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constrained generalized predictive control of battery charging process based on a coupled thermoelectric model

JOURNAL OF POWER SOURCES 2017年 347卷 145-158页

作者： Liu, Kailong Li, Kang Zhang, Cheng Queens Univ Belfast Sch Elect Elect Engn & Comp Sci Belfast BT9 5AH Antrim North Ireland

Battery temperature is a primary factor affecting the battery performance, and suitable battery temperature control in particular internal temperature control can not only guarantee battery safety but also improve its efficiency. This is however challenging as current controller designs for battery charging have no mechanisms to incorporate such information. This paper proposes a novel battery charging control strategy which applies the constrained generalized predictive control (GPC) to charge a LiFePO4 battery based on a newly developed coupled thermoelectric model. The control target primarily aims to maintain the battery cell internal temperature within a desirable range while delivering fast charging. To achieve this, the coupled thermoelectric model is firstly introduced to capture the battery behaviours in particular SOC and internal temperature which are not directly measurable in practice. Then a controlled auto-regressive integrated moving average (CARIMA) model whose parameters are identified by the recursive least squares (RLS) algorithm is developed as an online self-tuning predictive model for a GPC controller. Then the constrained generalized predictive controller is developed to control the charging current. Experiment results confirm the effectiveness of the proposed control strategy. Further, the best region of heat dissipation rate and proper internal temperature set-points are also investigated and analysed. (C) 2017 Published by Elsevier B.V. All rights reserved.

关键词： LiFePO4 battery constrained generalized predictive control Coupled thermoelectric model Battery internal temperature Battery charging process

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A Population Extremal Optimization Based Modified constrained generalized predictive control Method 29

A Population Extremal Optimization Based Modified Constraine...

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第29届中国控制与决策会议

作者： Hai-Yang Liu Kang-Di Lu Guo-Qiang Zeng Huan Wang Yu-Xing Dai National-Local Joint Engineering Laboratory of Digitalize Electrical Design Technology Wenzhou University Department of Automation College of Information Sciences and TechnologyDonghua University College of Electrical and Information Engineering Hunan University

ISBN: (纸本)9781509046584

As one of the most popular and successful methods in industrial applications,model predictive control(MPC)has attracted increasing interest in the past two ***,one of open issues in this research filed is how to solve the constrained nonlinear optimization problems in *** the perspective of evolutionary algorithm,this paper presents a novel population extremal optimization(PEO) based modified constrained generalized predictive control(CGPC) method called *** key idea behind the proposed CGPC-PEO is using PEO for rolling optimization to minimize the weighted objective function subjecting to a set of *** superiority to other evolutionary algorithms such as genetic algorithm and particle swarm optimization based CGPC is demonstrated by the simulation results on an industrial process plant.

关键词： constrained generalized predictive control Population Extremal Optimization Evolutionary Algorithms Rolling Optimization

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Adaptive constrained generalized predictive controller for the PMSM speed servo system to reduce the effect of different load torques

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e-Prime - Advances in Electrical Engineering, Electronics and Energy 2022年 2卷

作者： Asvadi-Kermani, Omid Felegari, Bashir Momeni, Hamidreza Department of Control Tarbiat Modares University Faculty of Electrical and Computer Engineering Iran

Fractional-order models have been used in recent years to model the number of processes and applications like boilers, supercapacitors, power electronic devices, permanent magnet synchronous motor (PMSM) speed servo systems, and batteries in many papers. In this paper DC motor equivalent fractional-order model is used to model the PMSM speed servo system. This model has two parts: The electrical part and the Mechanical part. Every aspect has a fractional-order differential equation with an independent fractional order parameter. Its real value is unknown, but its span is evident. To specify the model stability region and to simulate it, the fractional model is approximated with a recursive (Oustaloup) filter. In this work, the PMSM motor's speed is controlled by applying the adaptive recursive least squares (RLS-based) constrained generalized predictive controller (GPC) over the system with unknown model order and in the presence of two types of loads: constant load torque, sinusoidal load. In the last section, adaptive constrained generalized predictive controller (AGPC) has been implemented on the real system. Experimental results also show this controller performance. © 2022 The Author(s)

关键词： Adaptive control constrained generalized predictive control Disturbance effect Fractional-order model PMSM speed servo

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An adaptive CGPC based anti-windup PI controller with stability constraints for the intermittent power penetrated system

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2021年 130卷 106922-106922页

作者： Liu, Wanying Zheng, Yang Chen, Qijuan Geng, Dazhou Wuhan Univ Minist Educ Key Lab Transients Hydraul Machinery Wuhan 430072 Peoples R China

With the increasing penetration of the renewable energy, the modern power system is facing greater challenges to maintain the frequency stability, which can be studied with load frequency control (LFC). Since the conventional proportional integral (PI) controller can?t necessarily satisfy the ever-growing robustness requirement, an adaptive constrained generalized predictive control (CGPC) based anti-windup PI controller with stability constraints is proposed, which is referred to as CGPC-PI in this article. Wherein, the CGPC logic in the upper hierarchy acts as a real-time optimizer for the PI parameters in the lower hierarchy. The proposed control scheme inherits the self-tuning and adaptive control characteristics from CGPC and can maintain the facilities and control logic from PI. Furthermore, simpler stability constraints and performance improvement could be gained considering that PI is the actual implementing control method. Simulation experiments are conducted to reveal the frequency regulation performances in a Generation Rate Constraint (GRC) and Governor Deadband (GDB) involved interconnected power system with intermittent power penetration. The results can testify the superiority of CGPC-PI over the comparative methods in terms of the overshoot and damping performance, which includes:(1) CGPC-PI outperforms PI and CGPC. (2) the superiority is more obvious when working with varying disturbances which is big enough can trigger the anti-windup scheme. (3) CGPC-PI can enhance the frequency regulation performance of the intermittent power penetrated systems.

关键词： Load frequency control constrained generalized predictive control Stability constraints The anti-windup scheme

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control of Organic Rankine Cycle for Waste Heat Recovery Based on An Optimized predictive Model 36

Control of Organic Rankine Cycle for Waste Heat Recovery Bas...

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第36届中国控制会议

作者： Kailong Liu Kang Li Mingming Lin Jianhua Zhang Queen's University Belfast Qingdao University of Science and Technology North China Electric Power University

ISBN: (纸本)9781538629185

The Organic Rankine Cycle(ORC) is a promising technique to recover low grade waste heat,and thus helps to improve the overall thermal efficiency of a process and reduce the environmental impact of large consumption of fossil fuels.A proper control strategy is a key for the safe and efficient operation of the ORC *** this paper,the key components in the ORC system are introduced *** a constrained generalized predictive control(CGPC) is designed to control the process.A controlled auto-regressive integrated moving average(CARIMA) model is used as the online self-tuning predictive model for the GPC controller,while the structure of the CARIMA model is optimized by the fast recursive algorithm(FRA).Simulation results confirm that the developed ORC control strategy is capable of achieving desirable set-point tracking performance,while also has a satisfactory disturbance rejection capability.

关键词： Organic Rankine Cycle Waste heat recovery constrained generalized predictive control Fast recursive algorithm

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The High Efficiency Cooperative control of Power and Temperature of a Stand-Alone Solid Oxide Fuel Cell System with an Air Bypass Valve

The High Efficiency Cooperative Control of Power and Tempera...

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Chinese Automation Congress (CAC)

作者： Jiang, Jianhua Li, Xi Li, Jian Huazhong Univ Sci & Technol Sch Automat Wuhan Hubei Peoples R China Huazhong Univ Sci & Technol Sch Mat Sci & Engn Wuhan Hubei Peoples R China

ISBN: (纸本)9781467371896

In this paper, a temperature feed-forward and power feedback control strategy based on open-loop optimal operation path and constrained generalized predictive control algorithm is proposed to address the competitive relations among power tracking, temperature constraints and high system efficiency of an independent solid oxide fuel cell (SOFC) system. Firstly, optimal operation points (OOPs) for different output powers are obtained by forcing temperature constraints and optimizing system efficiency based on a distributed SOFC system dynamic model. Then the thermo-electrical coupling characteristics of SOFC system are studied through static and dynamic analysis. As the temperature variation in the stack is slow, we can apply the thermal management relevant variables of OOPs to system immediately when the power changed, such as U, AR and BP, to suppress the potential system temperature fluctuation during power switching process. Due to the output power is directly determined by fuel flow rate, a constrained generalized predictive control algorithm based on online T-S fuzzy model (TS-CGPC) is utilized to regulate fuel flow rate to achieve fast load following with the consideration of input constraint. The simulation results indicate that the controller can drive the system achieves excellent load tracking capability while keeping system constraints safe with high system efficiency of 42%similar to 53%, implying that the independent SOFC system can possess excellent performances by design an appropriate controller and this work set a solid foundation for the high efficiency and long operation life of SOFC.

关键词： solid oxide fuel cell thermo-electrical coupling system cooperative control system efficiency constrained generalized predictive control

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Order-reduced constrained GPC algorithm with wavelet-based feature extraction

Order-reduced constrained GPC algorithm with wavelet-based f...

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IFAC Workshop on New Technologies for Automation of Metallurgical Industry

作者： Yu, SM Wang, HQ Zhang, BY Zhejiang Univ Technol Coll Informat Engn Hangzhou 310014 Peoples R China

ISBN: (纸本)008044170X

Model predictive control(MPC) has a promising prospect in metallurgical process control. In this work, the main features of a high-order process are represented by a low frequency component of a response curve of the process based on wavelet decomposition.. and then the model order of the process is reduced by approaching the low frequency component with a low-order model. Subsequently, the high-order process is controlled by employing the order-reduced model and a constrained generalized predictive control(GPC) algorithm with simple feedback correction. Lastly, the feasibility and effectiveness are confirmed by a simulation example. Copyright (C) 2003 IFAC.

关键词： high-order process wavelet feature extraction order reduction constrained generalized predictive control

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Order-Reduced constrained GPC Algorithm with Wavelet-Based Feature Extraction *

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IFAC Proceedings Volumes 2003年第24期36卷 275-279页

作者： Shiming Yu Haiqini Wang Baoyuan Zhang College of Information Engineering Zhejiang University of Technology Hangzhou 310014. China Institute of Industrial Process Control Zhejiang University Hangzhou 310027 China Technical Center Gansu Television Station Lanzhou 730000 China

Model predictive control(MPC) has a promising prospect in metallurgical process control. In this work, the main features of a high-order process are represented by a low frequency component of a response curve of the process based on wavelet decomposition, and then the model order of the process is reduced by approaching the low frequency component with a low-order model. Subsequently, the high-order process is controlled by employing the order-reduced model and a constrained generalized predictive control(GPC) algorithm with simple feedback correction. Lastly, the feasibility and effectiveness are confirmed by a simulation example.

关键词： high-order process wavelet feature extraction order reduction constrained generalized predictive control

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constrained generalized predictive control of unstable nonlinear processes

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CHEMICAL ENGINEERING RESEARCH & DESIGN 1997年第A3期75卷 371-376页

作者： Venkateswarlu, C Gangiah, K INDIAN INST CHEM TECHNOL PROC DYNAM & CONTROL GRPHYDERABAD 500007ANDHRA PRADESHINDIA

A constrained generalized predictive linear control strategy is extended to constrained control of open-loop unstable nonlinear processes. In this strategy, process nonlinearities are accounted through adaptation of model parameters while taking care of input and output constraints acting on the open-loop unstable nonlinear process. The usefulness of this control strategy is evaluated by applying it to a chemical reactor and a biochemical reactor. The results show that this strategy is effective for control of open-loop unstable plants.

关键词： generalized predictive control constrained generalized predictive control model predictive control open-loop unstable systems nonlinear processes

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