Permanent Magnet DC Motor Research Articles

Vibration Reduction Characteristics of Permanent Magnet DC Motors With Sawtooth Edge Poles

It is known that the slot frequency vibration is the one of the main components in electromagnetic vibration spectrum of permanent magnet DC motors (PMDCM). After finding that the vibration reduction scheme of the piecewise varying pole width (PVPW) is only effective for the odd order harmonic of slot frequency vibrations by analytical method, the PM pole with sawtooth edge is put forward to reduce all harmonic components of slot frequency vibrations of PMDCM. In this article, after the air gap flux density and radial force density are analyzed, the two vibration sources, radial force and bending moment, are derived for the motor with sawtooth edge poles (SEP). Then the optimized pole shape is obtained to reduce all harmonic components of both the radial force and bending moment at the same time. Three dimensional finite element method of electromagnetic field and structure are used to calculate the magnetic flux density, radial force and vibration for the motors of PVPW and SEP. Three permanent magnet motors with fixed pole width (FPW), PVPW and SEP are manufactured and tested. The comparison and verification show that SEP is better than the other two schemes in general.

Observer-based robust control for flexible-joint robot manipulators: A state-dependent Riccati equation-based approach

In this paper, the robust control problem is tackled by employing the state-dependent Riccati equation (SDRE) for uncertain systems with unmeasurable states subject to mismatched time-varying disturbances. The proposed observer-based robust (OBR) controller is applied to two highly nonlinear, coupled and large robotic systems: namely a manipulator presenting joint flexibility due to deformation of the power transmission elements between the actuator and the robot known as flexible-joint robot (FJR) and also an FJR incorporating geared permanent magnet DC motor dynamics in its dynamic model called electrical flexible-joint robot (EFJR). A novel state-dependent coefficient (SDC) form is introduced for uncertain EFJRs. Rather than coping with the OBR control problem for such complex uncertain robotic systems, the main idea is to solve an equivalent nonlinear optimal control problem where the uncertainty and disturbance bounds are incorporated in the performance index. The stability proof is presented. Solving the complicated robust control problem for FJRs and EFJRs subject to uncertainty and disturbances via a simple and flexible nonlinear optimal approach and no need of state measurement are the main advantages of the proposed control method. Finally, simulation results are included to verify the efficiency and superiority of the control scheme.

Optimal Tuning of Linear Quadratic Regulator Controller Using Ant Colony Optimization Algorithm for Position Control of a Permanent Magnet DC Motor

This paper presents the design of an optimal Linear Quadratic Regulator (LQR) controller using Ant Colony Optimization (ACO) and particle swarm optimization (PSO) methods for position control of a permanent magnet DC (PMDC) motor. In this work, Ant Colony control and particle swarm control algorithms have been utilized to set the optimal elements of the weighting matrices subjected to a proposed cost function. The proposed cost function is a combination of the quadratic performance index and integral square error. The proposed design can overcome the difficulty in setting the weighting matrices with the suitable elements. The simulation results using (Matlab Package) show that the optimal LQR controller using ACO algorithm can give excellent performance in terms of obtaining smooth and unsaturated state voltage control action that will stabilize the DC motor system performance and minimize the position tracking error of the system output. In addition, the rising time and settling time is decreased in comparison with the LQR based PSO controller performance.

Performance of the Noise and Vibration of the AC/DC Signal for a Permanent Magnetic DC Motor

Herein, a single-phase dc permanent magnet motor (PMM) operated at direct current (dc) was proposed, affected by a type of alternating current (ac) signal >5% and frequency between 50 and 3000 Hz to explore characteristics such as noise, vibration, and motor power efficiency. The finite-element method (FEA) was used to model the motor and the transient results of the core flux and current were simulated. The noise level of the motor was experimentally determined for the motor under normal dc power operation subjected to higher hybrid power supply. This indicates that the vibration displacement (mm) and velocity (mm/s) vary, while acceleration (mm/s <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) is linearly stable. From the experimental results, the vibration is inversely proportional to the noise. The lower noise level is only observed under medium frequency, similar to a bathtub curve. In addition, when the motor is operated at a low frequency of 50-500 Hz, the characteristics of the power performance were increased more than 1.5 times, including real power P (real power, Watt), apparent power S (apparent power, VA), and reactive power Q (reactive power, VAR), which is much higher than the high-frequency power signal at frequency >500 Hz, gradually stabilizing the motor power. Moreover, a hybrid ac signal of up to 15% was added to the motor system at a frequency between 50 and 500 Hz, drastically changing the displacement and vibration by up to 1.36 times. However, at high frequencies of >1 kHz, the power and noise increase slightly before reaching the steady state.

Model-free control of electrically driven robot manipulators using an extended state observer

This paper deals with the robust control of robot manipulators by presenting a novel voltage-based control approach. For this purpose, an Extended State Observer (ESO) is utilized to estimate the dynamical behaver of the system without any need to use the equations of motion including robot dynamics, actuator dynamics and their parameters in the proposed method. Convergence analysis proves that the estimated parameters converge to actual parameters asymptotically. The boundedness of tracking error is guaranteed through the Lyapunov theorem. Simulation results on an articulated robot driven by permanent magnet DC motors, and experimental implementation on a SCARA robot show that the proposed model-free controller has a satisfactory performance as compared to an adaptive uncertainty estimation-based controller.

Modeling the Performance of the Photovoltaic (PV) Water Pumping Systems (Dept. E )

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Adaptive fuzzy voltage-based backstepping tracking control for uncertain robotic manipulators subject to partial state constraints and input delay

The aim of this paper is to tackle the problem of adaptive fuzzy voltage-based tracking control for uncertain electrically driven robotic manipulators subject to input delay and partial state constraints in a unified framework. With the aid of barrier Lyapunov function-based backstepping method and adaptive fuzzy approximators, the proposed method is constructed for uncertain robotic systems in the framework of voltage control strategy. This is intended to convert robot control problem to motor control problem. Based on input integral technique, a new variable is introduced for the system such that the input-delayed robotic system is turned to the non-delayed robotic system. Furthermore, the number of adaptive learning parameters is free from the number of subsystems. In other words, only one adaptive parameter is adjusted online for each joint to reduce computational burden; hence, a new adaptive fuzzy voltage tracking control law is developed to ensure that all variables of the closed-loop system are semi-globally uniformly ultimately bounded. The tracking error of joint positions also converges to a small neighborhood around the origin such that the constraints on the joint angular positions and velocities are not transgressed during operation. Various scenarios for numerical simulations are given to show the potential of the proposed control algorithm when applied to a robot manipulator driven by permanent magnet dc motors.

Robust Control of Robotic Manipulators in the Task-Space Using an Adaptive Observer Based on Chebyshev Polynomials

In this paper, an adaptive observer for robust control of robotic manipulators is proposed. The lumped uncertainty is estimated using Chebyshev polynomials. Usually, the uncertainty upper bound is required in designing observer-controller structures. However, obtaining this bound is a challenging task. To solve this problem, many uncertainty estimation techniques have been proposed in the literature based on neuro-fuzzy systems. As an alternative, in this paper, Chebyshev polynomials have been applied to uncertainty estimation due to their simpler structure and less computational load. Based on strictly-positive-real (SPR) Lyapunov theory, the stability of the closed-loop system can be verified. The Chebyshev coefficients are tuned based on the adaptation rules obtained in the stability analysis. Also, to compensate the truncation error of the Chebyshev polynomials, a continuous robust control term is designed while in previous related works, usually a discontinuous term is used. An SCARA manipulator actuated by permanent magnet DC motors is used for computer simulations. Simulation results reveal the superiority of the designed method.

A Simple Nonlinear Observer for State and Unknown Input Estimation: DC Motor Applications

The contribution of this brief is to propose a method based on a simple nonlinear observer with an easy-to-compute observer gain, in order to achieve both state and unknown input (UI) estimation. Since the structure of the original model of the process does not require any transformation, the nonlinear dynamics are preserved. This allows an accurate estimation of the states and the UIs or faults. Two particular cases involving dc motors are illustrated in simulation and an experiment using a permanent magnet dc motor is presented.

Friction-Tracker-Embedded Discrete Finite-Time Sliding Mode Control Algorithm for Precise Motion Control of Worm-Gear Reducers Under Unknown Switched Assistive/Resistive Loading

This paper proposes a novel method for simultaneous estimation of unknown switched external disturbance and precise position control of dynamical systems which employ worm gear drive reducers. This algorithm is based on an improved discrete sliding mode control (DSMC) design which ensures convergence to the desired sliding set without introducing chattering effects to the dynamical system. In order to improve the performance of DSMC and to obtain an accurate estimation of gearbox model, a new method for incorporation of switched friction is proposed in the presence of external disturbance. To this end, the dynamical response of worm gear drive reducer is investigated in distinct switched disturbance modes of resistive disturbances, assistive disturbances and no disturbance to obtain approximate functions describing system dynamics in aforementioned configurations. In comparison with the feedback data, the obtained models permit appropriate incorporation of friction into the improved DSMC scheme. Based on multiple common Lyapunov functions and calculation of virtual reference signals for armature currents, the feasibility of control algorithm is ensured in all modes of switched dynamics. The effectiveness of the proposed estimation and control schemes has been verified using an experimental setup employing a worm gear drive reducer on which multiple permanent magnet DC motors are installed, and improvements resulted from incorporation of friction estimation algorithm are analyzed.

Stability analysis of brain emotional intelligent controller with application to electrically driven robot manipulators

This study discusses stability analysis of the brain emotional learning-based intelligent controller (BELBIC) for model-free tracking control of a class of uncertain non-linear systems. Due to the unique adaptation laws for the controller gains, stability analysis of these controllers is a challenging task. This issue constructs the motivation of this study to undertake this task. Similar to direct adaptive fuzzy control, the BELBIC plays the role of a direct intelligent controller. Thus, the stability of the BELBIC can be guaranteed based on the stability analysis of direct adaptive fuzzy control. The main objective of this study is that the stability of the BELBIC in tracking control of a class of uncertain non-linear systems is guaranteed. Based on the proposed stability analysis and Barbalat's lemma, BELBIC can yield in the asymptotic convergence of the tracking error to zero. In comparison with the existing works in the literature, the proposed approach has fewer tuning parameters. Therefore, the developed approach has a simple structure. The simulation results on an articulated manipulator actuated by permanent magnet DC motors and comparison with other model-free approaches are presented to show the superiority of the proposed approach.

Biomass Stand-Alone System for Power Supply Option to Remote Isolated Locations

Reliability and continuity of electricity supply generated by the use of fossil fuels cannot be guaranteed absolutely because of the present decline in oil and gas. Because of this, it becomes necessary to consider another form of energy generation such as biomass. In this work, the potential of electricity generation for a small household rural/isolated location using combustion technique was done. Due to the availability of sufficient biomass (agricultural waste) in rural/isolated locations, rice husk combustion technique for biopower generation was investigated in this work. The experiment was conducted at Uburu in Ohaozara Local Government Area of Ebonyi State. A 12V permanent magnet DC motor was used as the alternator while rice husk was used as biomass fuel. The biopower was achieved by heating water to steam which was used to turn the turbine attached to the permanent DC motor and a maximum of 155Whr was generated. From the result, it can be seen that the typical load of a household in a rural/isolated location is 55W and the peak experimental power is 154.96W. This peak experimental power is sufficient to carry the household load in a rural/isolated location. The peak experimental energy value is 1549.6Whr in a 10 minutes interval which is far more than the energy demand of 260Whr in a typical household in rural/isolated location. The result shows that biomass can be used to generate power for lighting point and power outlet for small households in rural/isolated locations.

Robust adaptive control of robot manipulators using Bernstein polynomials as universal approximator

SummaryThis article presents a robust adaptive controller for electrically driven robots using Bernstein polynomials as universal approximator. The lumped uncertainties including unmodeled dynamics, external disturbances, and nonimplemented control signals (they assumed as a function of time, instead a function of several variables) are represented with this powerful mathematical tool. The polynomial coefficients are then tuned based on the adaptation law obtained in the stability analysis. A comprehensive approach is adopted to include the saturated and unsaturated areas and also the transition between these areas in the stability analysis. As a result, the stability and the performance of the proposed controller have been improved considerably in dealing with actuator saturation. Also, in comparison with a recent paper based on uncertainty estimation using Taylor series, the proposed controller is less computational due to reducing the size of the matrix of convergence rate. A performance evaluation has been carried out to verify satisfactory performance of transient response of the controller. Simulation results on a Puma560 manipulator actuated by geared permanent magnet dc motors have been presented to guarantee its satisfactory performance.

EXPERIMENTAL STUDY OF PERMANENT MAGNET WITH VARIABLE POWER SUPPLY

In this paper we are studying about maximum R.P.M. of Permanent Magnet DC Motor. In this way we are using the regulator circuit and 1Amp. 2 Amp. 3Amp. With different voltages. R.P.M. of D.C. motor is measured by the digital type tachometer. The D.C. power supplies are obtaining by the rectifier circuit and also used the step down transformer.

Estimation of Actuator and System Faults Via an Unknown Input Interval Observer for Takagi–Sugeno Systems

This paper presents a simultaneous state variables and system and actuator fault estimation, based on an unknown input interval observer design for a discrete-time parametric uncertain Takagi–Sugeno system under actuator fault, with disturbances in the process and measurement noise. The observer design is synthesized by considering unknown but bounded process disturbances, output noise, as well as bounded parametric uncertainties. By taking into account these considerations, the upper and lower bounds of the considered faults are estimated. The gain of the unknown input interval observer is computed through a linear matrix inequalities (LMIs) approach using the robust H ∞ criteria in order to ensure attenuation of process disturbances and output noise. The interval observer scheme is experimentally evaluated by estimating the upper and lower bounds of a torque load perturbation, a friction parameter and a fault in the input voltage of a permanent magnet DC motor.

Selection of Motor foran Electric Vehicle: A Review

In this study, five kinds of drive train systems of the electric motor drives for EVs are discussed. Furthermore, the requirements of EVs on electric motor drives are presented. Hence, a review on motor types and their drives used in EV has been made. The comparative investigation on the efficiency, cost, maximum speed, and reliability is carried out for switched reluctance motor, induction motor, permanent magnet motor, DC motor and axial flux permanent magnet brushless dc motor, in order to find out most appropriate electric motor drives for electric vehicle applications. According to these researches, some conclusions have been obtained. The study shows that axial flux permanent magnet brushless dc motor drives are the prior choice for electric vehicles.

Fractional-order PID controller for permanent magnet DC motor based on PSO algorithm

&lt;span&gt;This paper proposes the fractional-order proportional integral derivative (FOPID) controller, as a speed controller for permanent magnet direct current (PMDC) motor, instead of the traditional integer-order PID controller. The FOPID controller is the general form of the integer-order PID controllers, which found wide applications in all engineering fields. In this work a hybrid M-file and SIMULINK program is developed to simulate the overall system, the FOPID controller has five associated parameters. The optimum values of those parameters are found out by using particle swarm optimization technique. Simulation results show excellent command speeds tracking and superior dynamic response in conjunction with that of the integer-order PID controller. The proposed controller shows a high ability to overcome any external disturbance the system may be exposed; also, it performs a high degree of robustness to control the system in motoring and regenerative operating modes.&lt;/span&gt;

Speed Control Analysis of Permanent Magnet DC motor with Zeta Converter

This Paper explains the performance analysis of Permanent Magnet DC motor. Here the Solar PV cells are used as a source and connected through the zeta converter and the DC voltage of the converter is fed to armature of the DC motor.The Zeta Converter is a fourth order DC to DC converter made up of two inductors and two capacitors operating as either step up or step down.and The Performance such as Speed are analyzed with MATLAB simulink. The results of the plots are discussed in the below studies.

Sensorless Robust Speed Controller Design of Pancake Axial Field PMDC Motor

Due to superior multi-dimensional features (e.g., large torque to inertia ratio, fast response, high power density, negligible maintenance requirement, etc.) the axial-field pancake permanent magnet dc (PMDC) motors are popularly used for many control applications. When driven by pulsewidth modulation (PWM) controllers, due to their negligible electrical time constant, the armature current tends to be discontinuous. When the current disappears the measured armature voltage [i.e., back electromotive force (EMF)] is linearly related to its speed. In this article, the armature voltage at zero current is sampled to be used as feedback for speed control of axial field PMDC motors for wide range applications. Negligible prospect of demagnetization makes these motors ideal candidate to be controlled sensorless. When PWM frequency is large the armature time-constant poses as constraint for the back EMF to be available for sampling. The choice of PWM frequency is an important design parameter for the proposed concept. Further, this article explores, in practical domain, the usability of different control functions for robust speed control of pancake PMDC motors. It also details product design for sensorless PMDC motor speed controller using modified second-order sliding mode control function.

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.