Dynamic Model Of Motor Research Articles

Synchronization controller design of two coupling permanent magnet synchronous motors system with nonlinear constraints

In this paper, two coupling permanent magnet synchronous motors system with nonlinear constraints is studied. First of all, the mathematical model of the system is established according to the engineering practices, in which the dynamic model of motor and the nonlinear coupling effect between two motors are considered. In order to keep the two motors synchronization, a synchronization controller based on load observer is designed via cross-coupling idea and interval matrix. Moreover, speed, position and current signals of two motor all are taken as self-feedback signal as well as cross-feedback signal in the proposed controller, which is conducive to improving the dynamical performance and the synchronization performance of the system. The proposed control strategy is verified by simulation via Matlab/Simulink program. The simulation results show that the proposed control method has a better control performance, especially synchronization performance, than that of the conventional PI controller.

Using FE Calculations and Data-Based System Identification Techniques to Model the Nonlinear Behavior of PMSMs

This paper investigates the modeling of brushless permanent-magnet synchronous machines (PMSMs). The focus is on deriving an automatable process for obtaining dynamic motor models that take nonlinear effects, such as saturation, into account. The modeling is based on finite element (FE) simulations for different current vectors in the$dq plane over a full electrical period. The parameters obtained are the stator flux in terms of the direct and quadrature components and the air-gap torque, both modeled as functions of the rotor angle and the current vector. The data are preprocessed according to theoretical results on potential harmonics in the targets as functions of the rotor angle. A variety of modeling strategies were explored: linear regression, support vector machines, symbolic regression using genetic programming, random forests, and artificial neural networks. The motor models were optimized for each training technique, and their accuracy was then compared based on the initially available FE data and further FE simulations for additional current vectors. Artificial neural networks and symbolic regression using genetic programming achieved the highest accuracy, particularly with additional test data.

Path Tracking Control of Micro-Tracked Mobile Robot

The positioning accuracy of tracked mobile robot is low because of sliding in steering process. Taking the micro-tracked mobile robot as the platform, the interface force between tracks and ground was analyzed, and the motor model, kinematic model and dynamic model were established further. A tracking error controller was built based on the tracking error equations, and the co-simulation of mechanical and control system was applied to predict the robot’s trajectory. That controller was applied on a small tracked mobile robot designed by the authors’ laboratory, and the path tracking experiments with and without obstacles had been done. The results show that the robot can accurately track the given path, whether there are obstacles or not.

Aggregation method for motor drive systems

When many variable frequency drives are connected to a common switchboard, their aggregated effect on system dynamics can be significant. In this paper, the aggregation method for variable frequency drives and their motors in industrial facilities is proposed, which is suitable for power systems dynamic studies. The proposed method can be applied to various types of motor drive systems. There are two steps involved for the proposed aggregation method: (1) aggregate motor drive systems connected to the same bus, and (2) further combine the aggregated model of motor drive systems from Step 1 with upstream series impedance and/or transformers. Due to involvement of high-order transfer functions in dynamic models of individual motor drive systems, Pade approximation is used as a useful tool in the aggregation process. Using the proposed aggregation method, an equivalent aggregated dynamic model of motor drive systems can be obtained at the substation bus. A case study is conducted in the paper, and the proposed aggregation method is verified to be effective by the case study.

Design High-Efficiency Intelligent PID like Fuzzy Backstepping Controller for Three Dimension Motor

The minimum rule base Proportional Integral Derivative (PID) Fuzzy backstepping Controller for three dimensions spherical motor is presented in this research. The popularity of PID Fuzzy backstepping controller can be attributed to their robust performance in a wide range of operating conditions and partly to their functional simplicity. The process of setting of PID Fuzzy backstepping controller can be determined as an optimization task. Over the years, use of intelligent strategies for tuning of these controllers has been growing. PID methodology has three inputs and if any input is described with seven linguistic values, and any rule has three conditions we will need 7 × 7 × 7 = 343 rules. It is too much work to write 343 rules. In this research the PID-like fuzzy controller can be constructed as a parallel structure of a PI-like controller and a PD-like fuzzy controller to have the minimum rule base. However backstepping controller is work based on cancelling decoupling and nonlinear terms of dynamic parameters of each dimension, this controller is work based on spherical motor dynamic model and this technique is highly sensitive to the knowledge of all parameters of nonlinear three dimension spherical motors dynamic equation. This research is used to reduce or eliminate the backstepping controller problem based on minimum rule base fuzzy logic theory to control of spherical motor system and testing of the quality of process control in the simulation environment of MATLAB/SIMULINK Simulator.

Induction Motor Driven by a CAMC Using Predictive Control

This work presents a control strategy for an induction motor fed by a Cascade Asymmetric Multilevel Converter (CAMC). The approach is based on the Finite-States Model Predictive Control technique and uses the dynamic motor model and the converter model to pre-calculate the evolution of the variables of interest. These target variables are jointly compared with their reference values by means of an optimization function which allows to determine the best state among all switching combinations. This selection is carried out in a direct way, in each sampling period without modulator.

Design New PID like Fuzzy CTC Controller: Applied to Spherical Motor

The minimum rule base Proportional Integral Derivative (PID) Fuzzy Computed Torque Controller with application to spherical motor is presented in this research. The popularity of PID Fuzzy Computed Torque Controller can be attributed to their robust performance in a wide range of operating conditions and partly to their functional simplicity. PID methodology has three inputs and if any input is described with seven linguistic values, and any rule has three conditions we will need 343 rules. It is too much work to write 343 rules and have lots of problem to design embedded control system e.g., Field Programmable Gate Array (FPGA). In this research the PID-like fuzzy controller can be constructed as a parallel structure of a PD-like fuzzy controller and a conventional PI controller to have the minimum rule base and acceptable trajectory follow disturbance to control of spherical motor. However computed torque controller is work based on cancelling decoupling and nonlinear terms of dynamic parameters for each direction of three degree of freedom spherical motor, this controller is work based on motor dynamic model and this technique is highly sensitive to the knowledge of all parameters of nonlinear spherical motor‟s dynamic equation. This research is used to reduce or eliminate the computed torque controller problem based on minimum rule base fuzzy logic theory to control of three degrees of freedom spherical motor system and testing of the quality of process control in the simulation environment of MATLAB/SIMULINK Simulator. Index Term—PID like fuzzy control, computed torque controller, PD like fuzzy control, conventional PI control, three degrees of freedom spherical motor.

Design Intelligent PID like Fuzzy Sliding Mode Controller for Spherical Motor

The minimum rule base Proportional Integral Derivative (PID) Fuzzy Sliding Mode Controller (SMC) with application to spherical motor is presented in this research. The popularity of PID Fuzzy Sliding Mode Controller can be attributed to their robust performance in a wide range of operating conditions and partly to their functional simplicity. The process of setting of PID Fuzzy Sliding Mode Controller can be determined as an optimization task. Over the years, use of intelligent strategies for tuning of these controllers has been growing especially in nonlinear and uncertain systems. Proportional Integral Derivative methodology has three inputs and if any input is described with seven linguistic values, and any rule has three conditions, we will need 343 rules. It is too much work to write 343 rules and have lots of problem to design embedded control system e.g., Field Programmable Gate Array (FPGA). In this research the PID-like fuzzy controller can be constructed as a parallel structure of a PD-like fuzzy controller and a conventional PI controller to have the minimum rule base and good trajectory follow disturbance to control of spherical motor. However Sliding Mode Controller is work based on cancelling decoupling and nonlinear terms of dynamic parameters for each direction of three degree of freedom spherical motor, this controller is work based on motor dynamic model and this technique is highly sensitive to the knowledge of all parameters of nonlinear spherical motor‟s dynamic equation which caused to challenge in uncertain system. This research is used to reduce or eliminate the Sliding Mode Controller problem based on minimum rule base fuzzy logic theory to control of three degrees of freedom spherical motor system and testing of the quality of process control in the simulation environment of MATLAB/SIMULINK Simulator. Index Term—PID like fuzzy control, Sliding Mode Controller, PD like fuzzy control, conventional PI control, three degrees of freedom spherical motor.

Dynamic Performance Comparison of Cúk Converter with DC Motor Driving and Using PI, PID, Fuzzy Logic Types Controllers

DC-DC converters are widely used in electrical machinery driver circuits. Classic controllers and fuzzy logic controllers, DC converters operating range setting switches provide control of electrical machines drives. In this study, which is one of the Cúk converter DC converters MATLAB / Simulink model was prepared, at the output of a DC Motor Dynamic Model, Proportional Integral, Proportional Integral Derivative and Fuzzy Logic Controllers to be controlled by a speed and a reference was provided and compared with the performances of these controllers.

Control Strategies for AC Motor of Electric Vehicles

Electric Vehicles (EVs) have been the important tendency of future vehicle development. This paper discusses the performance and features of EVs with AC drive system, and analyzes two dominating control schemes of AC motor dynamic model, i.e., Vector Control (VC) and Direct Torque Control (DTC). Principles, advantages, disadvantages, research hot spots and developing directions of the two control schemes were carefully presented. Moreover, the paper points out that the two difficulties of AC drive system are improving low-speed performance and dynamic performance.

Experiment and Dynamic Model of Motor for Rotary-Screw-Driven Dispensing System

Motor plays an important role in the dynamic property of the rotary-screw-driven dispensing system. Dynamic model of the motor was developed and validated in this paper. The output angle displacement and input voltage were measured from photoelectric digital encoder which is used to measure the angle displacement of the motor. In order to realize data smooth processing, Alpha-Beta filter was used. Discrete model of the motor was developed based on the Least Square Method and Model Selection criterion. Computational studies show that the system is equivalent to second order system. Moreover, the model was validated based on the experiment results under the different applied pressure and angular speed of motor. It is revealed that there is a good fit between experiment data and model simulation.

High performance direct torque control schemes for an IPMSM drive

Classical direct torque control (DTC) has several advantages, however, the high torque and flux ripples and variable switching frequency are considered its main drawbacks. In this paper, two techniques are proposed to improve the classical DTC performance of the interior permanent magnet synchronous motor (IPMSM) drive. Firstly, a torque/flux sliding mode controller (SMC) is used to replace the hysteresis comparators and lookup table of the classical DTC. The proposed torque/flux SMC has two integral switching functions for torque and flux control. The idea of total SMC is selected to avoid the reaching phase problem; however, the chattering problem is considered its main drawback. Secondly, to overcome the chattering problem, a torque/flux diagonal recurrent neural network (DRNN) controller is designed to replace the SMC. DRNN has several advantages such as recurrence and simple construction. In addition, a full motor dynamic model and the band of parameters variation are not required. Dynamic off line back-propagation algorithm is used to train the torque/flux DRNN controller. In addition, a space vector modulation (SVM) is combined with the two proposed techniques to provide constant switching frequency and high voltage resolution.The feasibility and effectiveness of the proposed systems have been demonstrated through computer simulations. A comparison between the classical DTC, torque/flux SMC and torque/flux DRNN controller have been made in order to confirm the validity of the proposed schemes. The superiority of the torque/flux DRNN controller has been proved through comparative simulation results.

Motor Fault On-Line Diagnosis Based on Innovation Energy Detection

For the motor current noise signal, vibration signal, the phase current signal, a motor dynamic system model is established. A motor energy detection equation is introduced and constituted by an innovation series of these signal tested in the dynamic system, then the main factor analysis of the motor abnormal elements is presented by orthogonal decomposition, and the main factor distribution chart is described by decomposing the main failure elements to tow-dimensional observation vector. The motor fault can be detected on-line by using the main factor analysis, and then the failure factors can be identified with fault Mode.

Development of the Energy Simulator for the Water Hydraulic System Under Flow Condition Changes

The new energy simulator we developed is based on a hydraulic servosystem dynamic flow model introducing flow coefficients determined by Reynolds number. One is the pipe flow coefficient flow determined by the Moody diagram and the other is the servovalve flow coefficient based on flow model experiments. The motor dynamic model is introduced to determine efficiency such as coil resistance or rotor viscosity loss. Leakage of the hydraulic servovalve was also determined by the leak model. The feasibility of the proposed simulator was verified using computer simulation and experiments, showing differences from conventional simulators that depend on manually set parameters such as flow coefficients. Simulation and experiment results agreed well, and the proposed simulator determines hydraulic servosystem energy consumption. New simulator concepts, calculation models, and experiment results are also discussed.

STEPPER MOTOR SYSTEM IDENTIFICATION USING INVERSE DYNAMIC NEURAL MIMO NARX MODEL

This paper introduces the novel inverse dynamic intelligent MIMO model which is applied for modeling and identifying the stepper motor dynamic model. Hence the highly nonlinear features of stepper motor system are modeled thoroughly based on the inverse neural NARX model identification process using experimental input-output training data. Consequently the proposed inverse neural NARX MIMO model scheme of the nonlinear stepper motor has been investigated. The results showed that the proposed inverse neural NARX MIMO model trained by the back propogation learning algorithm (BP) yields outstanding performance and perfect accuracy.

Research of Motor Fault Diagnosis by Detecting Dynamic Model Parameters

A diagnosis ellipsoid equation is put forward in order to solve motor fault on-line diagnosis. It is first to estimate the motor dynamic model parameters by the on-line least squares estimation, then to detect the parameters changes in the system model, and last to identify t the parts of the system failure occurred and factors. Through a practical example of the application to diagnose a motor fault, the motor fault can be detected according to the parameter changes of the motor model, and the failure factors can be diagnosed by using the diagnosis equation. It is proved feasible and effective.

Inverter Nonlinearity Compensation in the Presence of Current Measurement Errors and Switching Device Parameter Uncertainties

This paper proposes a compensation strategy for the unwanted disturbance voltage due to inverter nonlinearity. We employ an emerging learning technique called support vector regression (SVR). SVR constructs a motor dynamic voltage model by a linear combination of the current samples in real time. The model exhibits fast observer dynamics and robustness to observation noise. Then the disturbance voltage is estimated by subtracting the constructed voltage model from the current controller output. The proposed method compensates for all of the inverter nonlinearity factors at the same time. All the processes in estimating distortions are independent of the dead time and power device parameters. From the analysis of the effect on current measurement errors, we confirmed that the sampling error had little negative impact on the proposed estimation method. Experiments demonstrate the superiority of the proposed method in suppressing voltage distortions caused by inverter nonlinearity

Generation of adaptive gait patterns for quadruped robot with CPG network including motor dynamic model

AbstractThis paper describes the generation of adaptive gait patterns using new Central Pattern Generators (CPGs) including motor dynamic models for a quadruped robot under various environments. The CPGs act as the flexible oscillators of the joints and adjust joint angles to required values. The CPGs are interconnected with each other and sets of their coupling parameters are adjusted by a genetic algorithm so that the quadruped robot can realize stable and adequate gait patterns. Generation of gait patterns results in the formation of the CPG networks suitable for the formation of not only a straight walking pattern but also of rotating gait patterns. Experimental results demonstrate that the proposed CPG networks are effective for the automatic adjustment of the adaptive gait patterns for the tested quadruped robot under various environments. Furthermore, the target tracking control based on image processing is achieved by combining the general gait patterns. © 2006 Wiley Periodicals, Inc. Electr Eng Jpn, 155(1): 35–43, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20225

Load Model Effects on Distance Relay Settings

The purpose of this paper is to study load model effects on distance protective relay settings in Taipower's transmission system. Five load models have been used in order to explore the effects of load characteristics on relay settings: (1) static ZIP model, (2) dynamic motor model, (3) composite model, (4) PTI IEEE model, and (5) exponential model. The major points of this study include (1) setting of impedance values for the three distance protective relay zones and the protection against loss of synchronicity in the outermost periphery, (2) exploring the effects of load models on impedance angles at the time of distance relay tripping, (3) study whether the load model will cause a malfunction in the distance relay when the system swings due to a sudden change in the power system, (4) analyze the coordination of the blocking time of the out-of-step blocking relay during system power swings, and (5) propose how to select a better load model for accuracy in relay settings.

Modelling and Simulation of Variable Speed Thruster Drives with Full-Scale Verification

In this paper considerations about modelling and simulation of variable speed thruster drives are made with comparison to full scale measurements from Varg FPSO. For special purpose vessels with electric propulsion operating in DP (Dynamic Positioning) mode the thruster drives are essential for the vessel operation. Different model strategies of thruster drives are discussed. An advanced thruster drive model with a dynamic motor model and field vector control principle is shown. Simulations are performed with both the advanced model and a simplified model. These are compared with full-scale measurements from Varg FPSO. The simulation results correspond well with the measurements, for both the simplified model and the advanced model.