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optimized fuzzy controller for a power-torque distribution in a hybrid vehicle with a parallel configuration

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2014年第14期228卷 1654-1674页

作者： Derakhshan, Mohsen Shirazi, Kourosh Heidari Shahid Chamran Univ Ahvaz Dept Mech Engn Ahvaz Iran

In this study, an optimized fuzzy controller was designed for a power-torque distribution in a hybrid passenger vehicle using the bees algorithm. For this purpose, a dynamic model for a parallel hybrid vehicle, including an internal-combustion engine, an electric motor and battery, a torque converter, a continuously variable transmission, torque-speed coupling and wheels (forward dynamic), is built. To simulate the driver's skill and performance when facing different conditions, a fuzzy controller (which is called the first-layer controller) is used. On the one hand, decisions made by the first-layer controller are a function of the desired acceleration, the desired speed and the speed error and, on the other hand, they depend on the vehicle's performance mode. The vehicle's performance mode is determined with regard to the charged condition (the state of charge) of the batteries, the vehicle's required power and the driver commands by another fuzzy controller which is called the second-layer controller. The necessary commands for the subsystems such as the throttle angle, the controller command for the electric motor and the appropriate speed ratio in the continuously variable transmission are determined by another controller, called the third-layer controller. Both the first layer and the second layer are optimized using the bees algorithm. According to the results, the optimized controller indicates an appropriate performance based on the defined rules in different situations. It also improves the vehicle's performance parameter and decreases the fuel consumption and the pollutions produced by the engine.

关键词： optimized fuzzy controller torque distribution strategy hybrid electric vehicle parallel configuration bees algorithm

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Improvement in automatic generation control of two-area electric power systems via a new fuzzy aided optimal PIDN-FOI controller

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ISA TRANSACTIONS 2018年 80卷 475-490页

作者： Arya, Yogendra Maharaja Surajmal Inst Technol Dept Elect & Elect Engn New Delhi India

Automatic generation control (AGC) executes a vital role to supply quality power in an interconnected power system. To cultivate good quality of power supply via preserving area frequency and tie-line power oscillations following consumer's load demand disturbances, the controller designed for AGC of power system should display excellent disturbance rejection expertise. Hence, in this paper, a maiden attempt is made to propose a fuzzy aided integer order proportional integral derivative with filter-fractional order integral (FPIDN-FOI) controller for AGC of multi-area power systems. A more recent intelligent optimization technique termed as imperialist competitive algorithm (ICA) is fruitfully employed for concurrent tuning of various parameters of the proposed controller. It is observed from the simulation results that the proposed FPIDN-FOI controller outperforms the various existing control strategies and PID/PIDN/FPIDN controller designed in the study for five different power system models. Effect of variation in fractional order value of integral on the system performance is analyzed. A sensitivity analysis is conducted to test the robustness of the designed controller under variations in the system parameters, load demands and existence of the system nonlinearities. It is perceived that the proposed controller is robust and executes adequately under variations in system parameters, random load disturbance patterns and nonlinearities.

关键词： Electric power system optimized fuzzy controller Robust control Automatic generation control

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fuzzy control technique based on Genetic Algorithms optimizing and its application

Fuzzy control technique based on Genetic Algorithms optimizi...

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IEEE International Conference on Intelligent Processing Systems

作者： Yi, JK Yan, HP Sun, HT Hou, YB Beijing Polytech Univ Dept Automat Beijing 100022 Peoples R China

ISBN: (纸本)0780342534

Aimed at a kind of complex industrial production processes with nonlinear dynamic properties, the fuzzy-Neural Network controller based on Genetic Algorithms was designed in this paper. The coding optimization method for the parameters of the stimulating functions of the network's hidden nodes is the concatenated, multi-parameters, mapped, and fixed-point coding method. Based on this method, we can get the optimized fuzzy controller on-line. The step response curve of practical oven temperature control is given in this paper. The experimental results show that the fuzzy-Neural Network controller based on Genetic Algorithms optimizing is robust and effective and will find wide industrial application scope.

关键词： process control production control fuzzy control fuzzy set theory fuzzy neural nets neurocontrollers genetic algorithms temperature control fuzzy control technique genetic algorithms complex industrial production process nonlinear dynamic properties fuzzy Neural Network controller coding optimization method stimulating functions hidden nodes fixed point coding method optimized fuzzy controller step response curve oven temperature control industrial application

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Two-level optimization strategy for fuzzy control design

Two-level optimization strategy for fuzzy control design

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IEEE International Conference on Intelligent Processing Systems

作者： Sheng, WX Miao, DQ Dai, RW Chinese Acad Sci Inst Automat Beijing 100080 Peoples R China

ISBN: (纸本)0780342534

A two level optimization strategy is proposed fur fuzzy control design in this paper. The phase-plane of dynamic system is firstly divided into two-lever nonlinear regions according to response analysis, then a neuro-fuzzy hybrid network is built to optimize the region lever by lever, By the former, control process is decomposed properly, quick dynamic response and stable steady state with high accuracy are achieved coordinately, While through the later, unreasonable factors in the design of fuzz? control are decreased/eliminated and effect of fuzzy control is improved by learning. It offers a general, simple and efficient way for fuzzy control design. The optimized fuzzy controller is adopted in an electrohydraulic servo system, and satisfactory performance is obtained.

关键词： optimisation fuzzy control control system synthesis optimal control fuzzy neural nets neurocontrollers learning (artificial intelligence) hydraulic systems two-level optimization strategy fuzzy control design dynamic system two-level nonlinear regions response analysis neuro-fuzzy hybrid network dynamic response stable steady state learning optimized fuzzy controller electro-hydraulic servo system performance

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Multi-Converter UPQC Optimization for Power Quality Improvement Using Beetle Swarm-Based Butterfly Optimization Algorithm

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2023年第20期51卷 2487-2498页

作者： Sankar, Joyal Isac Subbaraman, Srinath Saveetha Engn Coll Dept EEE Chennai 602105 Tamil Nadu India Velammal Engn Coll Dept EEE Chennai Tamil Nadu India

The primary goal of this paper is to design a Multi-Converter Unified Power Quality Conditioner (MC-UPQC). The proposed method is solved based on the Synchronous Reference Frame (SRF) theory. The MC-UPQC involves two series Voltage Source Converters (VSCs) for power transfer between feeders to eliminate voltage sag, swell, interruption, and transient response in the system. The proposed model adopts control strategies based on an optimized fuzzy Logic controller (FLC) in SRF, utilizing a hybrid metaheuristic algorithm called Beetle Swarm-based Butterfly Optimization Algorithm (BS-BOA), which combines Beetle Swarm Optimization (BSO) and Butterfly Optimization Algorithm (BOA) for membership limit optimization and control rule generation. The major benefit of the optimized FLC-based MC-UPQC is its quick behavior in minimizing Total Harmonic Distortion (THD) in source and load side voltages and currents. Simulation and MATLAB environment are used for the entire system implementation. The comparative analysis of the proposed controller for MC-UPQC is performed against conventional controllers to validate its effectiveness. Quantitative data related to the main research outcomes, such as THD of source voltage and current, and dynamic behavior of the system, are included. The main benefit of the study is the significant reduction in THD and improved dynamic performance of the system.

关键词： multi-converter UPQC power quality improvement optimized fuzzy controller voltage source converter beetle swarm-based butterfly optimization algorithm

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