PSO BASED TAKAGI-SUGENO FUZZY PID CONTROLLER DESIGN FOR SPEED CONTROL OF PERMANENT MAGNET SYNCHRONOUS MOTOR

A permanent magnet synchronous motor (PMSM) is one kind of popular motor. They are utilized in industrial applications because their abilities included operation at a constant speed, no need for an excitation current, no rotor losses, and small size. In the following paper, a fuzzy evolutionary algorithm is combined with a proportional-integral-derivative (PID) controller to control the speed of a PMSM. In this structure, to overcome the PMSM challenges, including nonlinear nature, cross-coupling, air gap flux, and cogging torque in operation, a Takagi-Sugeno fuzzy logic-PID (TSFL-PID) controller is designed. Additionally, the particle swarm optimization (PSO) algorithm is developed to optimize the membership functions' parameters and rule bases of the fuzzy logic PID controller. For evaluating the proposed controller's performance, the genetic algorithm (GA), as another evolutionary algorithm, is incorporated into the fuzzy PID controller. The results of the speed control of PMSM are compared. The obtained results demonstrate that although both controllers have excellent performance; however, the PSO based TSFL-PID controller indicates more superiority

Control, optimization and monitoring of Portland cement (Pc 42.5) quality at the ball mill

Thesis (Master)--Izmir Institute of Technology, Chemical Engineering, Izmir, 2006Includes bibliographical references (leaves: 77-78)Text in English; Abstract: Turkish and Englishxi, 89 leavesIn this study, artificial neural networks (ANN) and fuzzy logic models were developed to model relationship among cement mill operational parameters. The response variable was weight percentage of product residue on 32-micrometer sieve (or fineness), while the input parameters were revolution percent, falofon percentage, and the elevator amperage (amps), which exhibits elevator charge to the separator. The process data collected from a local plant, Cimenta Cement Factory, in 2004, were used in model construction and testing. First, ANN (Artificial Neural Network) model was constructed. A feed forward network type with one input layer including 3 input parameters, two hidden layer, and one output layer including residue percentage on 32 micrometer sieve as an output parameter was constructed. After testing the model, it was detected that the model.s ability to predict the residue on 32-micrometer sieve (fineness) was successful (Correlation coefficient is 0.92). By detailed analysis of values of parameters of ANN model.s contour plots, Mamdani type fuzzy rule set in the fuzzy model on MatLAB was created. There were three parameters and three levels, and then there were third power of three (27) rules. In this study, we constructed mix of Z type, S type and gaussian type membership functions of the input parameters and response. By help of fuzzy toolbox of MatLAB, the residue percentage on 32-micrometer sieve (fineness) was predicted. Finally, It was found that the model had a correlation coefficient of 0.76. The utility of the ANN and fuzzy models created in this study was in the potential ability of the process engineers to control processing parameters to accomplish the desired cement fineness levels. In the second part of the study, a quantitative procedure for monitoring and evaluating cement milling process performance was described. Some control charts such as CUSUM (Cumulative Sum) and EWMA (Exponentially Weighted Moving Average) charts were used to monitor the cement fineness by using historical data. As a result, it is found that CUSUM and EWMA control charts can be easily used in the cement milling process monitoring in order to detect small shifts in 32-micrometer fineness, percentage by weight, in shorter sampling time interval

Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes

The book documents 25 papers collected from the Special Issue “Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes”, highlighting recent research trends in complex industrial processes. The book aims to stimulate the research field and be of benefit to readers from both academic institutes and industrial sectors

Closed-loop control of product properties in metal forming

Metal forming processes operate in conditions of uncertainty due to parameter variation and imperfect understanding. This uncertainty leads to a degradation of product properties from customer specifications, which can be reduced by the use of closed-loop control. A framework of analysis is presented for understanding closed-loop control in metal forming, allowing an assessment of current and future developments in actuators, sensors and models. This leads to a survey of current and emerging applications across a broad spectrum of metal forming processes, and a discussion of likely developments.Engineering and Physical Sciences Research Council (Grant ID: EP/K018108/1)This is the final version of the article. It first appeared from Elsevier via https://doi.org/10.1016/j.cirp.2016.06.00

Development of the UMAC-based control system with application to 5-axis ultraprecision micromilling machines

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Increasing demands from end users in the fields of optics, defence, automotive, medical, aerospace, etc. for high precision 3D miniaturized components and microstructures from a range of materials have driven the development in micro and nano machining and changed the manufacturing realm. Conventional manufacturing processes such as chemical etching and LIGA are found unfavourable or limited due to production time required and have led mechanical micro machining to grow further. Mechanical micro machining is an ideal method to produce high accuracy micro components and micro milling is the most flexible enabling process and is thus able to generate a wider variety of complex micro components and microstructures. Ultraprecision micromilling machine tools are required so as to meet the accuracy, surface finish and geometrical complexity of components and parts. Typical manufacturing requirements are high dimensional accuracy being better than 1 micron, flatness and roundness better than 50 nm and surface finish ranging between 10 and 50 nm. Manufacture of high precision components and parts require very intricate material removal procedure. There are five key components that include machine tools, cutting tools, material properties, operation variables and environmental conditions, which constitute in manufacturing high quality components and parts. End users assess the performance of a machine tool based on the dimensional accuracy and surface quality of machined parts including the machining time. In this thesis, the emphasis is on the design and development of a control system for a 5-axis bench-type ultraprecision micromilling machine- Ultra-Mill. On the one hand, the developed control system is able to offer high motion and positioning accuracy, dynamic stiffness and thermal stability for motion control, which are essential for achieving the machining accuracy and surface finish desired. On the other hand, the control system is able to undertake in-process inspection and condition monitoring of the machine tool and process. The control of multi-axis precision machines with high-speed and high-accuracy motions and positioning are desirable to manufacture components with high accuracy and complex features to increase productivity and maintain machine stability, etc. The development of the control system has focused on fast, accurate and robust positioning requirements at the machine system design stage. Apart from the mechanical design, the performance of the entire precision systems is greatly dependent on diverse electrical and electronics subsystems, controllers, drive instruments, feedback devices, inspection and monitoring system and software. There are some variables that dynamically alter the system behaviour and sensitivity to disturbance that are not ignorable in the micro and nano machining realm. In this research, a structured framework has been developed and integrated to aid the design and development of the control system. The framework includes critically reviewing the state of the art of ultraprecision machining tools, understanding the control system technologies involved, highlighting the advantages and disadvantages of various control system methods for ultraprecision machines, understanding what is required by end-users and formulating what actually makes a machine tool be an ultraprecision machine particularly from the control system perspective. In the design and development stage, the possession of mechatronic know-how is essential as the design and development of the Ultra-Mill is a multidisciplinary field. Simulation and modelling tool such as Matlab/Simulink is used to model the most suitable control system design. The developed control system was validated through machining trials to observe the achievable accuracy, experiments and testing of subsystems individually (slide system, tooling system, monitoring system, etc.). This thesis has successfully demonstrated the design and development of the control system for a 5-axis ultraprecision machine tool- Ultra-Mill, with high performance characteristics, fast, accurate, precise, etc. for motion and positioning, high dynamic stiffness, robustness and thermal stability, whereby was provided and maintained by the control system

Advances in Computational Intelligence Applications in the Mining Industry

This book captures advancements in the applications of computational intelligence (artificial intelligence, machine learning, etc.) to problems in the mineral and mining industries. The papers present the state of the art in four broad categories: mine operations, mine planning, mine safety, and advances in the sciences, primarily in image processing applications. Authors in the book include both researchers and industry practitioners

Postprocesamiento CAM-ROBOTICA orientado al prototipado y mecanizado en células robotizadas complejas

The main interest of this thesis consists of the study and implementation of postprocessors to adapt the toolpath generated by a Computer Aided Manufacturing (CAM) system to a complex robotic workcell of eight joints, devoted to the rapid prototyping of 3D CAD-defined products. It consists of a 6R industrial manipulator mounted on a linear track and synchronized with a rotary table. To accomplish this main objective, previous work is required. Each task carried out entails a methodology, objective and partial results that complement each other, namely: - It is described the architecture of the workcell in depth, at both displacement and joint-rate levels, for both direct and inverse resolutions. The conditioning of the Jacobian matrix is described as kinetostatic performance index to evaluate the vicinity to singular postures. These ones are analysed from a geometric point of view. - Prior to any machining, the additional external joints require a calibration done in situ, usually in an industrial environment. A novel Non-contact Planar Constraint Calibration method is developed to estimate the external joints configuration parameters by means of a laser displacement sensor. - A first control is originally done by means of a fuzzy inference engine at the displacement level, which is integrated within the postprocessor of the CAM software. - Several Redundancy Resolution Schemes (RRS) at the joint-rate level are compared for the configuration of the postprocessor, dealing not only with the additional joints (intrinsic redundancy) but also with the redundancy due to the symmetry on the milling tool (functional redundancy). - The use of these schemes is optimized by adjusting two performance criterion vectors related to both singularity avoidance and maintenance of a preferred reference posture, as secondary tasks to be done during the path tracking. Two innovative fuzzy inference engines actively adjust the weight of each joint in these tasks.Andrés De La Esperanza, FJ. (2011). Postprocesamiento CAM-ROBOTICA orientado al prototipado y mecanizado en células robotizadas complejas [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/10627Palanci

Modern approaches to control of a multiple hearth furnace in kaolin production

The aim of this thesis is to improve the overall efficiency of the multiple hearth furnace (MHF) in kaolin calcination by developing control strategies which incorporate machine learning based soft sensors to estimate mineralogy related constraints in the control strategy. The objective of the control strategy is to maximize the capacity of the furnace and minimize energy consumption while maintaining the product quality of the calcined kaolin. First, the description of the process of interest is given, highlighting the control strategy currently implemented at the calciner studied in this work. Next, the state of the art on control of calcination furnaces is presented and discussed. Then, the description of the mechanistic model of the MHF, which plays a key role in the testing environment, is provided and an analysis of the MHF dynamic behavior based on the industrial and simulated data is presented. The design of the mineralogy-driven control strategy for the multiple hearth furnace and its implementation in the simulation environment are also outlined. The analysis of the results is then presented. Furthermore, the extensive sampling campaign for testing the soft sensors and the control strategy logic of the industrial MHF is reported, and the results are analyzed and discussed. Finally, an introduction to Model Predictive Control (MPC) is presented, the design of the Linear MPC framework for the MHF in kaolin calcination is described and discussed, and future research is outlined

Advances in CAD/CAM/CAE Technologies

CAD/CAM/CAE technologies find more and more applications in today’s industries, e.g., in the automotive, aerospace, and naval sectors. These technologies increase the productivity of engineers and researchers to a great extent, while at the same time allowing their research activities to achieve higher levels of performance. A number of difficult-to-perform design and manufacturing processes can be simulated using more methodologies available, i.e., experimental work combined with statistical tools (regression analysis, analysis of variance, Taguchi methodology, deep learning), finite element analysis applied early enough at the design cycle, CAD-based tools for design optimizations, CAM-based tools for machining optimizations