In spite of improvement of the AC drive systems still the DC drives are widely used in industry. One of the problems associated with CONTROL of DC MOTOR which might cause unsuccessful attempts for designing a proper CONTROLler would be the time-varying nature of DC MOTORs parameters and variables which might be changed while working with the motion systems. In these conditions, the CONTROL systems will not response properly. One of the best suggested solutions to overcome this problem would be the use of sliding mode CONTROL (SMC). SMC is not sensitive to parameters changes and yet would have a fair response to the systems variations. However, SMC suffers from some deficiencies including inflexibility in CONTROLler parameters. A Better response can be achieved by SMC in compare with classical methods but it is not the most optimized response. The fair solution can be defined through faster fulfillment of target, less overshoot and more consistency of the system against the changes of the parameters. In this paper, a new fuzzy based method is presented to increase the SMC ability to reach a more convenient solution. Optimized response can be achieved in terms of shorter settling time, less overshoot, and more stability.

This paper describes a simple way to CONTROL the Brush Less DC MOTOR (BLDCM) for electrical applications. To CONTROL this machine it is generally required to measure the speed and position of rotor by using the sensor because the inverter phases, acting at any time, must be commutated depending on the rotor position. The position sensors make the MOTOR system more complicated and mechanically unreliable. A method for the estimation of the speed and rotor position of a BLDCM is presented in this work. Fuzzy based Back EMF observer is employed to estimate the speed by using measurements of the stator line voltage and line current. Most existing sensorless methods of the BLDC MOTOR have low performance at transients or low speed range and occasionally require an additional circuit. To overcome this problem, the estimation of a back-EMF is carried out by fuzzy logic techniques to improve the performance of the system. This method proposes back-EMF observer based on fuzzy function approximation and the system state equation of the BLDC MOTOR. The fuzzy logic technique is used to estimate the speed of the BLDC MOTOR under variable and fixed condition of the back-EMF. Finally, the speed is CONTROLled by using Proportional-Integral (PI) CONTROLler with the help of fuzzy based estimation of the speed and rotor position. Here, fuzzy based estimation of speed and rotor position which is also verified with the sensor, feeds input to the PI CONTROLler which does really well for good performance.

Due to nonlinear actuators or changing environmental conditions, the parameter of the process changes resulting in the failure of a conventional CONTROLler. To overcome the failure of the conventional CONTROLler and to achieve the desired output, an adaptive mechanism called Model Reference Adaptive CONTROLler (MRAC) can be designed. Since the conventional MRAC is aimed at the first-order system for two-variable parameter adjustment, it cannot be applied for most practical systems, including DC MOTOR. To overcome this a modified MRAC which is the combination of conventional MRAC and a PID CONTROLler is designed in this paper.

this paper presents finite CONTROL set-model predictive CONTROL (FCS-MPC) in the low and high speed range for the CONTROL of brushless DC (BLDC) MOTOR. In the proposed CONTROL method, by removing the mechanical sensor and using the sliding mode observer (SMO), the electromotive force (BACK-EMF) as well as the speed and position of the rotor are accurately estimated. Then through fcs-mpc to improve speed CONTROL performance and reduce chattering, by minimizes a cost function, predicts the future behavior of the  system variables. The method is simulated with MATLAB software and the output speed and back-emf obtained from the CONTROL model CONTROL method with a limited CONTROL set are compared with the slip model observer method. The simulation results show that the CONTROL method used improves the speed convergence accuracy and reduces the steady-state error and the steady-state fluctuations.

CONTROLling the speed and direction of DC MOTOR rotation is vital in various industrial and educational applications. However, many college students do not understand the characteristics and CONTROL of DC MOTORs. Therefore, this study aims to study the simulation of DC MOTORs using the L298 MOTOR driver and Arduino platform with the help of Proteus software. This study focuses on the simulation of CONTROLling the speed and direction of DC MOTORs using a potentiometer as a speed CONTROLler and a switch to change the direction of MOTOR rotation (clock and anti-clock). The ACS712 current sensor and voltage sensor are used to monitor the current, voltage, and power displayed on the LCD screen. By using Arduino as a microCONTROLler, this system allows precise CONTROL and real-time monitoring of the MOTOR's electrical parameters. The simulation results show that the designed system can CONTROL the speed and direction of DC MOTORs well and provide important information about the operational characteristics of the MOTOR. This study not only offers theoretical insights but also practical applications in the development of efficient and effective MOTOR CONTROL systems. Thus, this study is expected to be an essential reference for students, researchers, and practitioners in understanding and developing better MOTOR CONTROL systems.

Nowadays, due to significant increase in demands of electric MOTORs for residential, commercial and industrial applications, and for optimum consumption of electrical energy, the design and manufacturing of high efficiency MOTORs and related variable speed drives have been considered by many suppliers. Among several kinds of MOTORs, the brushless DC (BLDC) MOTOR is employed in many applications due to its high efficiency, high power and torque density, and ease in CONTROL, simple fabrication, high reliability, and lower maintenance. This MOTOR is similar to PMSM in construction, while is CONTROLled as easy as of DC MOTOR. This paper is devoted to help for development and employing BLDC MOTORs. It reviews the different aspects of BLDC MOTORs including performance, modeling, specifications, inverters, assessment of CONTROL methods for BLDC MOTOR and implementation of its drive. Advantages and disadvantages of different CONTROL methods, remarks on various position sensor less methods, the effectiveness of various minimization schemes for commutation torque ripple, and CONTROL of BLDC MOTOR in constant power region or flux-weakening are described in more details. Finally, some practical points are suggested for fabrication of a commercial BLDC MOTOR drive.

Due to the widespread use of dc MOTORs, their position or speed CONTROL becomes very important. The aim in this paper is providing a new method for intelligent position CONTROL of separately excited dc MOTOR using neural networks. For this purpose the NARMA-L2 neural network CONTROLler is used. In the position CONTROL using neural network, based position for neural network intended as input position (ideal), and after adapting of output position of MOTOR to base position, Armature voltage become zero and MOTOR stops working. In this way, neural network learns the used model of dc MOTORs to CONTROL the position, then the input optimized for matching of model output position to ideal position.Advantage of the proposed neural network method is, correction coefficients during the working engine and Replies robustness to changes inertia moment (J) and friction (B). Unlike the PID CONTROLlers that will lose their optimization Performance with changing one of the model parameters, such as J & B, and need to reset the parameters of the CONTROLler, the proposed method needs not to redesign, and these parameters repair automatically. Proposed method is simulated using information from a separately excited dc MOTOR in SIMULINK environment of MATLAB software.Results show that by using of proposed method, fluctuations in response and need times to reach the ideal situation decreases.

Various methods have been proposed to CONTROL the speed of induction MOTORs. Among these methods, the direct torque CONTROL (DTC) method contains the desired dynamic response. One of the main problems of DTC is the expensive hardware of this type of drivers, especially the current sensors cost. In practice, at least three current sensors are required, two of which are located on the output phases of the inverter and one sensor on the inverter’s DC link for protection purposes. The aim of this paper is to present a new and inexpensive method for direct torque CONTROL of induction MOTOR using only one DC link current sensor. In this method, the zero vector is removed and each of the real vectors 1 to 6 is replaced by two proposed virtual vectors. As a result, it is possible to estimate the phase currents of the MOTOR utilizing only one current sensor in the DC link for a wide range of speeds, even low speeds and close to zero speeds. Another advantage of the proposed method is its constant switching frequency. The proposed idea is simulated using Matlab/Simulink environment and the dynamic response of the system is improved. Also, the ripple reduction in the flux as well as the torque of MOTOR is obtained compared to the conventional DTC method.