Stability analysis and speed control of brushless DC motor based on self-ameliorate soft switching control methods

In recent years, electric vehicles are the large-scale spread of the transportation field has led to the emergence of brushless direct current (DC) motors (BLDCM), which are mostly utilized in electrical vehicle systems. The speed control of a BLDCM is a subsystem, consisting of torque, flux hysteresis comparators, and appropriate switching logic of an inverter. Due to the sudden load torque variation and improper switching pulse, the speed of the BLDCM is not maintained properly. In recent research, the BLDC current control method gives a better way to control the speed of the motor. Also, the rotor position information should be the need for feedback control of the power electronic converters to varying the appropriate pulse width modulation (PWM) of the inverter. The proposed optimization work controls the switching device to manage the power supply BLDCM. In this proposed self-ameliorate soft switching (SASS) system is a simple and effective way for BLDC motor current control technology, a proposed control strategy is intended to stabilize the speed of the BLDCM at different load torque conditions. The proposed SASS system method is analyzing hall-based sensor values continuously. The suggested model is simulated using the MATLAB Simulink tool, and the results reveal that the maximum steady-state error value achieved is 4.2, as well as a speedy recovery of the BLDCM's speed

Advantages of Fuzzy Control While Dealing with Complex/ Unknown Model Dynamics: A Quadcopter Example

Commonly, complex and uncertain plants cannot be faced through well-known linear approaches. Most of the time, complex controllers are needed to attain expected stability and robustness; however, they usually lack a simple design methodology and their actual implementation is difficult (if not impossible). Fuzzy logic control is an intelligent technique which, on its basis, allows the translation from logic statements to a nonlinear mapping. Although it has been proven to effectively deal with complex plants, many recent studies have moved away from the basic premise of linguistic interpretability. In this work, a simple fuzzy controller is designed in a clear way, privileging design easiness and logical consistency of linguistic operators. It is simulated together to a nonlinear model of a quadcopter with added actuators variability, so the robust operation of the controller is also proven. Uneven gain, bandwidth, and time-delay variations are applied among quadcopter’s motors, so the simulations results enclose those characteristics which could be found in reality. As those variations can be related to actuators’ performance, an analysis can be driven in terms of the features which are not commonly included in mathematical models like power electronics drives or electric machinery. These considerations may shorten the gap between simulation and actual implementation of the fuzzy controller. Briefly, this chapter presents a simple fuzzy controller which deals with a quadcopter plant as a first approach to intelligent control

Mathematical Approaches to Modeling, Optimally Designing, and Controlling Electric Machine

Optimal performance of the electric machine/drive system is mandatory to improve the energy consumption and reliability. To achieve this goal, mathematical models of the electric machine/drive system are necessary. Hence, this motivated the editors to instigate the Special Issue “Mathematical Approaches to Modeling, Optimally Designing, and Controlling Electric Machine”, aiming to collect novel publications that push the state-of-the art towards optimal performance for the electric machine/drive system. Seventeen papers have been published in this Special Issue. The published papers focus on several aspects of the electric machine/drive system with respect to the mathematical modelling. Novel optimization methods, control approaches, and comparative analysis for electric drive system based on various electric machines were discussed in the published papers

Precision Control of a Sensorless Brushless Direct Current Motor System

Sensorless control strategies were first suggested well over a decade ago with the aim of reducing the size, weight and unit cost of electrically actuated servo systems. The resulting algorithms have been successfully applied to the induction and synchronous motor families in applications where control of armature speeds above approximately one hundred revolutions per minute is desired. However, sensorless position control remains problematic. This thesis provides an in depth investigation into sensorless motor control strategies for high precision motion control applications. Specifically, methods of achieving control of position and very low speed thresholds are investigated. The developed grey box identification techniques are shown to perform better than their traditional white or black box counterparts. Further, fuzzy model based sliding mode control is implemented and results demonstrate its improved robustness to certain classes of disturbance. Attempts to reject uncertainty within the developed models using the sliding mode are discussed. Novel controllers, which enhance the performance of the sliding mode are presented. Finally, algorithms that achieve control without a primary feedback sensor are successfully demonstrated. Sensorless position control is achieved with resolutions equivalent to those of existing stepper motor technology. The successful control of armature speeds below sixty revolutions per minute is achieved and problems typically associated with motor starting are circumvented.Research Instruments Ltd

Analysis and implimentation of radial basis function neural network for controlling non-linear dynamical systems

PhD ThesisModelling and control of non-linear systems are not easy, which are now being solved by the application of neural networks. Neural networks have been proved to solve these problems as they are described by adjustable parameters which are readily adaptable online. Many types of neural networks have been used and the most common one is the backpropagation algorithm. The algorithm has some disadvantages, such as slow convergence and construction complexity. An alternative neural networks to overcome the limitations associated with the backpropagation algorithm is the Radial Basis Function Network which has been widely used for solving many complex problems. The Radial Basis Function Network is considered in this theses, along with a new adaptive algorithm which has been developed to overcome the problem of the optimum parameter selection. Use of the new algorithm reduces the trial and error of selecting the minimum required number of centres and guarantees the optimum values of the centres, the widths between the centres and the network weights. Computer simulation usmg SimulinklMatlab packages, demonstrated the results of modelling and control of non-linear systems. Moreover, the algorithm is used for selecting the optimum parameters of a non-linear real system 'Brushless DC Motor'. In the laboratory implementation satisfactory results have been achieved, which show that the Radial Basis Function may be used for modelling and on-line control of such real non-linear systems.The Libyan Ministry of Higher Education

High Resolution Vision-Based Servomechanism Using a Dynamic Target with Application to CNC Machines

This dissertation introduces a novel three dimensional vision-based servomechanism with application to real time position control for manufacturing equipment, such as Computer Numerical Control (CNC) machine tools. The proposed system directly observes the multi-dimensional position of a point on the moving tool relative to a fixed ground, thus bypassing the inaccurate kinematic model normally used to convert axis sensor-readings into an estimate of the tool position. A charge-coupled device (CCD camera) is used as the position transducer, which directly measures the current position error of the tool referenced to an absolute coordinate system. Due to the direct-sensing nature of the transducer no geometric error compensation is required. Two new signal processing algorithms, based on a recursive Newton-Raphson optimization routine, are developed to process the input data collected through digital imaging. The algorithms allow simultaneous high-precision position and orientation estimation from single readings. The desired displacement command of the tool in a planar environment is emulated, in one end of the kinematic chain, by an active element or active target pattern on a liquid-crystal display (LCD). On the other end of the kinematic chain the digital camera observes the active target and provides visual feedback information utilized for position control of the tool. Implementation is carried out on an XYθZ stage, which is position with high resolution. The introduction of the camera into the control loop yields a visual servo architecture; the dynamic problems and stability assessment of which are analyzed in depth for the case study of the single CAM- single image processing thread-configuration. Finally, two new command generation protocols are explained for full implementation of the proposed structure in real-time control applications. Command issuing resolutions do not depend upon the size of the smallest element of the grid/display being imaged, but can instead be determined in accordance with the sensor\u27s resolution

Survey of FPGA applications in the period 2000 – 2015 (Technical Report)

Romoth J, Porrmann M, Rückert U. Survey of FPGA applications in the period 2000 – 2015 (Technical Report).; 2017.Since their introduction, FPGAs can be seen in more and more different fields of applications. The key advantage is the combination of software-like flexibility with the performance otherwise common to hardware. Nevertheless, every application field introduces special requirements to the used computational architecture. This paper provides an overview of the different topics FPGAs have been used for in the last 15 years of research and why they have been chosen over other processing units like e.g. CPUs

Performance Improvement of Water Temperature Control using Anti-windup Proportional Integral Derivative

In this research, the controller was implemented in water temperature control system. This system has delay and saturation effect that caused instability problem in system. One of the effects occurred was windup effect. So, the implementation of controller needs to add anti-windup system. This paper described the comparison between 2 methods of controller design, conventional PID method and PID with Anti-Windup method.  The conventional PID method resulted the system that was hardly to achieve the steady state condition. This was caused by windup effect as the system get saturation. The integrator part in PID will get bigger. The solution to fix this instability problem was by using the PID with Anti-Windup. The result of experiment showed that the output response from the control system with the anti-windup PID has a more stable than that of the conventional PI

Mehatronički pristup pozicioniranju ultravisokih preciznosti i točnosti

Ultra-high precision mechatronics positioning systems are critical devices in current precision engineering and micro- and nano-systems’ technologies, as they allow repeatability and accuracy in the nanometric domain to be achieved. The doctoral thesis deals thoroughly with nonlinear stochastic frictional effects that limit the performances of ultra-high precision devices based on sliding and rolling elements. The state-of-the-art related to the frictional behavior in the pre-sliding and sliding motion regimes is considered and different friction models are validated. Due to its comprehensiveness and simplicity, the generalized Maxwell-slip (GMS) friction model is adopted to characterize frictional disturbances of a translational axis of an actual multi-degrees-of-freedom point-to-point mechatronics positioning system aimed at handling and positioning of microparts. The parameters of the GMS model are identified via innovative experimental set-ups, separately for the actuator-gearhead assembly and for the linear guideways, and included in the overall MATLAB/SIMULINK model of the used device. With the aim of compensating frictional effects, the modeled responses of the system are compared to experimental results when the system is controlled by means of a conventional proportional-integral-derivative (PID) controller, when the PID controller is complemented with an additional feed-forward model-based friction compensator and, finally, when the system is controlled via a self-tuning adaptive regulator. The adaptive regulator, implemented within the real-time field programmable gate array based control system, is proven to be the most efficient and is hence used in the final repetitive point-to-point positioning tests. Nanometric-range precision and accuracy (better than 250 nm), both in the case of short-range (micrometric) and long-range (millimeter) travels, are achieved. Different sensors, actuators and other design components, along with other control typologies, are experimentally validated in ultra-high precision positioning applications as well.Mehatronički sustavi ultra-visokih (nanometarskih) preciznosti i točnosti pozicioniranja su u današnje vrijeme vrlo važni u preciznom inženjerstvu i tehnologiji mikro- i nano-sustava. U disertaciji se temeljito analiziraju nelinearni stohastički učinci trenja koji vrlo često ograničavaju radna svojstva sustava za precizno pozicioniranje temeljenih na kliznim i valjnim elementima. Analizira se stanje tehnike za pomake pri silama manjim od sile statičkog trenja, kao i u režimu klizanja, te se vrednuju postojeći matematički modeli trenja. U razmatranom slučaju mehatroničkog sustava ultra-visokih preciznosti i točnosti pozicioniranja, namijenjenog montaži i manipulaciji mikrostruktura, trenje koje se javlja kod linearnih jednoosnih pomaka se, zbog jednostavnosti i sveobuhvatnosti toga pristupa, modelira generaliziranim Maxwell-slip (GMS) modelom trenja. Parametri GMS modela se identificiraju na inovativnim eksperimentalnim postavima, i to posebno za pokretački dio analiziranog sustava, koji se sastoji od istosmjernog motora s reduktorom, te posebno za linearni translator. Rezultirajući modeli trenja se zatim integriraju u cjeloviti model sustava implementiran u MATLAB/SIMULINK okruženju. S ciljem minimizacije utjecaja trenja, modelirani odziv sustava uspoređuje se potom s eksperimentalnim rezultatima dobivenim na sustavu reguliranom pomoću često korištenog proporcionalno-integralno-diferencijalnog (PID) regulatora, kada se sustav regulira po načelu unaprijedne veze, te kada se regulira prilagodljivim upravljačkim algoritmom. Regulator s prilagodljivim vođenjem, implementiran unutar stvarno-vremenskog sustava temeljenog na programibilnim logičkim vratima, pokazao se kao najbolje rješenje te se stoga koristi u uzastopnim eksperimentima pozicioniranja iz točke u točku, koji predstavljaju željenu funkcionalnost razmatranog sustava. Postignute su tako nanometarska preciznost i točnost (bolje od 250 nm) i to kako kod kraćih (mikrometarskih), tako i duljih (milimetarskih) pomaka. U završnom se dijelu disertacije eksperimentalno analizira i mogućnost korištenja drugih pokretača, osjetnika i strojnih elemenata kao i različitih upravljačkih pristupa pogodnih za ostvarivanje ultra-visokih preciznosti i točnosti pozicioniranja