Robust Adaptive Sliding Mode Control Design with Genetic Algorithm for Brushless DC Motor (original) (raw)
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COMPARISON OF SLIDING MODE AND PROPORTIONAL INTEGRAL CONTROL FOR BRUSHLESS DC MOTOR
This paper will compare properties of Sliding Mode Controlled (SMC) and classical Proportional Integral (PI) controlled brushless DC motor (BLDC) in applications. It is the simple strategy required to achieve good performance in speed or position control applications. This paper addresses controlling of speed of a BLDC motor which remains among the vital issues. A BLDC motor is generally controlled by Proportional plus Integral (PI) controller. PI controller is simple but sensitive to parameter variations and external disturbance. Due to this reasons, Sliding Mode Control (SMC) is proposed in this paper. This control technique works against parameters variations and external disturbances, and also its ability in controlling linear and nonlinear systems. Performance of these controllers has been verified through simulation using MATLAB/SIMULINK software. The simulation results showed that SMC was a superior controller than PI controller for speed control of a BLDC motor
Design of Sliding Mode Control Strategy for DC Motor
International Journal for Research in Applied Science and Engineering Technology, 2023
: This research paper presents a comparative study ofsliding mode control (SMC) strategies and proportional- integralderivative (PID) control for DC motor applications. The project involves the design and implementation of PID and SMC controllers, as well as the evaluation of their respective response characteristics. Furthermore, the SMCcontroller is designed using three different sliding surfaces to analyze their impact on the control system's performance. A model is developed and simulated usingMATLAB/SIMULINK. Overall, the simulation results show that sliding mode controller is superior than PID for speed control of dc motor.
Modelling and Analysis of BLDC Motor Using Sliding Mode Control and comparing it with PI Controller
International Journal of Scientific Research in Science, Engineering and Technology, 2020
The sliding mode control technique for brushless DC motor is used to improve its dynamic performance with high accuracy. The proposed novel sliding mode (SM) controller method is used drive at all speed levels. The SM controller is the most attractive and simple in modelling for its insensitivity to parameter variations and external disturbances. The validity of the proposed method is verified through simulation. The BLDC motor is inherently electronically controlled and requires rotor position information for proper commutation of current. An equation based model for closed loop operation of BLDC motor drive is simulated in MATLAB/Simulink. Simulation results show the proposed SM Controller has the advantage of fast response and less steady-state error when compared to that of the conventional PI controller. In this paper the responses of current, speed and torque using SM controller is compared with that of PI controller.
This paper presents a brief study of proportional integral sliding mode control (PISMC) techniques for controlling the rotor position of PMDC motor drive system. In particular, since SMC is robust in the presence of the matched uncertainties and external disturbances, the desired position is perfectly tracked. In addition, the advantages and disadvantages of both proportional-integral (PI) and sliding mode control (SMC) control methods are studied. Since the major drawback of SMC is a phenomenon, known as chattering, resulting from discontinuous controllers, the PISMC method presented reduced the chattering very well. The performance of this method, PISMC is compared with the responses of the system with PID and conventional SMC controllers, and the PISMC is found to be better with higher precision and better robustness to plant imprecision and external disturbances than PID controllers.
Switching Gain Adaptive Control Brushless DC Motor
Brushless DC (BLDC) is replacing DC motors in wide range of applications such as household appliances, automotive and aviation. These applications require a very robust, high power density and efficient motor for operation. BLDCs are commutated electronically unlike the DC motor. BLDCs are controlled using a microcontroller which powers a three phase power semiconductor bridge. This semiconductor bridge provides power to the stator windings based on the control algorithm. The motor is electronically commutated, and the control technique/ algorithm required for commutation can be achieved either by using a sensor or a sensor less approach. To achieve the desired level of performance the motor also can be controlled using a velocity feedback loop. Sensor less control techniques such as Direct Back Electromotive Force (Back-EMF), Indirect Back EMF Integration and Field Oriented Control (FOC) are studied and discussed. The speed vs. torque characteristics of several different sensor less control techniques of BLDCs were studied and compared to the speed vs torque curve of a separately excited DC motor.
FPGA-based adaptive dynamic sliding-mode neural control for a brushless DC motor
Asian Journal of Control, 2011
In the adaptive neural control design, since the number of hidden neurons is finite for real-time applications, the approximation errors introduced by the neural network cannot be inevitable. To ensure the stability of the adaptive neural control system, a switching compensator is designed to dispel the approximation error. However, it will lead to substantial chattering in the control effort. In this paper, an adaptive dynamic sliding-mode neural control (ADSNC) system composed of a neural controller and a fuzzy compensator is proposed to tackle this problem. The neural controller, using a radial basis function neural network, is the main controller and the fuzzy compensator is designed to eliminate the approximation error introduced by the neural controller. Moreover, a proportional-integral-type adaptation learning algorithm is developed based on the Lyapunov function; thus not only the system stability can be guaranteed but also the convergence of the tracking error and controller parameters can speed up. Finally, the proposed ADSNC system is implemented based on a field programmable gate array chip for low-cost and high-performance industrial applications and is applied to control a brushless DC (BLDC) motor to show its effectiveness. The experimental results demonstrate the proposed ADSNC scheme can achieve favorable control performance without encountering chattering phenomena.
CHATTER-LESS SLIDING MODE CONTROLLER FOR DC MOTOR
Abstract—DC motors are used in most industrial processes, robots, and CNC machines etc. The main parameters interested in control system are speed, accuracy, and steady-state error. A choice of Sliding Mode Controller (SMC) had been backed by its advantages as a high speed, more accuracy, and simple installation; however the drawback of using SMC is the high frequencies on the output called chattering phenomenon. This paper presents the design of a New Sliding Mode Controller based on state feedback controller (SMSFC), a new algorithm propose to reduce the chattering phenomenon by utilizing to reduce the gain value of SMC. Results have obtained it shows that the chattering is decreased up to 85% also the value of the gain controller is decreased (from 40% to 95%) especially in sliding phase, The results show a robust algorithm (more so than traditional ones) high accuracy and speedy response were achieved via external load and change in the system parameters.
Position sensorless and adaptive speed design for controlling brushless DC motor drives
2017 North American Power Symposium (NAPS), 2017
This paper proposes a method for direct torque control of Brushless DC (BLDC) motors. Evaluating the trapezium of back-EMF is needed, and is done via a sliding mode observer employing just one measurement of stator current. The effect of the proposed estimation algorithm is reducing the impact of switching noise and consequently eliminating the required filter. Furthermore, to overcome the uncertainties related to BLDC motors, Recursive Least Square (RLS) is regarded as a real-time estimator of inertia and viscous damping coefficients of the BLDC motor. By substituting the estimated load torque in mechanical dynamic equations, the rotor speed can be calculated. Also, to increase the robustness and decrease the rise time of the system, Modified Model Reference Adaptive System (MMRAS) is applied in order to design a new speed controller. Simulation results confirm the validity of this recommended method.
Intelligent fuzzy sliding mode controller based on FPGA for the speed control of a BLDC motor
International Journal of Power Electronics and Drive System (IJPEDS) , 2020
Brushless DC (BLDC) motors are one of the most widely used motors for various industrial applications due to their high efficiency, high torque to weight ratio and elimination of mechanical commutator. These motors operate in wide range of speeds and necessitate precise speed control techniques, for their nonlinear model, insenseitive to parameter variations and external disturbances, when used in various sensitive applications. Conventional PI and other existing controllers produce high overshoot and increased rise time and settling time. The performance of BLDC motor is enhanced using a Fuzzy Sliding Mode Controller (FSMC) whose gain is intelligently varied with the help of a Fuzzy Inference System (FIS). For this purpose, a suitable FSMC is designed, simulated and implemented using FPGA. The simulation results are validated using Hardware in the loop (HIL) simulation as well as actual hardware implementation. Great improvement in the transient performance is achieved when compared to chatter free SMC, Fuzzy PI and conventional PI controller.