Model Of DC Motor Research Articles

OPTIMIZATION OF THE DC MOTOR MODEL COMPLEXITY LEVEL SELECTION FOR THE SYSTEM USING A NEURAL NETWORK

A mathematical and computer model of the torque control system of a DC motor with independent excitation was built using the NARMA 2 neurocontroller. NARMA - a nonlinear moving average autoregressive model is one of the basic structures of a discrete and nonlinear model. The task was to conduct a comparative analysis of the operation of the neurocontroller-based control system using plant model of varying complexity. For the experiment, three models of the object were built with different degrees of detail, and therefore the reliability of the object. The full model includes an independently excited DC motor model that takes into account all the main parameters of the DC machine, internal friction parameters, excitation circuits, etc. The simplified model is a linear approximation of the DC motor by a second-order system that takes into account both mechanical and electrical time constants. The simplest model is a linear approximation of a DC motor by a first-order aperiodic link that takes into account only the mechanical time constant. The neurocontroller was trained using the above object models and an experiment was conducted to process the reference torque signal by the system. For each of the three training cases, the neurocontroller was set to 1000 epochs, since further training performance improvement is unnecessary due to the huge loss of computation time. The NARMA-L2 neurocontroller, which is also called feedback linearization control, was used. This controller can be implemented using a pre-identified NARMA-L2 object model. Neural networks that are trained on simplified object models do not take into account most of the electrical processes in a DC motor, especially the excitation winding is not modeled at all. The obtained results were compared with the use of a neurocontroller as a torque regulator. Further research in this direction involves the study of the necessary computing power for the microprocessor implementation of the neurocontroller.

Design, modelling, and experimental validation of a self-rotating flapping wing rotorcraft with motor–spring resonance actuation system

Compared with traditional flapping motion, the flapping wing rotor (FWR) allows rotating freedom by installing the two wings asymmetrically, which introduces rotary motion characteristics and enables the FWR to have higher lift and aerodynamic efficiency at low Reynolds number. However, most of the proposed FWRs contain linkage mechanical transmission structures, the fixed degrees of freedom of which prohibit the wings from achieving variable flapping trajectories, limiting further optimization and controller design of FWRs. In order to fundamentally address the above challenges of FWRs, this paper presents a new type of FWR with two mechanically decoupled wings, which are directly driven by two independent motor–spring resonance actuation systems. The proposed FWR has 12.4 g of system weight and 165–205 mm wingspan. In addition, a theoretical electromechanical model based on the DC motor model and quasi-steady aerodynamic forces is established, and a series of experiments are conducted in order to determine the ideal working point of the proposed FWR. It is notable that both our theoretical model and experiments exhibit uneven rotation of the FWR during flight, i.e. rotation speed dropping in the downstroke and increasing in the upstroke, which further tests the proposed theoretical model and uncovers the relationship between flapping and passive rotation in the FWR. To further validate the performance of the design, free flight tests are conducted, and the proposed FWR demonstrates stable liftoff at the designed working point.

P19: Modeling the Effects of Heartbeat Synchronized Speed Modulation for a Pediatric LVAD

Study: Increasing the pulsatility of combined LVAD and heart output can be done by modulating the speed of the pump driver in synchrony with the heart rhythm. Increased pulsatility is closer to the physiological norm, lessens blood stagnation, and improves baroreceptor feedback for pressure regulation. This study is a first step to model the systemic response to pump speed modulation to develop the precise synchronization timing and controls for an optimized outcome and to analyze the results. Methods: A previously validated computational model of a mock circulatory loop is used as a platform to observe the hemodynamic effects of synchronized pump speed modulation on the heart. A model of a brushless DC motor used to drive the pediatric LVAD is established using the speed, torque, and inertia constants of the manufacturer specification sheet to represent the motor’s ability to change speed. The pressure and flow HQ curve of the LVAD impeller is used to calculate the pump output flow at different pressures and impeller speeds. The flow of the set speed LVAD is 3L/min, and the flow of the speed modulated LVAD varies between 1 L/min and 5 L/min at diastole and systole respectively. A PID controller is used to control the pump speed to reach the desired flow output. Results: The modulated LVAD flow results in larger changes in aortic pressure. The speed modulated LVAD had an aortic pressure difference of 20 mmHg between the minimum diastole and maximum systole values while the set speed LVAD had a difference of 7 mmHg. The set speed LVAD and the speed modulated LVAD had similar average aortic pressure values of 93mmHg and 91mmHg respectively. The changes in aortic pressure at systole and diastole resulting from the speed modulated flow show that synchronized motor speed modulation results in physiologic conditions closer to the norm.Figure 1. Overview of the Mock Circulatory Loop model and LVAD motor speed controller.Figure 2. Left Ventricular and Aortic Pressure with a set speed LVAD and a speed modulated LVAD.

Android App Controlled Automobile Screw Jack for Light and Heavy Transport

Abstract: This project is designed with Driver circuit with relay, BLUETOOTH APP (remote), Dc motor and jack model. Either the battery power or direct power supply is used to control the jack motor. The Bluetooth keypad is used to control the direction of the motor which is coupled with the spur gear. Relay is directly connected with the DC motor. When the start key is pressed the motor is operated in forward direction and the when the stop key is pressed the motor is stops automatically. The forward and reverse button in the remote is used to operate the motor is required directions. Bluetooth app Using To Control All Operation Using Wireless Communication.

Research on clutch position control based on backstepping method for small-sized tractors.

Tractors installed automated manual transmission can avoid discomfort for the drivers because of excessive limbs intervention as well as improve shift quality. Automatic clutch control is critical for the performance of the automated manual transmissions. For a good operation, precise and fast control of clutch position is mandatory. In order to meet these requirements, an enhanced strategy focused on the clutch is presented adopting a simple tracking control method based on the detailed models in this study. Clutch models including DC motor model and mechanical actuator model are established and transformed to a controllable model. On the basis of the control model, a clutch position tracking control scheme is proposed composed of motor control circuit and motor angle tracking controller designed according to the backstepping method. Simulations are carried out in comparation with the internal model control method, and the results demonstrate the effectiveness of the presented control scheme by superior rapidity and accuracy of the controller response for the clutch position tracking system.

Event-triggered extended dissipativity stabilization of semi-Markov switching systems

This paper is concerned with event-triggered extended dissipativity stabilization of uncertain semi-Markov switching systems with external disturbances. The purpose is to ensure the stochastic stability and extended dissipativity of the semi-Markov switching systems via using event-triggered control. A mode- and disturbance-dependent switched event-triggered mechanism is devised to determine the triggered moments, which can further reduce the number of triggered events compared to some existing switched event-triggered mechanisms. On the basis of the proposed mechanism, a time- and mode-dependent piecewise-defined Lyapunov functional is constructed to establish a criterion for the stochastic stability and extended dissipativity. Subsequently, a co-design scheme for the needed feedback-gain and event-triggered matrices is presented using some equivalent transformations of matrix inequalities. Lastly, a DC motor model and a robotic arm model are utilized to illustrate the validity of the designed controller.

Sliding mode control for discrete-time singular semi-Markovian jumping models

In this paper, the sliding mode control (SMC) is studied for discrete-time uncertain singular semi-Markovian jumping models. The aim is to construct an appropriate SMC strategy such that the stochastic admissibility conditions in the form of strict linear matrix inequalities are established for the corresponding closed-loop system under the framework of the semi-Markovian jumping process. Firstly, considering the particularity of singular systems, a common sliding surface with the singular matrix is designed, which can effectively reduce the influence of repetitive jumping among subsystems on the sliding surface and the numerical problem caused by the existence of the singular matrix. Then, in line with an improved reaching condition, the desired SMC mechanism is synthesized to drive the system state onto the pre-designed sliding surface. Finally, the DC motor model is taken as an example to demonstrate the effectiveness of the proposed SMC approach.

Modeling of a brushless dc motor driven electric vehicle and its pid-fuzzy control with dSPACE

In this study, a high power (75 kW) original driver and control algorithm has been developed for an electric passenger vehicle whose features can be used practically. It has been observed that some problems occur in the operation of the developed control algorithms in traction systems operating at high power. In this study, the solution methods of these problems are included. Firstly, the simulation model of an electrical vehicle was obtained by determining the basic parameters for a passenger electric vehicle. Then a brushless DC motor and drive system was determined for the electric vehicle and an original 75 kW DC-AC Converter (Inverter) in accordance with automotive standards has been designed and tested for the Brushless DC motor. Also, in the design and implementation phase, PID and Fuzzy control-based vehicle control software was developed in MATLAB/Simulink environment on the purpose of rapid prototyping and loaded on the DS1401 dSPACE based control system. It has been seen that through rapid prototyping, the appropriate controller development cycle time for the vehicle drastically reduced, which significantly has reduced the research and development costs. In the vehicle control algorithm, speed information is used as a reference input and brake information is used as feedback. The control signal generated by the controller is converted into PWM pulses for each phase and applied to the IGBT driver. These PWM pulses were used to switch the six IGBT power components used in the three-phase full-bridge DC-AC converter. Driving performance at the design stage has been studied for cases of starting, speed, reversal and load failure. Simulation and experimental results demonstrated the effectiveness of the driver and drive control system that were originally developed. When the system response was examined, it was revealed that the fuzzy logic control algorithm presented much better results than the PI and then the PID control algorithm. Simulation results and application results were consistent with each other and the system performance was successfully tested. Many protection circuits have been designed and configured in the system, with the control algorithms developed according to the problems arising in the operation of high-power systems, hardware add-ons for the operation of the high power (75kW) power-train. Safety and security infrastructures have been developed in both hardware and software for the appropriate certification in automotive standards.

Identification of the separately excited DC motor with extended instrumental variables

The problem of identifying the parameters of a DC motor is considered. The presence of measurement errors of currents and voltages leads to errors in both input and output signals. Existing methods for identifying the parameters of a DC motor do not take into account the presence of errors in both the output and input signals. A discrete model of a DC motor designed for use in digital systems is explored. One of the advantages of this model is the reduction of the problem of parameter estimation to two reduced dimension problems. Reducing the dimension of the problems being solved improves their conditionality and reduces sensitivity to measurement errors. A new method for identifying the parameters of DC motor models is proposed. Parameter estimates are found based on the extended method of instrumental variables. To find estimates, the use of extended equivalent systems of equations is proposed. Extended equivalent systems make it possible to reduce the condition numbers. The conducted numerical experiments showed the advantage of the proposed algorithm over the least squares. The results of the work can be applied in the development of predictive diagnostic systems. The use of the proposed method for identifying the parameters of a DC motor also makes it possible to reduce the requirements for measuring devices due to less sensitivity to measurement errors.

Guest Editorial: Learning, optimisation and control of cyber‐physical systems

Guest Editorial: Learning, optimisation and control of cyber‐physical systems

Switched electromechanical dynamics for transient phase control of brushed DC servomotor.

Robotic tasks often exceed the scope of steady-state or periodic behavior, which necessitates generally-applicable models of actuators intended to generate transient or aperiodic motion. However, existing electromechanical models of servomotors typically omit consideration of the switching power converter circuits required for directional, speed, or torque control. In this study, a multi-domain framework is established for switched electromechanical dynamics in servomotor systems for their analysis and control in general aperiodic tasks including transient phases. The switched electromechanical dynamics is derived from the individual models of the internal DC motor, gear train, and H-bridge circuit. The coupled models comprehensively integrate all possible distinct switching configurations of on-state, off-state, and dead time. A combination of cycle averaging with piecewise analytical solutions of the non-smooth dynamics is introduced to handle different temporal scales from high-frequency electrical to low-frequency mechanical variables. System parameters were estimated from experimental data using a dual-servomotor test platform. The model was validated for predictive accuracy against measured data in two distinct tasks-dynamic braking of a pendulum system and sinusoidal trajectory following. The model was also used to formulate the servomotor power consumption, which was implemented for optimal control demonstration and energy analysis. In particular, the servomotor power consumption model provided true optimality (minimization) when compared with the squared rotor torque and the positive rotor mechanical power that are commonly used as proxy models. While the focus of this work is on permanent-magnet, armature-controlled brushed DC servomotors, the approach is applicable to general electromechanical systems with switching-based control.

Robust Control Simulation and Implementation for DC Motor

The sliding mode controller has been suggested to achieve robust performance against parameter variations and load disturbances. It also offers a fast dynamic response, stable control system and easy hardware-software implementation. This paper focuses the application of this approach to the adjustment of a speed control DC motor, in Matlab Simulink simulation and Arduino hardware implementation, The main goal of this paper is to improve the performances of DC motor controlling by sliding mode. In first the modeling of DC motor is well explained in this paper, is important step for control of system, secondly the basic theory regarding sliding mode controller SMC using Lyapunovis function is presented. Finley the application of SMC using Matlab simulation and Arduino implementation for DC motor, the results show that SMC has a better performance compared to PI which is faster settling time and no overshoot and undershoot, could be used as an alternative controller for the DC Motor.

Improved passivity‐based control for Markovian jump singular systems with aperiodic sampling and actuator failures

AbstractThis aricle investigates the passivity‐based control problem for Markovian jump singular systems with aperiodic sampling and actuator failures. Firstly, in order to fully consider the system information, two novel mode‐dependent Lyapunov–Krasovskii functions (LKFs) are constructed, which are composed of one‐sided and two‐sided looped‐functionals respectively. Based on these two LKFs and an improved integral inequality, two stochastic admissibility and robust passivity criteria with lesser conservatism are given by using linear matrix inequalities (LMIs). Moreover, through these theorems, it is proved that the positive constraint of LKFs can be relaxed from all times to sampling times for Markovian jump singular systems with aperiodic sampling and actuator failures. Then, two aperiodic sampled‐data controller algorithms are proposed by LMIs to ensure the stability of the systems. Finally, A numerical example and a model of DC motor driving an inverted pendulum are provided to demonstrate the validity of the main results.

Simulation of Output Torque of Coal Mine Permanent Magnet DC Motor for Belt Conveyor

With the analysis of the global coal production trend in the past ten years and the requirements of coal mine belt conveyor for drive motor, we summarized the disadvantages of coal mine belt conveyor asynchronous motor such as high loss and low operating efficiency, designed the system structure and simulation calculation model of coal mine permanent magnet DC motor, simulated the output torque of coal mine permanent magnet DC motor for 50N load condition, and realized the output characteristics of coal mine permanent magnet DC motor Calculation.

Fuzzy SMC for Quantized Nonlinear Stochastic Switching Systems With Semi-Markovian Process and Application.

This article is concerned with the issue of quantized sliding-mode control (SMC) design methodology for nonlinear stochastic switching systems subject to semi-Markovian switching parameters, T-S fuzzy strategy, uncertainty, signal quantization, and nonlinearity. Compared with the previous literature, the quantized control input is first considered in studying T-S fuzzy stochastic switching systems with a semi-Markovian process. A mode-independent sliding surface is adopted to avoid the potential repetitive jumping effects. Then, by means of the Lyapunov function, stochastic stability criteria are proposed to be dependent of sojourn time for the corresponding sliding-mode dynamics. Furthermore, the fuzzy-model-based SMC law is proposed to ensure the finite-time reachability of the sliding-mode dynamics. Finally, an application example of a modified series dc motor model is provided to demonstrate the effectiveness of the theoretical findings.

Performance Degradation Model and Reliability Evaluation of Brush DC Motor for the Intelligent on–Off Valve

Performance Degradation Model and Reliability Evaluation of Brush DC Motor for the Intelligent on–Off Valve

Complete Electrical Equivalent Circuit Based Modeling and Analysis of Permanent Magnet Direct Current (DC) Motors

The modeling and analysis of permanent-magnet DC motor, whose attractiveness has increased with the availability of high-energy rare earth permanent magnet materials such as SmCo and NdFeB, is very important in recent years. The analysis of the established model is very important for researchers and engineers before siteworks. The most important features of the established model are that the equations are simple to obtain, the model can be set up using a simple platform, and ease of model analysis. Generally, for DC motor models, only the armature circuit model is given and only the equations of the mechanical system are given. In the armature circuit model, equations are obtained by switching to the s-domain, and analyzes are made on highly advanced platforms by using these equations. In this study, electrical equivalents of mechanical equations were obtained and both armature circuit and mechanical parameters of a DC motor were expressed as electrical circuit elements. Although the motor model includes mechanical parameters and variables, the whole model is expressed only with electrical elements and variables. Thus, a complete electrical equivalent circuit is proposed for the dynamic model of the permanent-magnet DC motor, in which both the armature and the mechanical part can be modeled as an electrical circuit. With the analyzes, the performance of the permanent magnet DC motor model was examined and it was seen that the system dynamics responses were compatible.

Finite-Time Stabilization of Markov Switching Singularly Perturbed Models

This brief is concerned with the issue of finite-time stabilization of discrete-time stochastic singularly perturbed models, in which the stochastic process is regulated by a Markov chain with partially unknown transition probabilities (TPs). The slow-state and fast-state variable are considered in the modeling, and the corresponding Markov switching model with a singularly perturbed parameter is obtained in a unified framework. Ill-conditioned problems caused by a small singular perturbation parameter are prevented by developing a finite-time stability criterion for the resultant system. Furthermore, feasible conditions are derived for the desired finite-time state feedback controller by using matrix inequalities that are independent of the singularly perturbed parameter. Finally, a gear-driven DC motor model is applied to illustrate the effectiveness of the described control strategy.

Dynamic event-based sliding mode security control for singular Semi-Markov jump LPV systems against deception attacks

In this paper, we preliminarily propose the dissipative sliding mode control (SMC) scheme for polyhedral singular semi-Markov jump linear parameter varying (SS-MJLPV) systems considering deception attacks between the sensor and controller. The main feature of this scheme is that a novel developed parameter dependent integral-type SMC law follows the changes of the system. Note that the mode of the sliding mode controller is not synchronized with the system mode, and the transition rates (TRs) of the system are assumed to be unknown. Moreover, we extend the previous work concerning the static event-triggered transmission protocol (ETP) to the dynamic one, in which the triggering threshold is dynamically updated via the internal-dynamic-variable. Finally, a DC-motor model is presented to illustrate the correctness of the developed results.

Simulation and Modelling of Electric Vehicle

Today, electric vehicles are increased among all over the world. Transportation vehicles are playing a major role in many applications. Mostly all type of vehicles using energy sources such as oil and gas. This is an ecological and urban means of transport and it's source of energy is battery. Electric vehicles began to play an more important role Since 2000’s. It is economic and simple means of transport and eco friendly. Over the past few years the electric vehicles have remained a frequent subject of the research community. In this article, we developed an EV setup using a DC motor. The model developed contains battery power, DC motor, H-Bridge controller, Wheel configuration (front and rear), PWM controller and vehicle body model developed on Simulink from Matlab. Through Simulink, the designed electric vehicle is simulated and various factors like State of Charge, Current and Voltage were calculated by providing driving cycle. The various factors were analysed for improving the model.