Fuzzy Logic Speed Research Articles

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.

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.

Speed Control of Doubly Fed Induction Motor

In this work the performancecomparison study of the proportional integral and fuzzy logic speed controllers which used for the speed control of doubly fed induction machine is presented. For a long time, electromechanical systems used the squirrel-cage induction motors, as main actuators, however, doubly fed induction motors, present of estimable advantages at variable speed drive. From that, the performances of conventional speed controllers are sensitive to parameter variations of the motor. So, in this paper, the analyze of performances of speed fuzzy logic controller is presented. The simulation results showed that the fuzzy logic controller ensure the best dynamic performances in rotor resistance and load variations.

High Speed Min/Max Architecture Based on a Novel Comparator in 0.18-μm CMOS Process

This paper describes the design of a high speed min/max architecture based on a new current comparator. The main advantage of the proposed circuit which employs a novel preamplifier-latch comparator is the higher operating frequency feature in comparison with previous works. Because the comparator can work in voltage mode, the min/max structure can be redesigned either in voltage or current mode. The designed comparator is refreshed without any external clock. Therefore, it does not degrade the speed performance of proposed min/max structure. These features along with low power consumption qualify the proposed architecture to be widely used in high speed fuzzy logic controllers (FLCs). Post-layout simulation results confirm 3.4 GS/s comparison rate with 9-bit resolution for a 0.9 V peak-to-peak input signal range for the comparator and 800 MHz operating frequency for min/max circuit. The power consumption of whole structure is 912 μW from a 1.8 V power supply using TSMC 0.18-μm CMOS technology.

Improved brushless DC motor speed controller with digital signal processor

Brushless motors are used in many applications owing to their advantages. In most of the applications, conventional control methods with a hysteresis band (HB) controller are used. An improved speed and current control scheme for brushless DC motors with a trapezoidal shape back EMF is presented. Instead of the conventional HB and proportional-integral (PI) controllers, a fuzzy logic controller that is independent of motor equations and based on expert knowledge has been employed for current and also for speed regulation; thereby, the disadvantages of the HB are eliminated and the overall performance of the controller is enhanced. Experimental studies have been carried out with a TMS320F2812 digital signal processor. The presented control scheme has been validated through comparative experiments with the fuzzy logic speed and HB current controller. The results show that the proposed control scheme operates satisfactorily and provides a constant switching frequency.

Comparative Study of Conventional, Fuzzy Logic and Neural PID Speed Controllers with Torque Ripple Minimization for an Axial Magnetic Flux Switched Reluctance Motor

Three speed controllers for an axial magnetic flux switched reluctance motor with only one stator, are described and experimentally tested. As it is known, when current pulses are imposed in their windings, high ripple torque is obtained. In order to reduce this ripple, a control strategy with modified current shapes is proposed. A workbench consisting of a machine prototype and the control system based on a microcontroller was built. These controllers were: a conventional PID, a fuzzy logic PID and a neural PID type. From experimental results, the effective reduction of the torque ripple was confirmed and the performance of the controllers was compared.

Recurrent and Feedforward Neural Network Control of Permanent Magnet Synchronous Motor

In this paper, the fuzzy logic, neuro-fuzzy logic, and artificial neural network speed controllers in feedforward and recurrent architectures are designed and modeled to control the permanent magnet synchronous motor (PMSM) drive. The fundamentals of artificial intelligence-based control algorithms are illustrated. The detailed performance of the PMSM drive is studied by applying various mechanical disturbances such as starting performance, speed reversal, flux weakening, and load perturbations.

An improved efficiency of fuzzy logic control of PMBLDC for PV pumping system

This paper presents an analysis by which the dynamic performances of a permanent magnet brushless DC (PMBLDC) motor is controlled through a hysteresis current loop and an outer speed loop with different controllers. The dynamics of the photovoltaic pumping drive system with (PI) and a fuzzy logic (FL) speed controllers are presented. In order to optimize the overall system efficiency, a maximum power point tracker is also used. Simulation is carried out by formatting the mathematical model for photovoltaic source, MPPT, motor and pump load. The results for such complicated and nonlinear system, with FL speed controller show improvement in transient response of PMBLDC drive over conventional PI. The effectiveness of the FL controller is also demonstrated.

Optimization of Fuzzy-Logic Speed Controller for DC Drive System With Elastic Joints

This paper deals with the analysis of a DC drive system with elastic joints and different speed controllers. The control structure with one and two speed feedbacks was analyzed. The dynamics of the drive system with classical proportional-integral (PI) and fuzzy-logic (FL) speed controllers was compared. Parameters of the classical PI and FL speed controllers were optimized using the same control indexes. Controllers were parameterised using the hybrid genetic-gradient algorithm. The simulation results for different parameters and operation modes of the drive system were demonstrated and compared.

Fuzzy Logic Versus PI Speed Control in High-Performance AC Drives: A Comparison

A frequently discussed application of artificial intelligence inmotion control is the replacement of a standard Proportional Plus Integral (PI)speed controller with a fuzzy logic (FL) speed controller. A common conclusionthat emerges from such studies is that the FL control provides superior performance. However, such a conclusion usually is based on a limited simulation and/or experimental study. It appears that a thorough comparison of the drive behavior under PI and FL speed control, using simulations and an experimental rig, is still missing. This paper attempts to provide such an in-depthcomparison of the operation of a vector-controlled permanent magnet synchronous motor. Speed responses under PI and FL speed control are at first simulated and then measured on the experimental rig for a variety of operating conditions. Twodifferent machines are used in simulation and experimentation, enabling a better generalization of the results. The transients studied include response to a large step speed command from standstill with nominal inertia and an increased inertia, response to a small step speed reference change, response to a step load torque application, and a reversing transient. The transient behavior is examined for various initial speed settings, so that a thorough comparison is enabled. It is shown that superiority of the FL speed control is much less pronounced than it is often portrayed in literature on the basis of limited comparisons. Indeed, in a number of cases PI speed control provided a superior speed response. Predictions obtained by simulations and experimental results are found to be in reasonable agreement, considering all the differences between the simulation and experimental study.

A comparative analysis of fuzzy logic and PI speed control in high-performance AC drives using experimental approach

One of the frequently discussed applications of artificial intelligence in motion control is the replacement of a standard proportional plus integral (PI) speed controller with a fuzzy logic (FL) speed controller. Regardless of all the work, it appears that a thorough comparison of the drive behavior under PI and FL speed control is still missing. This paper attempts to fill in this gap, by providing an in-depth comparison of operation of a vector-controlled permanent-magnet synchronous motor, using at first an experimental rig. Speed responses, obtained under PI and FL speed control, are recorded and compared for a variety of operating conditions. The transients studied include response to a large step speed command from standstill with nominal inertia and an increased inertia, response to small step speed reference change, and response to step load torque application. The transient behavior is examined for various initial speed settings, so that a thorough comparison is enabled. Experimental results are further supplemented with a set of simulation results, obtained using a different permanent-magnet machine and a different FL controller. Better generalization of the results is enabled in this way. It is shown that superiority of the FL speed control is less pronounced than it is often portrayed in the literature on the basis of limited comparisons. Indeed, in a number of cases, PI speed control provides a superior speed response.

An Experimental Investigation of Fuzzy Logic Speed Control in Permanent Magnet Synchronous Motor Drives

One possible application of artificial intelligence in motion control is the use of a fuzzy logic (FL) speed controller. Regardless of all the work, it appears that a detailed investigation of the drive behaviour under FL speed control, using an experimental rig, is still missing. This paper provides an in-depth report on operation of a vector controlled permanent magnet synchronous motor subjected to FL speed control. The transients studied include speed response to large step speed command from standstill with nominal inertia and with an increased inertia, response to small step speed reference change with nominal inertia and with an increased inertia, and response to step load torque application. The transient behaviour is examined for various initial speed settings, so that an insight into the impact of the operating point on the controller behaviour is enabled. It is shown that the reference speed at which certain transient is initiated may strongly influence the speed response obtainable with constant parameter FL speed controller.

Roblin Linear Transport Robots Command Using Fuzzy Logic Controller

A speed fuzzy logic controller is proposed for transport robots with ac linear induction motors drives. To control the robot displacements the controller reference signal is changing continuously and robot speed output signal must track it The performance of the fuzzy logic controller is improved compared to that of the conventional PI-action controller in spite of the robot command saturation. To show that some simulation results are illustrated.