Model Of DC Motor Research Articles

Dynamic event-based mixed H∞ and dissipative asynchronous control for Markov jump singularly perturbed systems

The paper investigates the issue of mixed H∞ and dissipative asynchronous controller design for a class of Markov jump singularly perturbed systems (MJSPSs). A suitable dynamic event-triggered rule is offered to further mitigate the transmission burden of communication network. Since the mode information of Markov chain is extremely difficult to get, an asynchronous controller is well constructed. Hence, a hidden Markov model (HMM) is chosen to describe the non-synchronous facts between states of the original Markov chain and the constructed non-synchronous controller. Resorting to the Lyapunov functional concerning the internal dynamic variable, sufficient conditions of stochastically stable with a certain mixed H∞ and dissipative performance for the resulting closed-loop MJSPSs are offered. Based on the LMI technique, the design framework of asynchronous controller and the dynamic event-triggered rule are given in a unified way. Lastly, a modified DC motor model is offered to demonstrate the superiority of the proffered method.

Finite-time control for Markovian jump systems subject to randomly occurring quantization

Abstract This paper is concerned with the issue of finite-time control for Markovian jump systems randomly occurring quantization. By absorbing the phenomena of unmeasurable state and randomly occurring quantization, a novel nonhomogeneous Markovian switching system is constructed, and an observer-based controller and non-fragile observer are designed. By utilizing Lyapunov function method, sufficient admissibility conditions are derived for the stability of the underlying system in a finite-time domain. Finally, a DC motor model is presented to explain the feasibility and validity of the proposed design method.

Linear quadratic regulator and pole placement for stabilizing a cart inverted pendulum system

The system of a cart inverted pendulum has many problems such as nonlinearity, complexity, unstable, and underactuated system. It makes this system be a benchmark for testing many control algorithm. This paper presents a comparison between 2 conventional control methods consist of a linear quadratic regulator (LQR) and pole placement. The comparison indicated by the most optimal steps and results in the system performance that obtained from each method for stabilizing a cart inverted pendulum system. A mathematical model of DC motor and mechanical transmission are included in a mathematical model to minimize the realtime implementation problem. From the simulation, the obtained system performance shows that each method has its advantages, and the desired pendulum angle and cart position reached.

Research on Simulation of Electromagnetic Field of DC Motor Based on Finite Element Analysis

With the continuous development of science and technology, the magnetic field distribution of DC motors is analyzed based on the finite element theory. These provide a theoretical basis and reliable basis for analyzing the working principle of DC motors and the further development and application of DC motors, establishing a reasonable non-linear model of DC motors, and applying a finite element analysis software to establish a simulation model of the electromagnetic field of DC motors. The characteristics of the electromagnetic field were analyzed during the start-up process, and the analysis results provided a theoretical basis and basis for the further optimization of the electromagnetic field of the DC motor.

Control of velocity of DC motors by classical and passivity methods measuring only position: Theory and experimental comparison

It is usual that in the design and development of control schemes, specifically in electrical machines, it is considered that the angular velocity measurement signal is available, but in practice, it is the signal of the angular position which is actually available. So that, in order to obtain the velocity, some numerical differentiation methods, whose dynamics is not included in the design of the controllers nor in the stability analysis of the closed loop, are implemented. In the present work, two control schemes for direct current motors are designed and implemented experimentally considering that only the angular position is measured. A filter of second order of relative degree 1 is used in order to obtain a signal for velocity feedback. The first one is a PID regulator of two degrees of freedom with an antiwindup structure, which is tuned analytically, and the second one is a new velocity tracking passivity based controller whose design takes advantage of the properties presented by the model of DC motor. Formal stability analyses for both control schemes are presented.

DC Motor Simulation using LTSpice

DC motor is simulated in this paper, in which LTSpice simulator is used. DC Motor is still highly needed in industrial world, for applications that needs goods’ movement in the process line. Therefore, in this paper, it is important to do simulation before real-world electronic circuit is developed. Thereby we promote green eco-friendly environment, by reducing electronic waste caused by prototyping. The simulation of DC Motor is divided into three (3) parts. First, a simplified DC motor model is assumed, and then the effect of inductance and inertia of the DC motor are considered. Lastly, a small perturbation is noticeable in the output of the electrical DC motor, and after a careful insight into the slip-ring mechanical inside of the DC motor, the effect of it is added in the final simulation model. This gradual modelling methodology certainly helps students to correlate between DC motor modelling with the sampled real-world data, which is taken directly from the experimental laboratory.

Research on brushless DC hub motor control system

The brushless DC hub motor is an important part of the wheeled electric vehicle. It has the advantages of simple structure, reliable operation, high efficiency and good speed regulation performance. Based on the mathematical model of brushless DC motor (BLDCM), the ontology model of BLDCM is established based on Matlab2016/Simulink environment combined with S-function. Then the model of speed-current double closed-loop PID, fuzzy adaptive PID and sliding mode control system of brushless DC hub motor is established, and the control system of BLDCM is simulated according to the demand of the electric vehicle. The results show that the sliding mode control system has a good control effect and lays a solid foundation for the design of the actual control system.

Simulation model of speed control DC motor using fractional order PID controller

DC motor speed can be achieved by changing the armature voltage fed through converter that generally employed with conventional PID. However, conventional PID controller has some disadvantages such as the high starting overshoot and sensitivity to controller gains. On the other hand, fractional order PID has potential to accomplish what conventional PID cannot. In this study, fractional order PID controller was applied to control speed of DC motor. By calculated error that occurred by reference speed and actual speed, fractional order PID brought motor run at desired speed. The parameters of fractional order PID controller (proportional constant, integral constant, derivative constant, derivative order and integral order) are optimally tuned by using Genetic Algorithm, and the optimization performance target is based on Integral Time Absolute Error (ITAE) criterion. Oustaloup’s approximation method is used to approximate the fractional order differentiator and integrator. This controller performances are tested in simulation mode using MATLAB/Simulink. Speed response of motor DC are compared between fractional order PID and conventional PID controller. The result of fractional order PID controller could reduce overshoot, settling time and steady state error. With this result, show that fractional order PID controller perform better than conventional PID controller.

Propeller speed estimation for unmanned aerial vehicles using Kalman filtering

This paper presents an online propeller speed estimation system for a multirotor unmanned aerial vehicle (UAV) equipped with brushless DC (BLDC) motors and powered by a lithium-polymer battery pack. Propeller speed estimation is based on battery drain current measurement extended with averaged state-space model of brushless DC motor utilised within a Kalman filter-based state estimator. Based on the BLDC motor and propeller physical parameters and utilising corresponding mathematical model, the estimation system is implemented within the flight computer on board the UAV. The proposed propeller speed estimation algorithm is verified experimentally for a wide range of propeller operating regimes, which has shown that the proposed method is able to provide efficient estimation of UAV propeller speed.

Digital twin of mechatronic drive based on the optimal control model of BLDC motor

This paper presents a digital twin of a mechatronic drive based on a brushless DC (BLDC) motor model based on a nonlinear discrete optimal control model. Some parameters of a BLDC motor, such as resistance and inductance of windings, magnetic flux, viscous friction coefficient in bearings, angular velocity and electromagnetic moment, can change due to both degradation of structural elements and external forces. Simulation by a complete enumeration of the values of the parameters of the mechatronic device with a certain step will make it possible to adapt the program of the control device to changing operating conditions according to the criterion of minimizing the control energy by changing the parameters of the state matrices and control of the digital twin. As a result, the accuracy of the movement of the mechatronic device along the given trajectory will increase due to the greater correspondence of the control parameters to the real object.

H∞ Control for Stochastic Singular Systems With Time-Varying Delays

In this article, we study the H ∞ control problems for stochastic singular systems with time-varying delays. Firstly, a new Lyapunov-Krasovskii functional is constructed, employing the free weighting matrix technique and Jensen inequality, the stochastic admissibility criteria in the mean square for stochastic singular time-varying delay systems are proposed on the basis of the auxiliary vector function. Secondly, the state feedback controller is designed such that the resulting closed-loop system meets regular, impulse-free, stochastically stable in the mean square and has H ∞ performance γ. In the proof process, the dual equation is used to derive the conditions of stochastic admissibility in the mean square. Finally, a practical example of DC motor model is presented to show the validity of our proposed theoretical results.

Passivity-Based Control for Hidden Markov Jump Systems With Singular Perturbations and Partially Unknown Probabilities

In this article, the passivity-based control problem is addressed for hidden Markov jump systems with singular perturbations and partially unknown probabilities. The hidden Markov model (HMM) with partially unknown probabilities is introduced, where the partially unknown probabilities may exist in either the transition probability matrix of Markov chain, the observation probability matrix of observed signal, or in both of them. Thus, the underlying HMM is more general than the one in some existing works. By using this HMM, some passivity analysis criteria are established for Markov jump singularly perturbed systems with partial unknown probabilities. Based on these criteria, a unified method is presented for the design of controllers to ensure the passivity of the system. A numerical example and an armature controlled dc motor model are given to illustrate the efficiency of the proposed method.

DC motor simulation transfer function estimation: case study Proteus Ver. 7

Computing technology development today has a significant influence on the design process of a product or system even including the learning process in the field concerned. The electronics and control field is a field that greatly helped by these developments. Developments of electronic products or systems become faster and more efficient with the availability of CAD (Computer-Aided Design) software. Some Electronic CAD software provides DC motor model, as Proteus 7.0. Availability of this model is beneficial in control system designing and learning but the availability of a DC motor models are often constrained because are not accompanied with adequate information about internal parameters of the dc motor model or dc motor modeling done in programming so it is not possible to derive dc motor transfer function based on internal parameters. This study successfully showed transfer function derivation of dc motor in Proteus CAD simulation with a black-box approach for linear systems.

Modeling and Control Unmanned Surface Vehicle (USV) with Hybrid Drivetrain

With the rapid development of unmanned surface vehicle (USV), the development of hybrid electric vehicles on USV is a technology that has a very important role to overcome the problem of how long the vehicle can be used. In hybrid electric vehicles (HEV), the main components consist of generators, electric motors, and batteries. Modeling component is intended to design models that fit on unmanned surface vehicle and represent the state of USV with hybrid drivetrain. This paper focuses on modeling USV with hybrid drivetrain. This vehicle uses a series configuration so that the generator act as a power generating system. The power system on USV was chosen using hybrid sources of DC generator and lithium-ion battery pack. The optimal size of DC generator and battery pack are very important to ensure that USV can work for a long period of time. This paper describes the simple characteristics of a DC generator with a PI controller and gain-scheduling PI controller which is accurate in generating 380V output voltage according to the initial plan to be built. We also described the model of permanent magnet dc motor as a driver in USV and described simulation about 200Ah 36V lithium-ion batteries. The development of this model will be represented in MATLAB/Simulink.

Solar powered UAV model on MATLAB/Simulink using incremental conductance MPPT technique

Purpose The aviation industry has started environment friendly and also conventional energy independent alternative energy dependent designs to reduce negative impacts on the nature and to maintain its future activities in a clear, renewable and sustainable way. One possible solution proposed is solar energy. Solar-powered aerial vehicles are seen as key solutions to reduce global warming effects. This study aims to simulate a mathematical model of a solar powered DC motor of an UAV on MATLAB/Simulink environment. Design/methodology/approach Maximum power point tracking (MPPT) is a critical term in photovoltaic (PV) array systems to provide the maximum power output to the related systems under certain conditions. In this paper, one of the popular MPPT techniques, “Incremental Conductance”, is simulated with solar-powered DC motor for an UAV design on MATLAB/Simulink. Findings The cascade structure (PV cell, MPPT, buck converter and DC motor models) is simulated and tested under various irradiance values, and results are compared to the DC motor technical data. As a result of that, mathematical model simulation results are overlapped with motor technical reference values in spite of irradiance changes. Practical implications It is suggested to be used in real time applications for future developments. Originality/value Different from other solar-powered DC motor literature works, a solar-powered DC motor mathematical model of an UAV is designed and simulated on MATLAB/Simulink environment. To adjust the maximum power output at the solar cell, incremental conductance MPPT technique is preferred and a buck converter structure is connected between MPPT and DC motor mathematical model. It is suggested to be used in solar-powered UAV designs for future developments.

Linear quadratic regulator problem governed by granular neutrosophic fractional differential equations

Quadratic cost functions estimation in the linear optimal control systems governed by differential equations (DEs) or partial differential equations (PDEs) has a well-established discipline in mathematics with many interfaces to science and engineering. During its development, the impact of uncertain phenomena to objective function and the complexity of the systems to be controlled have also increased significantly. Many engineering problems like magnetohydromechanical, electromagnetical and signal analysis for the transmission and propagation of electrical signals under uncertain environment can be dealt with. In this paper, we study the optimal control problem with operating a fractional DEs and PDEs at minimum quadratic objective function in the framework of neutrosophic environment and granular computing. However, there has been no studies appeared on the neutrosophic calculus of fractional order. Hence, we will introduce some derivatives of fractional order, including the neutrosophic Riemann–Liouville fractional derivatives and neutrosophic Caputo fractional derivatives. Next, we propose a new setting of two important problems in engineering. In the first problem, we investigate the numerical and exact solutions of some neutrosophic fractional DEs and neutrosophic telegraph PDEs. In the second problem, we study the optimality conditions together with the simulation of states of a linear quadratic optimal control problem governed by neutrosophic fractional DEs and PDEs. Some key applications to DC motor model and one-link robot manipulator model are investigated to prove the effectiveness and correctness of the proposed method.

Permanent magnet DC motor (PMDC) model identification and controller design

Abstract System modeling is a set of mathematical equations that describe the dynamical behavior of a system. It is considered as a primary concern in determining a suitable controller to meet specific requirements. An autoregressive with exogenous terms (ARX) model for a PMDC motor is identified experimentally based on the recursive least square (RLS) method. Adaptive discrete pole placement controller (APPC) is proposed and designed aiming to control the motor revolving speed. For the comparison purpose, a discrete Proportional Integral (PI) controller is also considered in this work. The steady step response, transient response, and the mean squared error (MSE) is counted throughout the comparison. The e ect of the uncertainties in the PMDC model is also investigated in this paper. The result shows a superiority in the performance of the proposed controller compared to that obtained using PI controller.

Continuous Discrete Sequential Observers for Time-Varying Systems Under Sampling and Input Delays

We provide continuous-discrete observers for a large class of time-varying linear systems where the inputs and outputs have sampling and delays, and where the systems and outputs contain uncertainties. We allow the delays in the output and input to differ and to be arbitrarily long. We use the observers to design controls that ensure input-to-state stability, under delays and sampling. The observers and controls have no distributed terms. We illustrate our work in a dc motor model.

A state augmentation approach to interval fault estimation for descriptor systems

This paper proposes a state augmentation approach to achieve interval fault estimation for descriptor systems with unknown but bounded disturbances and measurement noises. An augmented descriptor system, which is equivalent to the original system, is constructed while the fault vector is considered as an auxiliary state. Based on this augmented system, a robust fault estimation observer is designed to estimate the actuator faults. Under this augmented descriptor form, the conservatism of observer gain matrix can be significantly reduced by introducing more design degrees of freedom. Moreover, interval estimation of actuator faults can be achieved by using zonotopic techniques. Finally, a DC motor model simulation is used to illustrate the effectiveness of the proposed approach.

Adaptive Control of DC Motor Servo System With Application to Vehicle Active Steering

The direct current (dc) motor servo systems are widely used in vehicles. The parameters and disturbances of the servo systems are usually uncertain or unknown, which makes it difficult to achieve precise control. Motivated by this, an adaptive control scheme is proposed in this paper for the dc motor servo systems with unknown parameters and uncertain disturbances. A universal dc motor model is built, based on which the control law is deduced by backstepping method. The closed-loop system stability is ensured. Simulation results are provided to verify the effectiveness of the presented control scheme. Moreover, the method is utilized in active steering control of an intelligent vehicle, which is verified by the experiments on a hardware-in-loop bench.