Adaptive fuzzy control of a class of nonaffine nonlinear system with input saturation based on passivity theorem

Molavi, Ali; Jalali, Ahvand; Naraghi, Mehdi Ghasemi

doi:10.1016/j.isatra.2017.03.020

Cited by 29 publications

(21 citation statements)

References 39 publications

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“…Giving the properties of N i1 , N i2 , and N i3 in (46). Based on the bounds of the characteristic parameters provided by (20), we can prove that there exist c i1 , c i2 , and c i3 > 0, such that N i1 ∈ (0, 1); N i2 and N i3 > 0. To prove these, it suffices to show that…”

Section: Theoremmentioning

confidence: 99%

“…Over the past decades, nonaffine nonlinear system control has received considerable attention, and many important results have been presented on the design of such controllers [5-12, 14, 15]. Owing to the universal approximation theorem, some adaptive control schemes based on fuzzy logic systems [16][17][18][19][20][21][22] and neural networks [8,10,[23][24][25] have been developed for uncertain nonaffine nonlinear systems. Nevertheless, these approaches typically incur heavy computational costs.…”

Section: Introductionmentioning

confidence: 99%

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Characteristic Model-Based Adaptive Control for a Class of MIMO Uncertain Nonaffine Nonlinear Systems Governed by Differential Equations

Duoqing

2020

Complexity

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This paper addresses the difficulty of designing a controller for a class of multi-input multi-output uncertain nonaffine nonlinear systems governed by differential equations. We first derive the first-order characteristic model composed of a linear time-varying uncertain system for such nonaffine systems and then design an adaptive controller based on this first-order characteristic model for position tracking control. The designed controller exhibits a simple structure that can effectively avoid the controller singularity problem. The stability of the closed-loop system is analyzed using the Lyapunov method. The effectiveness of our proposed method is validated with a numerical example.

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Section: Theoremmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Characteristic Model-Based Adaptive Control for a Class of MIMO Uncertain Nonaffine Nonlinear Systems Governed by Differential Equations

Duoqing

2020

Complexity

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“…Assume all the nonlinearities and parameters are unknown, define the perturbations ψ 1 (·) and ψ 2 (·) for system (18) to aggregate all the nonlinearties, generator uncertainties, and external disturbances of f 1 , f 2 , and B into a lumped term, such that they can be rewritten into a concise form, it yields:…”

Section: Rpc Design Of Dfig For Power System Stability Enhancementmentioning

confidence: 99%

Nonlinear Observer-Based Robust Passive Control of Doubly-Fed Induction Generators for Power System Stability Enhancement via Energy Reshaping

Dong

Li²,

Wu³

et al. 2017

Energies

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Abstract:The large-scale penetration of wind power might lead to degradation of the power system stability due to its inherent feature of randomness. Hence, proper control designs which can effectively handle various uncertainties become very crucial. This paper designs a novel robust passive control (RPC) scheme of a doubly-fed induction generator (DFIG) for power system stability enhancement. The combinatorial effect of generator nonlinearities and parameter uncertainties, unmodelled dynamics, wind speed randomness, is aggregated into a perturbation, which is rapidly estimated by a nonlinear extended state observer (ESO) in real-time. Then, the perturbation estimate is fully compensated by a robust passive controller to realize a globally consistent control performance, in which the energy of the closed-loop system is carefully reshaped through output feedback passification, such that a considerable system damping can be injected to improve the transient responses of DFIG in various operation conditions of power systems. Six case studies are carried out while simulation results verify that RPC can rapidly stabilize the disturbed DFIG system much faster with less overshoot, as well as supress power oscillations more effectively compared to that of linear proportional-integral-derivative (PID) control and nonlinear feedback linearization control (FLC).

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“…9,10 Saturation error is traditionally treated as a system disturbance to obtain a good control effect, However, the real-time tracking performance is different from the expected effect. 11,12 Therefore, in order to ensure that the faults caused by input saturation are quickly and effectively suppressed during train operation. 13 We need to consider two control objectives.…”

Section: Introductionmentioning

confidence: 99%

Tracking control via sliding mode for heavy-haul trains with input saturation

Yang

Zhang

et al. 2020

Measurement and Control

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To address the tracking control problem of heavy-haul trains (HHTs) with input saturation during operation, an anti-saturation sliding mode (SMES) control method based on dynamic auxiliary compensator (DAC) is presented. Firstly, an HHT model with nonlinear coupling and uncertain disturbances is built. Secondly, a new type of DAC is introduced to overcome the difficulty of traditional dynamic auxiliary compensator (TDAC) with a large upper bound on the compensation signal. Finally, an anti-saturation SMES control algorithm is designed to reduce the influence of input saturation on the tracking accuracy of each carriage. Simulation results verify the effectiveness of the algorithm in terms of tracking accuracy, anti-interference, and anti-saturation.

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Adaptive fuzzy control of a class of nonaffine nonlinear system with input saturation based on passivity theorem

Cited by 29 publications

References 39 publications

Characteristic Model-Based Adaptive Control for a Class of MIMO Uncertain Nonaffine Nonlinear Systems Governed by Differential Equations

Characteristic Model-Based Adaptive Control for a Class of MIMO Uncertain Nonaffine Nonlinear Systems Governed by Differential Equations

Nonlinear Observer-Based Robust Passive Control of Doubly-Fed Induction Generators for Power System Stability Enhancement via Energy Reshaping

Tracking control via sliding mode for heavy-haul trains with input saturation

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