ANFIS based Direct Torque Control of PMSM Motor for Speed and Torque Regulation

Nowadays, the Permanent Magnet Synchronous Motors (PMSM) are gaining popularity among electric motors due to their high efficiency, high-speed operation, ruggedness, and small size. PMSM motors comprise a trapezoidal electromotive force which is also called synchronous motors. Direct Torque Control (DTC) has been extensively applied in speed regulation systems due to its better dynamic behavior. The controller manages the amplitude of torque and stator flux directly using the direct axis current. To manage the motor speed, the torque error, flux error, and projected location of flux linkage are employed to adjust the inverter switching sequence via Space Vector Pulse Width Modulation (SVPWM). One of the most common problems encountered in a PMSM motor is Torque ripple, which is recreated by power electronic commutation and a better controller reduces the ripples to increase the drive's performance. Conventional controllers such as PI, PID and SVPWM-DTC were compared with the proposed Adaptive Neuro-Fuzzy Inference System (ANFIS) in terms of performance measures such as speed and torque ripple. In this work, the Two-Gaussian membership function of the ANFIS controller is used in conjunction with a PMSM motor to reduce torque ripple up to 0.53 Nm and maintain the speed with a distortion error of 2.33 %

Vibration Torque Measurement and Mechanism Analysis of Rotary Stepping Motor

Vibration torque are existence obviously during operation of stepping motor, it is a periodic structure vibration problem. In this paper, the actual vibration torque testing of stepper motor is executed through a self-made vibration torque sensor, the experimental results show that the stepping motor vibration torque of single three shot operation is more bigger than the six shot, and obvious reply oscillation existence in two operations; sharp vibration torque is generated on low frequency lost step oscillation; Last, the generation of these experimental phenomena are analyzed, it can provide a certain reference for controller or control algorithm designation of stepper motor

ANFIS-based prediction of power generation for combined cycle power plant

This paper presents the application of an adaptive neuro-fuzzy inference system (ANFIS) to predict the generated electrical power in a combined cycle power plant. The ANFIS architecture is implemented in MATLAB through a code that utilizes a hybrid algorithm that combines gradient descent and the least square estimator to train the network. The Model is verified by applying it to approximate a nonlinear equation with three variables, the time series Mackey-Glass equation and the ANFIS toolbox in MATLAB. Once its validity is confirmed, ANFIS is implemented to forecast the generated electrical power by the power plant. The ANFIS has three inputs: temperature, pressure, and relative humidity. Each input is fuzzified by three Gaussian membership functions. The first-order Sugeno type defuzzification approach is utilized to evaluate a crisp output. Proposed ANFIS is cable of successfully predicting power generation with extremely high accuracy and being much faster than Toolbox, which makes it a promising tool for energy generation applications

Fuzzy control system review

Overall intelligent control system which runs on fuzzy, genetic and neural algorithm is a promising engine for large –scale development of control systems . Its development relies on creating environments where anthropomorphic tasks can be performed autonomously or proactively with a human operator. Certainly, the ability to control processes with a degree of autonomy is depended on the quality of an intelligent control system envisioned. In this paper, a summary of published techniques for intelligent fuzzy control system is presented to enable a design engineer choose architecture for his particular purpose. Published concepts are grouped according to their functionality. Their respective performances are compared. The various fuzzy techniques are analyzed in terms of their complexity, efficiency, flexibility, start-up behavior and utilization of the controller with reference to an optimum control system condition

Mathematical modeling of stepping motor and vibration torque mechanism research on its different operations

Vibration torque are existence obviously during operation of stepping motor, it is a periodic structure vibration problem. In this paper, the motion model of motor is deduced and is compared with the motion mathematic model of pendulum; then actual vibration torque testing of stepper motor is executed through a self made vibration torque sensor, including single-step operation, low frequency continuous operation, low frequency lost step oscillation and continuous operation, the experimental results show that the stepping motor vibration torque of single three shot operation is more bigger than the six shot, and obvious reply oscillation existence in two operations; sharp vibration torque is generated on low frequency lost step oscillation; the vibration torque of single step operation is greater than the continuous operation, and vibration torque is decreasing with the frequency increasing; last, the generation of these experimental phenomena are analyzed, and the relationship between the stepper motor vibration torque peak value and frequency of the normal continuous operation are found, it can provide a certain reference for controller or control algorithm designation of stepper motor

Low Speed Longitudinal Control Algorithms for Automated Vehicles in Simulation and Real Platforms

Advanced Driver Assistance Systems (ADAS) acting over throttle and brake are already available in level 2 automated vehicles. In order to increase the level of automation new systems need to be tested in an extensive set of complex scenarios, ensuring safety under all circumstances. Validation of these systems using real vehicles presents important drawbacks: the time needed to drive millions of kilometers, the risk associated with some situations, and the high cost involved. Simulation platforms emerge as a feasible solution.Therefore, robust and reliable virtual environments to test automated driving maneuvers and control techniques are needed. In that sense, this paper presents a use case where three longitudinal low speed control techniques are designed, tuned, and validated using an in-house simulation framework and later applied in a real vehicle. Control algorithms include a classical PID, an adaptive network fuzzy inference system (ANFIS), and a Model Predictive Control (MPC). The simulated dynamics are calculated using a multibody vehicle model. In addition, longitudinal actuators of a Renault Twizy are characterized through empirical tests. A comparative analysis of results between simulated and real platform shows the effectiveness of the proposed framework for designing and validating longitudinal controllers for real automated vehicles.Te authors would like to acknowledge the ESCEL Project ENABLE-S3 (with Grant no. 692455-2) for the support in the development of this work

Designing driving and control circuits of four-phase variable reluctance stepper motor using fuzzy logic control

Precise positioning and repeatability of movement for stepper motors require designing a robust control system. To achieve that, an analytical model of a four-phase variable reluctance stepper motor is presented. A proposed open-loop driving circuit is designed to control the motion of a variable reluctance stepper motor. The driving circuit has an ability to drive the motor into two-step angles, i.e. a full step (15◦) and a half step (7.5◦). The direction of movement can be either into clockwise or counterclockwise direction. The operation of the variable reluctance stepper motor in an open-loop control circuit has demonstrated disadvantages of an oscillation and a relatively high settling time. Therefore, a closed-loop control circuit has been introduced using fuzzy logic control to overcome the oscillation problem and to obtain on a precise positioning within a reasonable settling time. The fuzzy logic control is used to improve and enhance the behaviour of the step position response based on oscillatory response and hence to reduce the overshoot significantly. The comparisons between the open- and closed-loop circuits are presented to demonstrate the disparity between both control circuits. The simulation results of the open-loop and the closed-loop circuits show that the time responses have been improved using different loads conditions. The simulation experiments are conducted and investigated using MATLAB–SIMULINK software package

Autonomous Locomotion Mode Transition Simulation of a Track-legged Quadruped Robot Step Negotiation

Multi-modal locomotion (e.g. terrestrial, aerial, and aquatic) is gaining increasing interest in robotics research as it improves the robots environmental adaptability, locomotion versatility, and operational flexibility. Within the terrestrial multiple locomotion robots, the advantage of hybrid robots stems from their multiple (two or more) locomotion modes, among which robots can select from depending on the encountering terrain conditions. However, there are many challenges in improving the autonomy of the locomotion mode transition between their multiple locomotion modes. This work proposed a method to realize an autonomous locomotion mode transition of a track-legged quadruped robot steps negotiation. The autonomy of the decision-making process was realized by the proposed criterion to comparing energy performances of the rolling and walking locomotion modes. Two climbing gaits were proposed to achieve smooth steps negotiation behaviours for energy evaluation purposes. Simulations showed autonomous locomotion mode transitions were realized for negotiations of steps with different height. The proposed method is generic enough to be utilized to other hybrid robots after some pre-studies of their locomotion energy performances