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Optimisation of parallel distributed compensation for Real Time Control of Level in Carbonisation Column

AUTOMATIC CONTROL AND COMPUTER SCIENCES 2020年第5期54卷 379-390页

作者： Yordanova, S. Slavov, M. Gueorguiev, B. Tech Univ Sofia Fac Automat Sofia 1000 Bulgaria Solvay Sodi SA Devnya 9160 Bulgaria

Nonlinear plants with derived Takagi-Sugeno-Kang plant models can be successfully controlled by model-based fuzzy logic controllers built as parallel distributed compensation (PDC). The PDC simple structure of a few fuzzy rules facilitates both the design based on the well-mastered linear control technique and the real time industrial implementation via programmable logic controllers. The novelty of the present research is the optimisation of the PDC tuning parameters in order to improve the performance of the closed-loop system for the control of the liquid level in a carbonisation column for soda ash production. A multiobjective optimisation is carried out off-line using genetic algorithms and simulations. The improvement of the closed-loop system dynamic accuracy and the reduction of the control action variance for saving lifetime of the expensive control valve are assessed via simulation and real time industrial experiments in comparison to the system with the tuned by classical approaches PDC.

关键词： carbonisation column level control genetic algorithms parallel distributed compensation real time experimentation Takagi– Sugeno– Kang model

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parallel distributed compensation for improvement of level control in carbonization column for soda production

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CONTROL ENGINEERING PRACTICE 2018年 71卷 53-60页

作者： Yordanova, Snejana Slavov, Milen Gueorguiev, Branimir Tech Univ Sofia Fac Automat Sofia 1000 Bulgaria Solvay Sodi SA Devnya Bulgaria

The liquid level control is essential in many production installations but the classic approaches often fail to ensure the desired performance. The reasons are the plant nonlinearity, the level oscillations and the plant model uncertainties. The aim of the present investigation is to improve the existing linear control of the level in the carbonization columns for soda ash production by employing fuzzy logic using parallel distributed compensation (PDC). The design of the PDC is based on a nonlinear Takagi-Sugeno-Kang (TSK) plant model which is derived via genetic algorithms optimization and validated using the data from the real time linear level control. The PDC control performs soft blending of the outputs of several parallel local linear controllers each developed for the local linear plant of the TSK model. The fuzzy rules are represented by ordinary logics conditions to enable the PDC programming and use by an industrial programmable logic controller. The PDC increases the dynamic accuracy in the level control and reduces the frequency of the control oscillations compared to the previous linear control thus prolonging the lifetime of the expensive pneumatic actuators used. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Carbonization column Level control parallel distributed compensation Takagi-Sugeno-ICang plant modelling

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parallel distributed compensation for Voltage Controlled Active Magnetic Bearing System using Integral Fuzzy Model 9

Parallel Distributed Compensation for Voltage Controlled Act...

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9th International Conference on Intelligent Systems (IS)

作者： Tatchum, Martial Gegov, Alexander Jafari, Raheleh Razvarz, Sina Univ Portsmouth Sch Comp Portsmouth Hants England Univ Agder CAIR Grimstad Norway Natl Polytech Inst Dept Control Automat Mexico City DF Mexico

ISBN: (纸本)9781538670972

parallel distributed compensation (PDC) for current-controlled Active Magnetic Bearing System (AMBS) has been quite effective in recent years. However, this method does not take into account the dynamics associated with the electromagnet. This limits the method to smaller scale applications where the electromagnet dynamics can be neglected. Voltage-controlled AMBS is used to overcome this limitation but this comes with serious challenges such as complex mathematical modelling and higher order system control. In this work, a PDC with integral part is proposed for position and input tracking control of voltage controlled AMBS. PDC method is based on nonlinear TakagiSugeno (T-S) fuzzy model. It is shown that the proposed method outperforms the conventional fuzzy PDC. It stabilizes the bearing shaft at any chosen operating point and tracks any chosen smooth trajectory within the air gap with a high external disturbance rejection capability.

关键词： Takagi-Sugeno Active Magnetic Bearings parallel distributed compensation AMB voltage-controlled

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Design of new fuzzy sliding mode controller based on parallel distributed compensation controller and using the scalar sign function

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MATHEMATICS AND COMPUTERS IN SIMULATION 2017年 132卷 277-288页

作者： Chaouech, Lotfi Soltani, Moez Dhahri, Slim Chaari, Abdelkader Natl Higher Engn Sch Tunis ENSIT Res Unit Control Monitoring & Safety Syst C3S 5Ave Taha HusseinBP 56 Tunis 1008 Tunisia

This paper presents a new design of fuzzy sliding mode controller based on parallel distributed compensation and using a scalar sign function. The proposed fuzzy sliding mode controller (FSMC) uses the parallel distributed compensation (PDC) scheme to design the state feedback control law. The controller gains are determined in offline mode via linear quadratic regulator technique. Moreover, the fuzzy sliding surface of the system is designed using stable eigenvectors and the scalar sign function in order to overcome the discontinuous switching. This later is obtained by a sign function of the standard FSMC. The advantages of the proposed design are a minimum energy control effort, faster response and zero steady-state error. Finally, the validity of the proposed design strategy is demonstrated through the simulation of a flexible joint robot. (C) 2016 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.

关键词： Takagi-Sugeno fuzzy model Sliding mode control parallel distributed compensation Linear quadratic regulator Scalar sign function

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New delay-dependent finite-time stabilization of Takagi-Sugeno fuzzy approaches for delayed nonlinear systems

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ASIAN JOURNAL OF CONTROL 2025年第3期27卷 1119-1134页

作者： El Fezazi, Nabil Fahim, Mohamed Idrissi, Said Farkous, Rashid Alvarez, Teresa Tissir, El Houssaine Ibn Zohr Univ Higher Sch Technol Dakhla Morocco Sidi Mohammed Ben Abdellah Univ Fac Sci Dhar El Mehraz Dept Phys LISAC Lab Fes Morocco Ibn Tofail Univ Comp Sci Res Lab Kenitra Morocco Mohammed V Univ Higher Sch Technol Sale Rabat Morocco Univ Valladolid Ind Engn Sch Dr Mergelina S N Valladolid 47005 Spain

In this paper, the finite-time stability and stabilization of nonlinear systems with delays is studied, via a Takagi-Sugeno approach. By using a novel Lyapunov-Krasovskii functional and introducing some fuzzy free-weighting matrices, sufficient conditions are derived, for bounded and differentiable time-varying delays in terms of an upper bound of the delay derivatives. Then, we achieve closed-loop stabilization in finite time through an efficient parallel distributed compensation design. The sufficient conditions are formulated as linear matrix inequalities to achieve the desired performance. Finally, the proposed methodology is applied to various case studies, highlighting its significance.

关键词： finite-time stability nonlinear systems parallel distributed compensation T-S fuzzy approach

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An Approach to Generate the LQR Based Takagi-Sugeno Fuzzy Model Controller for Nonlinear System

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INTERNATIONAL JOURNAL OF FUZZY SYSTEMS 2025年 1-12页

作者： Yang, Zhi-Xiang Jhong, Bing-Gang Su, Shun-Feng Chen, Mei-Yung Natl Taiwan Normal Univ Dept Mechatron Engn Taipei 106209 Taiwan Natl Taiwan Univ Sci & Technol Dept Elect Engn Taipei 106335 Taiwan

In this paper, we propose a general method for designing Takagi-Sugeno (T-S) fuzzy model controllers, applicable to a general class of nonlinear systems represented in state-space form. The method is an automated controller design process that introduces the BLOCK concept. Through the automatic division of BLOCKs, the system is divided into more subsystems, and corresponding fuzzy rules and membership functions are automatically generated, significantly shortening the development time for systems with known system models. According to T-S fuzzy theory, nonlinear systems are decomposed into multiple linear subsystems governed by fuzzy rules. Unlike conventional methods that rely on linear matrix inequalities (LMI), which may suffer from infeasibility or excessively large controller gains and generally involve higher computational complexity, we integrate the linear quadratic regulator (LQR) approach to enhance stability and performance. The LQR method offers a more computationally efficient solution while still achieving effective control. The effectiveness of the proposed automated process is demonstrated through its application to a two-link robotic manipulator, showcasing its ability to improve tracking accuracy. Experimental results confirm that the proposed controller outperforms conventional PID control, achieving reduced tracking errors and demonstrating the practicality of the method for broader nonlinear control applications.

关键词： Takagi-Sugeno fuzzy model Linear-quadratic regulator parallel distributed compensation Two-link robotic manipulator

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Design a robust and optimal fuzzy logic controller to stabilize the speed of an electric vehicle in the presence of uncertainties and external disturbances

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TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL 2024年第3期46卷 482-500页

作者： Mousaei, Arash Rostami, Naghi Sharifian, Mohammad Bagher Bannae Univ Tabriz Dept Elect Engn Tabriz Iran Univ Tabriz Dept Elect Engn Tabriz *** Iran

In the nonlinear dynamic equations of the electric vehicle, parameters such as the coefficient of friction between the tires and the road, the coefficient of traction, the resistance of the anchor, and so on have ambiguities. Designing a controller that is robust to the existence of these parametric ambiguities and also to external disturbances, while still satisfying the optimality criteria, is a challenging task. In practical applications, in addition to the problems mentioned above, the computing load of the control input should also be taken into account and a sensible interaction between the performance desired by the controller and the computing volume should be offered. In the present work, a robust, optimally stable fuzzy controller based on parallel distributed compensation is designed using the Takagi-Sugeno fuzzy model of the electric vehicle. The fuzzy model stabilizer feedback gains, the upper bound of uncertainties, the upper bound of disturbance effect, and the upper bound of the cost function are obtained completely offline by solving a minimization problem based on the linear matrix inequality. Therefore, the calculation volume of the control input is extremely small. This allows the proposed control to be put into practice. The good performance of the proposed controller is demonstrated in five-stage simulations.

关键词： Electric vehicle fuzzy controller parallel distributed compensation optimization

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H-Infinity Approach Control On Takagi-Sugeno Fuzzy Model For 2-D Overhead Crane System

JOURNAL OF APPLIED SCIENCE AND ENGINEERING

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JOURNAL OF APPLIED SCIENCE AND ENGINEERING 2025年第5期28卷 995-1003页

作者： Nguyen, Manh-Linh Nguyen, Hoang-Phat Nguyen, Thi-Van-Anh Hanoi Univ Sci & Technol Hanoi Vietnam

In this paper, H-infinity control serves as primary strategy in combating external disturbance for overhead crane systems. The overhead crane model consists of a trolley, its cable tethering to a load, which is a highly nonlinear model. Therefore, the goal of moving the trolley while minimizing the oscillation of the load is challenging, particularly in the face of external disturbances. The Takagi-Sugeno (T-S) fuzzy model is employed to delineate the intricacies of the nonlinear overhead crane model. The design of the fuzzy controller relies on the parallel distributed compensation (PDC) concept, focusing on rule-based control within the T-S fuzzy model framework. Linear Matrix Inequalities (LMIs) are formulated based on stability conditions using Lyapunov functions combined with H-infinity performance, facilitating the computation of controller parameters. Subsequently, simulations are conducted to assess the efficacy of the H-infinity control strategy under the influence external disturbances.

关键词： Takagi-Sugeno Fuzzy Model Linear Matrix Inequality parallel distributed compensation H-infinity Reject Disturbance Overhead Crane

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CONTROLLER DESIGN FOR UNMANNED BICYCLES BASED ON TENSOR PRODUCT MODEL TRANSFORMATION AND VARIABLE UNIVERSE FUZZY CONTROL

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INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL 2025年第2期21卷 447-455页

作者： Wang, Degang Xie, Depeng Zhao, Guoliang Li, Hongxing Dalian Univ Technol Sch Control Sci & Engn 2 Linggong Rd Dalian 116024 Peoples R China Inner Mongolia Univ Coll Elect Informat Engn 235 East Second Ring West Rd Hohhot 010021 Peoples R China

. In this paper, a tensor product variable universe fuzzy (TPVUF) controller is designed for stabilizing the balance of unmanned bicycles. Firstly, the nonlinear exact model of the unmanned bicycles is obtained using Kane's method, and then the tensor product (TP) model transformation technique is used to derive the tensor product model of the unmanned bicycles. Subsequently, the TPVUF controller utilizes the gain calculated by the parallel distributed compensation (PDC) method as fusion coefficients of the error and its rate of change in the variable universe fuzzy (VUF) method. The VUF control method has the ability to quickly converge the error and its rate of change, which improves the response speed of the TPVUF controller. Finally, simulation experiments validate the effectiveness of the designed controller.

关键词： Unmanned bicycles Quasi-linear parametric model Tensor product model transformation parallel distributed compensation Variable universe fuzzy control

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Takagi-Sugeno fuzzy-based approach for modeling and control of an activated sludge process

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INTERNATIONAL JOURNAL OF DYNAMICS AND CONTROL 2024年第8期12卷 3123-3138页

作者： Arifi, Ali Bouallegue, Soufiene Natl Engn Sch Tunis Res Lab Automat Control Tunis 1002 Tunisia Univ Gabes Natl Engn Sch Gabes Gabes 6029 Tunisia Univ Gabes Higher Inst Ind Syst Gabes Gabes 6032 Tunisia

Wastewater treatment systems have recently taken on new trends resulting from the growing awareness of health and environmental risks. New strategies aimed at the recovery of treated water are increasingly being proposed. Given its better performance, biological treatment via an activated sludge process (ASP) represents the key phase in the overall treatment chain. In this work, a Takagi-Sugeno (TS) fuzzy-based modeling and control approach of an ASP is proposed and successfully carried out for the carbon removal. Using the formalism of linear parameter-varying state-space representation and convex polytopic transformation, a TS fuzzy model of the studied ASP is firstly established. Such a fuzzy model is then used to design advanced control laws that maintain the considered state variables, i.e., volume of the effluent and concentrations of the heterotrophic biomass, biodegradable substrate and dissolved oxygen, at the set-point values. Two stabilization control approaches, namely parallel distributed compensation and static output parallel distributed compensation, are proposed and successfully applied. All these control problems are reformulated as Lyapunov quadratic stability conditions and linear matrix inequality constraints. Demonstrative results are carried out and compared to show the effectiveness and superiority of the proposed TS fuzzy-based control approach of such complex and nonlinear biochemical processes.

关键词： Wastewater treatment systems Activated sludge process Carbon removal Takagi-Sugeno fuzzy modeling parallel distributed compensation Static output feedback control

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