearly, the transfer matrix H(s) is not SPR [41][42][43]. In order to have an SPR transfer matrix and thus using SPR-Lyapunov synthesis approach, (32) is written as…”

Section: The Proposed Observer-based Methodsmentioning

confidence: 99%

“…Since H(s)L(s) is SPR there exist symmetric positive-definite matrices P 2 and Q 2 such that [41][42][43] …”

Section: The Proposed Observer-based Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Observer-based adaptive interval type-2 fuzzy control of uncertain MIMO nonlinear systems with unknown asymmetric saturation actuators

Shahnazi

2016

Neurocomputing

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Adaptive Fuzzy Descriptor Sliding Mode Observer‐based Sensor Fault Estimation for Uncertain Nonlinear Systems

Shahnazi

Zhao

2015

Asian Journal of Control

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A sensor fault estimation method is proposed for a general class of uncertain nonlinear systems. Taking the sensor faults as auxiliary states, an augmented descriptor system is constructed. For this augmented descriptor system, an adaptive fuzzy proportional‐derivative sliding mode observer is designed to estimate the sensor faults and states, simultaneously. Adaptive fuzzy systems based on the universal approximation theorem are used to approximate the nonlinearities. Thus, the nonlinearities can be unknown and the Lipschitz assumption can be utterly relieved. To relax the requirement of knowing the bound of uncertainties, an adaptive gain for the sliding mode term is used. The semi‐global asymptotic convergence of the proposed fault estimation observer is proved using the Lyapunov approach. The proposed method is applied to a highly nonlinear mathematical model with both bounded and unbounded sensor faults. Simulation results show the satisfactory performance of the proposed method.

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Adaptive Neural Control Design of MIMO Nonaffine Nonlinear Systems with Input Saturation

Zerari

Chemachema

Essounbouli

2018

Advanced Control Engineering Methods in Electrical Engineering Systems

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Output feedback adaptive fuzzy control of uncertain MIMO nonlinear systems with unknown input nonlinearities

Cited by 29 publications

References 42 publications

Observer-based adaptive interval type-2 fuzzy control of uncertain MIMO nonlinear systems with unknown asymmetric saturation actuators

Observer-based adaptive interval type-2 fuzzy control of uncertain MIMO nonlinear systems with unknown asymmetric saturation actuators

Adaptive Fuzzy Descriptor Sliding Mode Observer‐based Sensor Fault Estimation for Uncertain Nonlinear Systems

Adaptive Neural Control Design of MIMO Nonaffine Nonlinear Systems with Input Saturation

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