Fuzzy Logic Speed Controller Research Articles

African vulture optimizer algorithm for fuzzy logic speed controller of fuel cell electric vehicle

African vulture optimizer algorithm for fuzzy logic speed controller of fuel cell electric vehicle

Cuckoo Optimization Algorithm Based Fuzzy Logic Speed Controller for BLDC Motor

Brushless direct current (BLDC) motors are widely used in dynamic applications because of advantages such as high efficiency, wide speed range and low maintenance requirements. The classical Proportional-Integral (PI) control method is generally used for speed control of BLDC motor drivers. Although this method is easy to apply, the determined controller coefficients are generally constant and hence insufficient in dynamic changes. For this reason, methods that respond faster to dynamic changes, such as fuzzy-PI, have been proposed in the literature. Although the rule-based fuzzy controller increases its response ability to dynamic changes, determined rule-based coefficients affects the system performance completely. Therefore, the determination of the rule base values of the fuzzy controller is critical. In this paper, meta-heuristic Cuckoo Optimization Algorithm (COA) is proposed to determine the rule base values of the fuzzy controller for BLDC motor. Additionally, the rule-based table values of the fuzzy controller used for BLDC motor is determined using other meta-heuristic algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Imperialist Competitive Algorithm (ICA), Invasive Weed Optimization (IWO) and the results are compared. Finally, experimental studies for Pittman44 series BLDC motor are also carried out and the results are obtained.

Speed control of electrical submersible pumps using fuzzy logic control

<p>Electrical submersible pumps (ESPs) are multistage centrifugal pumps driven by specially designed three-phase induction motors. They are used in many applications such as nuclear and petroleum industries. In the presented paper, we study the speed control of an ESP pump using a rule-based fuzzy logic controller (FLC). As a case study, an oil well is considered to analyze the effects of changing the speed of an ESP pump on both the ESP pump and motor parameters. The proposed speed control model of ESP pumps provides the ability to optimize wells production and power consumption, as well as soft starting of ESP motors. This is done by using a variable speed drive (VSD), which changes the frequency of the voltage supplied to the ESP motor. The utilized VSD model consists of a two-level voltage source inverter (VSI), space vector pulse width modulator (SVPWM) and a rule-based fuzzy logic speed controller. Also, in this study a dynamic hydraulic model of an oil well is implemented. In this study, a mathematical model of the ESP motor and ESP pump is developed. The obtained simulation results show that the combination of the FLC speed Controller and SVPWM provides a faster and more effective method of controlling the speed of electrical submersible pumps than the conventional PID speed controllers. The MATLAB/ SIMULINK software is used to achieve simulative validation of the complete system.</p>

Experimental Investigations into the Behavior of Scaling Factors in a Fuzzy Logic Speed Control Induction Motor with Model Reference Adaptive Control

This paper presents a self-tuning fuzzy logic speed controller (FLSC) with model reference adaptive control (MRAC) for an induction motor (IM) drive system. The MRAC is examined by output scaling the factor tuner for optimum motor speed performance. A detailed investigation is carried out on the scaling factor control of the input change error and main FLSC output increment. This proposed method utilizes seven simplified rules of the 5 × 5 matrix membership functions to minimize the computational burden and memory space limitations. All simulation work is conducted using Simulink and Fuzzy Tools in the MATLAB software and the experimental testing with the aid of a digital signal controller board, dSPACE DS1103. Based on the results, the output scaling factor makes a more significant impact on the performance effect compared to the input error scaling factor. The input change error and output SF also exhibit similar behavior, indicating that a large range of UoD tuners works well in terms of capability load rejection while a small range of UoD tuners performs well in terms of rise time. The analysis includes no-load and load tests to ascertain the overshoot percentage, rise time, and settling time for transient and steady-state conditions.

FPGA based co-design of a speed fuzzy logic controller applied to an autonomous car

This paper invests in FPGA technology to control the speed of an autonomous car using fuzzy logic. For that purpose, we propose a co-design based on a novel fuzzy controller IP. It was developed using the hardware language VHDL and driven by the Zynq processor through an SDK software design written in C. The proposed IP acts according to the ambient temperature and the presence or absence of an obstacle and its distance from the car. The partitioning of the co-design tasks divides them into hardware and software parts. The simulation results of the fuzzy IP and those of the complete co-design implementation on a Xilinx Zynq board showed the effectiveness of the proposed controller to meet the target constraints and generate suitable PWM signals. The proposed hardware architecture based on 6-LUT blocks uses 11 times fewer logic resources than other previous similar designs. Also, it can be easily updated when new constraints on the system are to be considered, which makes it suitable for many related applications. Fuzzy computing was accelerated thanks to the use of digital signal processing blocks that ensure parallel processing. Indeed, a complete execution cycle takes only 7 us.

Fuzzy Logic Speed Control and Adaptation Mechanism-Based Twelve Sectors DTC to Improve the Performance of a Sensorless Induction Motor Drive

Fuzzy Logic Speed Control and Adaptation Mechanism-Based Twelve Sectors DTC to Improve the Performance of a Sensorless Induction Motor Drive

Fuzzy logic based dynamic performance enhancement of five phase induction motor under arbitrary open phase fault for electric vehicle

Abstract The multiphase induction motor can be a highly preferable choice for the EV application, where the reliability and safety of passengers are one of the major concerns. The main objective of this article is to design high performance fault tolerant control of five phase induction motor (FPIM) drive to enhance the dynamic performance under healthy, faulty and fault tolerant modes of operation under arbitrary open phase fault condition. First, a simple method of modeling open phase fault in any phase of the FPIM drive is proposed. The most frequently occurring open phase faults due to the power electronics switch failure in the inverters are considered for the analysis. A generalized method of modeling arbitrary open phase fault in FPIM drive using back EMF calculations in faulty phase is suggested. The developed method utilizes the same transformation matrix for any open phase fault such that the minimum modification in control strategy is required under fault condition. Thereafter, the control technique is detailed. The rotor field oriented control (RFOC) of FPIM with fuzzy logic speed controller is developed to generate optimal torque reference. The design of FLC is detailed with fine-tuned scaling factor, rule base and membership function to obtain robust performance of the drive under healthy and fault tolerant modes of operation. The complete RFOC scheme for 2 HP FPIM drive is built in MATLAB/SIMULINK incorporating fuzzy logic based controller to verify its performance. The comparison of transient and steady state response and robustness (to the load disturbance as well as fault) obtained using developed fuzzy logic based controller with those using conventional PI controller is presented to prove the efficiency of the suggested controller under various speed torque profiles. The effectiveness of the proposed fuzzy based fault tolerant controller for FPIM drive is validated using OP4510 controller based real time HIL simulator.

Performance Estimation of Adaptive Fuzzy Logic Speed Controller for Reduced Switch BLDC Motor Drive

This article deals with the implementation of an adaptive fuzzy logic based reduced switch brushless DC motor drive. In topological view, the cost of the system chiefly depends upon the power semiconductor switches. Hence switch reduction concept is adapted in this paper. The operating principle, switching sequence formulation of reduced switch topology is presented. An intelligent system for reduced switch BLDC drive is designed and tested for different load conditions. Simulation results as well as comparative performance with conventional controllers are presented and discussed. The parameters such as rise time and steady state error are observed. The effectiveness and robustness of the reduced switch BLDC drive for variable speed applications is demonstrated. The rise time and steady state error of the proposed system is improved about an average of nearly 60% and 30% respectively compared to other controllers.

Investigation of the Computational Burden Effects of Self-Tuning Fuzzy Logic Speed Controller of Induction Motor Drives With Different Rules Sizes

Investigation of the Computational Burden Effects of Self-Tuning Fuzzy Logic Speed Controller of Induction Motor Drives With Different Rules Sizes

Comparison of DFOC of Seven-Phase Induction Motor with PI and Fuzzy-Logic speed Controller under speed sensor fault

Comparison of DFOC of Seven-Phase Induction Motor with PI and Fuzzy-Logic speed Controller under speed sensor fault

An improved simplified rules Fuzzy Logic Speed Controller method applied for induction motor drive

Fuzzy Logic Speed Controller (FLSC) has been widely used for motor drive due to its robustness and its non-reliance to real plant parameters. However, it is computationally expensive to be implemented in real-time and prone to the fuzzy rules’ selection error which results in the failure of the drive’s system. This paper proposes an improved simplified rules method for Fuzzy Logic Speed Controller (FLSC) based on the significant crisp output calculations to address these issues. A systematic procedure for the fuzzy rules reduction process is first described. Then, a comprehensive evaluation of the activated crisp output data is presented to determine the fuzzy dominant rules. Based on the proposed method, the number of rules was significantly reduced by 72%. The simplified FLSC rule is tested on the Induction Motor (IM) drives system in which the real-time implementation was carried out in the dSPACE DS1103 controller environment. The simulation and experimental results based on the proposed FLSC have proved the workability of the simplified rules without degrading the motor performance.

Simple Implementation of a Fuzzy Logic Speed Controller for a PMDC Motor with a Low Cost Arduino Mega

Control of the permanent magnetic direct current PMDC motor is a common practice, hence the importance of the implementation of the PMDC motor speed controller. The results of a fuzzy logic speed controller for the PMDC motor rely on an appropriate base. As the dimension of the rules increases, its difficulty rises which affects computation time and memory requirements. Fuzzy Logic Controller (FLC) can be carried out by a low-cost Arduino Mega which has a small flash memory and a maximum clock speed of 16MHz. It is realized by three membership functions and each was divided into three memberships. The results of the FLC are satisfactory, revealing superior transient and steady-state performance. In addition, the controller is robust to speed mode variations.

Fuzzy Logic Speed Control of Permanent Magnet Synchronous Machine and Feedback Voltage Ripple Reduction in Flux-Weakening Operation Region

Voltage feedback flux-weakening control has the advantages of simplicity and robustness against parameter variation. However, due to less voltage control margin in the flux-weakening region, the increased feedback voltage ripple could deteriorate the system performance in the flux-weakening region and may even cause oscillation. In this article, based on a nonsalient permanent magnet synchronous machine, the steady-state feedback voltage ripple in the flux-weakening region are analyzed first. It shows that the feedback voltage ripple caused by the current command ripple could dominate in some flux-weakening regions. Consequently, the speed bandwidth based on the conventional speed proportional-integral (PI) controller in the flux-weakening region can be hardly increased, which leads to poor dynamic performance. In order to obtain both fast speed dynamics and less steady-state ripple, especially in the flux-weakening region, an adaptive fuzzy logic (FLC) speed controller is designed and compared with the conventional speed PI controller. With the adaptive FLC, the dc-link voltage utilization can be increased and better flux-weakening capability can be obtained. Finally, the improved performances are verified by the experimental results.

Review and Investigation of Simplified Rules Fuzzy Logic Speed Controller of High Performance Induction Motor Drives

The use of Fuzzy Logic Controller (FLC) as a speed controller for Induction Motor (IM) drives is garnering strong researchers’ interest since it has proven to achieve superior performance compared to conventional controllers. The aim of this study is to review and investigate the design, operations, and effects of rules reduction for FLC in IM drives. Based on the literature, the most commonly used technique to design FLC Membership Functions (MFs) rule-base and control model is based on engineering skills and experienced behavioral aspects of the controlled system. Simplified fuzzy rules approaches have been introduced to reduce the number of fuzzy rules in order to realize hardware implementation. This study discusses different simplified rules methods applied to IM drives. Most of the proposed methods shared a common drawback in that they lacked systematic procedures for designing FLC rule base. Therefore, this research proposed a methodological approach to designing and simplifying the FLC rule-base for IM drives based on dynamic step response and phase plane trajectory of the second order representation of IM drives systems. The proposed method presents guidance for designing FLC rule-base based on the general dynamic step response of the controlled system. Following the proposed method procedures, a (9, 25, 49) rules size has been designed and simplified to a (5, 7, 9) rules size. The effectiveness and accuracy of the designed rules as well as the simplified rules were verified by conducting simulation analysis of IM drives using MATLAB/Simulink environment. Step speed command performance comparisons were achieved with both standard designed and simplified rules at various speed demands. The simulation results showed that the simplified rules maintain the drive performance and produced similar behavior as the standard designed rules.

Implementation of DSP-based optimal fuzzy logic speed controller for IM drive using quantum lightning search algorithm

This paper presents quantum-inspired lightning search algorithm (QLSA) based fuzzy speed controller (QLSAF) to tune and minimize the mean absolute error (MAE) to improve the performance of the induction motor (IM) drive under different speed and load conditions. A QLSAF is designed both in simulation and prototype implementation utilizing Texas Instruments TMS320F28335 DSP. The simulation model of the proposed QLSAF technique is compared with the different fuzzy optimized techniques to validate the superiority of the developed controller. The robustness of the QLSAF-based inverter controller is found to be superior in all tested cases than the robustness of other controllers in terms of transient response, damping capability, and reduction of the MAE, root mean square error and standard deviation. Several experimental results show that the speed responses and stator currents are consistent with the simulation results, which verify and validate the performance of the proposed QLSAF-based speed controller.

Adaptive MF tuned fuzzy logic speed controller for BLDC motor drive using ANN and PSO technique

This work focuses on adaptive controller design using fuzzy Logic (FL) controller to get better dynamic performance under non-linearities and parameter uncertainties. In the proposed controller, the membership function (MF) parameters are tuned in line with the parameter variations of the motor. The steady state, regulatory and servo response of the proposed controller are analysed to highlight the merits of the controller. The simulation results indicate that the proposed controller possesses good tracking capability and faster response time in comparison with conventional schemes.

Comparative Analysis of Induction Motor and Interior Permanent Magnet Synchronous Motor in Electric Vehicles with Fuzzy Logic Speed Control

Selection of electric motors and designing of efficient motor drives are important issues in the manufacturing of electric vehicle’s traction system, especially with the highly competitive electric vehicles’ market. Many electric motors can be used to drive electric vehicles, but the induction motor (IM) and the interior permanent magnet synchronous motor (IPMSM) are the dominant ones. This paper introduces a dynamic comparative analysis of the IM and the IPMSM in electric vehicles applications. To conduct this analysis, two identical IM and IPMSM have been selected and two motor drives have been built using field oriented control (FOC) techniques in Simulink software. The motors were used to drive identical vehicle body models with a fuzzy logic controller used to control the vehicle’s speed. Both motors were compared mainly in terms of the speed and the torque responses with and without vehicle body load. The results showed a convergent performance between both systems; however, the IM-driven vehicle model has a little faster response compared to the IPMSM-driven one, whereas the latter has a higher torque ripple compared to the IM drive.

A comparative study of universal fuzzy logic and PI speed controllers for four switch BLDC motor drive

This paper presents a comparison of PI controller and fuzzy controller for speed control of a low cost brushless DC (BLDC) motor drive used in variable speed drive applications. The cost reduction in BLDC drive system is achieved by the reduction of power semiconductor switches. A PI controller and universal fuzzy controller are designed for the speed control and tested by simulation for various conditions. The simulation is performed by using MATLAB Simulink toolbox and the results show the effective response of the fuzzy controller. The rise time and steady state error of fuzzy controller is improved on an average of about 26% and 55% respectively compared to the conventional PI controller.

A Novel Self-Tuning Fuzzy Logic Controller Based Induction Motor Drive System: An Experimental Approach

High-performance induction motor (IM) drives require fast dynamic responses, robust to parameter variations, withstand load disturbance, stable control systems, and support easy hardware/software implementation. Fuzzy logic control (FLC) for speed controllers is garnering attention from researchers, since it is proven to produce better results compared with the conventional PI speed controllers. However, fixed parameter FLC experiences performance degradation when the system operates away from the design point or is affected by parameter variations or load disturbances. The purpose of this paper is to design and implement a simple self-tuning fuzzy logic controller (ST-FLC) for IM drives application. The proposed self-tuning mechanism is able to adjust the output scaling factor of the main FLC speed controller by improving the accuracy of the crisp output. The IM drive employed an indirect field-oriented control (IFOC) method fed by a hysteresis current controller (HCC). The fixed parameter FLC for the main speed controller comprises nine rules that are tuned to achieve the best performance. Then, a simple self-tuning mechanism is applied to the main fuzzy logic speed controller. All simulation work was done using Simulink and fuzzy tools in the MATLAB software. The effectiveness of the proposed controller was investigated by conducting a comparative analysis between fixed parameter FLC and ST-FLC in forward and reverse speed operations, with and without load disturbances. Finally, the experimental testing was carried out to validate the simulation results with the aid of a digital signal controller board, dSPACE DS1104, with an induction motor drive system. Based on the results, the ST-FLC showed superior performance in transient and steady-state conditions in terms of various performance measures, such as overshoot, rise time, settling time, and recovery time.

Life Time Cycle in Power Electronics for Fuzzy Logic Speed Controller in Brushless Motors

Life Time Cycle in Power Electronics for Fuzzy Logic Speed Controller in Brushless Motors