A Stable Model-Based Fuzzy Predictive Control Based on Fuzzy Dynamic Programming

Belarbi, Khaled; Megri, Fayçal

doi:10.1109/tfuzz.2006.890656

Cited by 21 publications

(4 citation statements)

References 23 publications

(57 reference statements)

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“…However, thanks to its ability ability to give an accurate approximation of the complex nonlinear systems, the fuzzy models of the Takagi-Sugeno (TS) type proved to be suitable for the use in nonlinear MPC. So, an adaptive fuzzy logic systems (AFLS) is employed to determine the parameters of the AFLS as well as the controller structure (Angelov and Filev, 2004; Belarbi and Megri, 2007). In this strategy, the AFLS is used as the prediction model of the nonlinear process and the system performance is greatly dependent upon the online optimization.…”

Section: Introductionmentioning

confidence: 99%

RETRACTED: Constrained cuckoo search algorithm and Takagi-Sugeno fuzzy models for predictive control

Taeib

Salhi

Châari

2020

Transactions of the Institute of Measurement and Control

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In this paper, a new predictive control scheme formulated by using the Takagi-Sugeno fuzzy modeling method and a new constrained cuckoo search algorithm. The cuckoo search algorithm is used to determine the predictive controls by minimizing a constrained criterion. The Takagi-Sugeno fuzzy modelling approach is applied to forecast the states of the process. At the optimization stage, the proposed cuckoo search provides the control action taking into account constraints. The performances of the developed method are tested during its application in the three-tank process. Therefore, the experimental results demonstrate that the combination of the philosophy of the fuzzy model and cuckoo search is very good in the controlling of nonlinear processes. In addition, the closed-loop performance of the developed method is compared to approach based with the particle swarm optimisation algorithm and those obtained with fuzzy model predictive controller.

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Section: Introductionmentioning

confidence: 99%

RETRACTED: Constrained cuckoo search algorithm and Takagi-Sugeno fuzzy models for predictive control

Taeib

Salhi

Châari

2020

Transactions of the Institute of Measurement and Control

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“…There are a number of acoustic and optical techniques to estimate the dynamic profile of the fluid. 36 Coherent doppler LiDAR is one such system to estimate the wind velocity of the approaching upwind by emission of coherent light from the origin and the reflected signal from the target. In this work, it is assumed that the wind field is non-evolving or the evolution of the wind speed is ignored since its effect is negligible.…”

Section: Lidar and Sensors Enabledmentioning

confidence: 99%

Fatigue load mitigation in wind turbine using a novel anticipatory predictive control strategy

G¹,

Xavier²,

Vr³

2019

Proceedings of the Institution of Mechanical Engineers, Part I:

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Wind energy has become a recent evolving source of renewable energy which needs an extensive exploration. The increased configuration of wind turbine instantaneously increases the structural loading of wind turbine components. The prolonged loading on structural components imposes a great impact on the lifetime of the wind turbine and reduces the feasibility of thinner rotor blade. These economical detriments due to the structural damage of turbine are dealt effectively by proposing an anticipatory preview-based control strategy for individual pitching of blades. The proposed multiple point model predictive controller with fuzzy logic switching, exploits the preview wind measurement from the light detection and ranging system which predicts the wind speed in advance. The utmost objective of the proposed controller is its optimized individual blade pitching to reduce the fatigue loads on the wind turbine components using the preview wind data. The blade root bending moment of individual blades and the tower fore-aft deflection which are chosen as the parameters of fatigue stress to be analyzed and controlled. The National Renewable Energy Laboratory’s Fatigue, Aerodynamics, Structures and Turbulence 5 MW baseline onshore wind turbine is used for validating the proposed controller in MATLAB simulation. The non-linear wind field is simulated using the TurbSim software, and the short-term and lifetime damage equivalent loads of the wind turbine for the simulated wind field is analyzed using the MLife software of the National Renewable Energy Laboratory. The proposed controller is compared with the typical model predictive controller and linear quadratic-based controller.

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“…We show that the minimum aggregation operator does not guarantee, in general, the convergence of the infinite horizon optimal control with fuzzy objective functions to the equilibrium for all feasible initial states. We show the non-convergence of this control law by deriving an analytical solution for a simple first-order linear system using fuzzy dynamic programming [24], [25].…”

Section: Introductionmentioning

confidence: 99%

Infinite horizon fuzzy optimal control: optimality does not imply asymptotic stability

Teniou

Belarbi²

2023

IJECE

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In this paper, novel stability result for discrete-time infinite horizon optimal control using fuzzy objective functions is presented. For this class of control, the fuzzy goals and the fuzzy constraints introduced in the fuzzy objective function handle the constraints placed on both the state and the control vectors. We analyze the asymptotic stability of the equilibrium for the infinite horizon fuzzy optimal control law using the minimum aggregation operator. We show that the infinite horizon control with the minimum aggregation operator does not guarantee the asymptotic stability of the equilibrium in general. This is done by deriving an analytical solution of the control law for a simple linear system using a fuzzy dynamic programming approach. An example that shows the novel asymptotic stability result of the equilibrium for discrete-time infinite horizon optimal control with fuzzy objective function problem is given.

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A Stable Model-Based Fuzzy Predictive Control Based on Fuzzy Dynamic Programming

Cited by 21 publications

References 23 publications

RETRACTED: Constrained cuckoo search algorithm and Takagi-Sugeno fuzzy models for predictive control

RETRACTED: Constrained cuckoo search algorithm and Takagi-Sugeno fuzzy models for predictive control

Fatigue load mitigation in wind turbine using a novel anticipatory predictive control strategy

Infinite horizon fuzzy optimal control: optimality does not imply asymptotic stability

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