A robust control method for a PV-supplied DC motor using universal learning networks

In this paper, a new robust control method and its application to a photovoltaic (PV) supplied, separately excited DC motor loaded with a constant torque is discussed. The robust controller is designed against the load torque changes by using the first and second ordered derivatives of the universal learning networks (ULNs). These derivatives are calculated using the forward propagation algorithm, which is considered as an extended version of real time recurrent learning (RTRL). In this application, two ULNs are used: The first is the ULN identifier trained offline to emulate the dynamic performance of the DC motor system. The second is the ULN controller, which is trained online not only to make the motor speed follow a selected reference signal, but also to make the overall system operate at the maximum power point of the PV source. To investigate the effectiveness of the proposed robust control method, the simulation is carried out at four different values of the robustness coefficient γ in two different stages: The training stage, in which the simulation is done for a constant load torque. And the control stage, in which the controller performance is obtained when the load torque is changed. The simulation results showed that the robustness of the control system is improved although the motor load torque at the control stage is different from that at the training stage.     

Torque ripple analysis of a PM brushless DC motor using finite element method

Three-phase permanent magnet brushless DC motors are widely used. As a function of the rotor position, the torque produced by these machines has a pulsating component in addition to the DC component. This pulsating torque has a fundamental frequency corresponding to six pulses per electrical revolution of the motor. The shape of the torque waveform and, thus, the frequency content of the waveform can be influenced by several factors in the motor design and construction. This paper addresses the various factors that influence the torque waveshape. It is shown that in addition to the basic induced electromotive force (EMF) waveshape, the magnetic saturation in the stator core, and the accuracy in the skewing are also key factors in determining the torque waveshape. Computer simulation using finite element technique has been conducted to study the torque waveform. Simulation results successfully duplicated the torque waveforms measured in experiments under different excitation currents.     

Matching of a DC motor to a photovoltaic generator using a step-upconverter with a current-locked loop

A photovoltaic (PV) generator is a nonlinear device having insolation-dependent volt-ampere characteristics. Because of its relatively high cost, the system designer is interested in optimum matching of the motor and its mechanical load to the PV generator so that maximum power is obtained during the entire operating period. However, since the maximum-power point varies with solar insolation, it is difficult to achieve an optimum matching that is valid for all insolation levels. In this paper it is shown that for maximum power, the generator current must be directly proportional to insolation. This remarkable property is utilized to achieve insolation-independent optimum matching. A shunt DC motor driving a centrifugal water pump is supplied from a PV generator via a step-up converter whose duty ratio is controlled using a current-locked feedback loop     

Advanced fault diagnosis of a DC motor

This paper presents a model of the DCc motor with an eccentric rotor. The winding function theory shows the effect of eccentricity fault on the motor inductances and the simulation is done using a nonsymmetric air-gap function. A modified equation is presented to show the existence of rotor slot harmonics in the DC motor current. To detect the eccentricity fault, a pattern recognition technique is utilized. The proposed algorithm works at steady state and uses armature current as input. The rotor speed is needed in order to provide the appropriate feature for the classifier. Therefore, rotor speed is estimated from the armature current using the commutation harmonics. The experimental results obtained from a 1/3-hp shunt DC motor verifies the proposed method. In order to cover different motor conditions, data are collected at different shaft speeds for both a healthy dc motor and a dc motor with an unbalanced load which exhibits static eccentricity.     

A DC linear motor with a square armature

One of the advantages in using DC linear motors for low speed linear drives is that the position and speed of these motors can be precisely controlled with the help of a feedback circuit. In addition, linear motors get rid of the rotary-to-linear conversion mechanism, hence reduce the weight cost backlash and dynamic complexity which produces friction, and eventually minimizes the space required by the drive. The neodymium-iron-boron (NdFeB) permanent magnet with high energy product has been used as the field source of these motors thus reducing the size and weight of the motors further. This paper describes the analysis of flux and force in a DC linear stepping motor built with NdFeB magnets. In order to verify the experimental results obtained for determining the performance of the motor, a computational method has been employed to compute the flux distributions throughout the machine. The discrepancy between the measured and computed values of axial and radial flux at most points ranges between 8% and 16% while the discrepancy between the measured and computed values of starting thrust is in the range between 4% and 13%     

Speed control of a PV powered DC motor driving a self-excited3-phase induction generator for maximum utilization efficiency

Photovoltaic (PV) powered DC motors driving dedicated loads (e.g. water pumps) are increasingly used in the remote rural areas of many developing countries. The key to their success is simplicity (direct coupling, no DC-AC conversion, no storage batteries, etc.). Because of the relatively high cost of the PV array, the system designer is interested in maximizing its utilization efficiency. A PV powered DC motor can also be used to drive a three-phase self-excited induction generator (SEIG). This arrangement is useful as part of an integrated renewable energy system (IRES), which takes advantage of the inherent diversity of wind and solar energy in most developing countries to improve power quality. The SEIG is driven by a wind-turbine, DC motor, or both. Another advantage of this arrangement is its versatile control characteristics through the DC motor control. This paper describes a technique to maximize the utilization efficiency of the PV array by controlling the field current of the DC motor through a DC chopper     

Identification of a pilot scale fluidised-bed coal gasification unit by using neural networks

This work is under the general framework of advanced control system application to a pilot scale gasification reactor. In this paper the identification step of the system and the dynamic analysis have been studied. For system identification the artificial neural network (ANN) has been used and an ANN model was developed.     

Laboratory implementation of a neural network trajectory controllerfor a DC motor

The laboratory implementation of a neural network controller for high performance DC drives is described. The objective is to control the rotor speed and/or position to follow an arbitrarily selected trajectory at all times. The control strategy is based on indirect model reference adaptive control (MRAC). The motor characteristics are explicitly identified through a multilayer perceptron type neural network. The output of the trained neural network is used to drive the motor in order to achieve a desired time trajectory of the controlled variable. The neural network controller is assembled in a commercially available PC-based real-time control system shell, using software subroutines. An H-bridge, DC/DC voltage converter is interfaced with the computer to generate the specified terminal voltage sequences for driving the motor. All software and hardware components are off the shelf. The versatility of the motor/controller arrangement is displayed through real-time plots of the controlled states     

Self-tuning control of induction motor drive using neural networkidentifier

This study presents a new self-tuning PI speed controller with load torque observer and feedforward compensation based on neural network identification for an induction motor. A two-layer neural estimator is also used to provide a real-time adaptive estimation of the unknown motor dynamics. The widely used projection algorithm is used as the learning algorithm for this network, to minimize the difference between the motor's actual response and that predicted by the neural estimator. The proposed neural estimator uses this learning to adjust PI speed controller with a load torque observer to generate the control signal online, thereby bringing the motor output to a desired reference trajectory. The theoretical analysis, simulation and experimental results demonstrate the proposed scheme's effectiveness     

Electromagnetic modeling and control of switched reluctance motor using finite elements

This paper considered the implementation of a current control method for switched reluctance motors (SRMs) and presented a novel approach to the accurate online modeling of a three phase 6/4 SRM drive. A three phase 6/4 SRM is given theoretical calculation of inductance of the SRM model. The SRM was then tested in a Matlab/Simulink environment and numerically analyzed by using nonlinear 2D look-up tables created from its calculated flux linkage and static torque data. The simulation studied the hysteresis and voltage control strategies. The ideal waveform of stator current under the voltage-current condition and improved shape of rotor were proposed.     

Design and demonstration of a microcomputer controller for anindustrial sized DC motor

A method of designing a three-phase fully-controlled thyristor-DC motor drive system with speed and/or current closed-loop control is presented. Both the circuit design and the control algorithm of a continuous (analog) controller or a digital controller design are studied. The effectiveness of the design method is well verified by extensive experiments. The dynamics of the system reasonably confirm the theoretical analysis. In addition, the goal of multiple operating modes of the thyristor converter is also achieved. It is shown that both good performance and good flexibility with online calculation can be obtained by using a low-cost microcomputer. The parts cost of the microcomputer-based controller is still a little higher than the continuous controller, but the trend is towards lower costs of microcomputers. The main advantages of the digital controller are its versatility and flexibility     

改善直流牵引电机换向性能探讨

介绍了衡量直流电机换向性能的指标参数;分析了如何根据无火花换向区域试验结果,通过调整电机的参数,使电机达到最佳换向;介绍了在电机设计时改善电机换向的几种有效方法。     

Numerical investigation and optimization of the thermal performance of a brushless DC motor

A computational study of a brushless DC motor is presented to determine the thermo-flow characteristics in the windings and bearings under the effects of heat generation. The rotation of the rotor blades drives an influx of ambient air into the rotor inlet. The predicted inflow rates were higher at the front inlet than at the rear inlet due to non-uniform pressure distribution. A recirculation zone appeared in the tiny interfaces between windings. The poor cooling performance was caused by flow separation near the groove threshold by the inclination angle of the bearing groove and by a relatively slow velocity near the bearing and between windings. Based on these results, design parameters for the inlet location and geometry, and for the bearing groove geometry, were determined and optimized to enhance the cooling performance up to 24%.     

Automatic diagnosis and location of open-switch fault in brushless DC motor drives using wavelets and neuro-fuzzy systems

The faulty performance of permanent-magnet (PM) brushless dc motor drives is studied under open-switch conditions. The wavelet transform is used to extract diagnostic indices from the current waveform of the motor dc link. An intelligent agent based on adaptive neuro-fuzzy inference systems (ANFIS) is developed to automate the fault identification and location process. ANFIS is trained offline using simulation results under various healthy and faulty conditions obtained from a lumped-parameter, network model. ANFIS testing shows that the system could not only detect the open-switch fault, but also identify the faulty switch. Good agreement between simulation results and measured waveforms confirms the effectiveness of the proposed methodology.     

A microcomputer-based induction motor drive system using currentand torque control

This paper proposes an induction motor drive with current and torque control. The current control based on the current error with the current controller yields h_l signal. The torque control based on the torque error with the torque controller yields a h_l signal. According to the h_l signal, the h_l signal and the appropriate voltage vector is selected by using a look-up table to control the induction motor drive to obtain a rapid speed response. The torque controller, current controller, and d-q frame transform are constructed by the hardware which reduce the running time of the microcomputer to obtain a high performance drive. Computer simulations and experimental results demonstrate that the proposed method can obtain a high performance induction motor drive. Meanwhile, employing the advantages of the added zero voltage vector to reduce the inverter switching frequency greatly increasing the efficiency of the inverter     

Integrated modeling and control of a PEM fuel cell power system with a PWM DC/DC converter

A fuel cell powered system is regarded as a high current and low voltage source. To boost the output voltage of a fuel cell, a DC/DC converter is employed. Since these two systems show different dynamics, they need to be coordinated to meet the demand of a load. This paper proposes models for the two systems with associated controls, which take into account a PEM fuel cell stack with air supply and thermal systems, and a PWM DC/DC converter. The integrated simulation facilitates optimization of the power control strategy, and analyses of interrelated effects between the electric load and the temperature of cell components. In addition, the results show that the proposed power control can coordinate the two sources with improved dynamics and efficiency at a given dynamic load.     

Control of a linear permanent magnet brushless DC motor via exactlinearization methods

The author develops a position controller for permanent magnet brushless DC motors (PMBDCMs) which systematically determines control laws for operation in both the transient and steady-state with consideration of reluctance force. The controller design is based on a differential geometric approach which assists the motor in overcoming its inherent deficiencies, such as effects of torque ripples and reluctance torque. This is achieved by transforming the nonlinear state equations into an exact linear model. Computer simulations of the resulting closed-loop system were performed to demonstrate the effectiveness of the proposed control laws. Simulation results of the control variables were injected into the actual nonlinear system in an experimental open-loop setup to validate the design procedure     

防止直流牵引电动机环火的措施

在对直流牵引电动机环火产生的原因进行分析的基础上,提出了防止环火的各项措施。     

A photovoltaic panel emulator using a buck-boost DC/DC converter and a low cost micro-controller

In order to facilitate the design and testing of photovoltaic (PV) power systems, a PV emulator which models the electrical characteristic of a PV panel or array is needed. Among different approaches to modeling PV characteristic, namely the I–V curve, curve-fitting is a popular approach. Even though a single high-order polynomial equation may accurately represent the I–V curve, the process of derivation and implementation is rather complex. This paper hence proposes the use of piecewise linear approach which is easier to derive and implement in a low-cost micro-controller. A two-switch buck-boost DC/DC converter is selected as the PV emulator and is analyzed. Experimental results on a hardware prototype of the proposed PV emulator are reported to show the effectiveness of the approach.