Design and FPGA Implementation of Variable FIR Filters using the Spectral Parameter Approximation and Time-Domain Approach

This brief present a design and FPGA implementation of variable FIR filters using time domain approach of the spectral parameter approximation (SPA) technique. Farrow structure is used to implement the SPA-based filter. In the design of variable filters first design the practical filters which satisfy the given transition bandwidth, passband ripple, and stopband attenuation specifications and then approximate the coefficients of these filters by the impulse response of the Farrow structure. Least-squares technique is used to approximation problem. Various design and implementation cases with FPGA synthesis results are presented

Digital Filters

The new technology advances provide that a great number of system signals can be easily measured with a low cost. The main problem is that usually only a fraction of the signal is useful for different purposes, for example maintenance, DVD-recorders, computers, electric/electronic circuits, econometric, optimization, etc. Digital filters are the most versatile, practical and effective methods for extracting the information necessary from the signal. They can be dynamic, so they can be automatically or manually adjusted to the external and internal conditions. Presented in this book are the most advanced digital filters including different case studies and the most relevant literature

Design, Development, and Testing of Near-Optimal Satellite Attitude Control Strategies

Advances in space technology and interest toward remote sensing mission have grown in the recent years, requiring the attitude control subsystems of observation satellites to increase their performances in terms of pointing accuracy and on-board implementability. Moreover, an increased interest in small satellite missions and the recent technological developments related to the CubeSats standard have drastically reduced the cost of producing and flying a satellite mission. In this context, the proposed research aims to improve the state of the art for satellite attitude control methodologies by proposing a near-optimal attitude control strategy, simulated in a high-fidelity environment. Two strategies are presented, both are based on the implementation of a direct method, the Inverse Dynamics in the Virtual Domain (IDVD), and a nonlinear programming solver, the Sequential Gradient-Restoration Algorithm (SGRA). The IDVD allows the transcription of the original optimal control problem into an equivalent nonlinear programming problem. SGRA is adopted for the quick determination of near-optimal attitude trajectories. The two optimization criteria considered are the target acquisition time and the maneuver energy associated to the actuation torques. In addition, the development and initial testing of a satellite attitude simulator testbed for on-ground experimentation of attitude, determination, and control methodologies is proposed. The Suspended Satellite Three-Axis Rotation Testbed (START) is a novel low-cost satellite three-axis attitude simulator testbed, it is located at the Aerospace Robotics Testbed Laboratory (ARTLAB). START is mainly composed by a 3D printed base, a single-board computer, a set of actuators, and an electric battery. The suspension system is based on three thin high tensile strength wires allowing a three degrees-of freedom rotation range comparable to the one of air bearing-based floating testbeds, and minimal resistive torque in all the rotations axis. This set up will enable the hardware in-the-loop experimentation of attitude guidance navigation and control strategies. Finally, a set of guidelines to select a solver for the solution of nonlinear programming problems is proposed. With this in mind, a comparison of the convergence performances of commonly used solvers for both unconstrained and constrained nonlinear programming problems is presented. The terms of comparison involve accuracy, convergence rate, and convergence speed. Because of its popularity among research teams in academia and industry, MATLAB is used as common implementation platform for the solvers

Recent Advances in Robust Control

Robust control has been a topic of active research in the last three decades culminating in H_2/H_\infty and \mu design methods followed by research on parametric robustness, initially motivated by Kharitonov's theorem, the extension to non-linear time delay systems, and other more recent methods. The two volumes of Recent Advances in Robust Control give a selective overview of recent theoretical developments and present selected application examples. The volumes comprise 39 contributions covering various theoretical aspects as well as different application areas. The first volume covers selected problems in the theory of robust control and its application to robotic and electromechanical systems. The second volume is dedicated to special topics in robust control and problem specific solutions. Recent Advances in Robust Control will be a valuable reference for those interested in the recent theoretical advances and for researchers working in the broad field of robotics and mechatronics

Design and Control of Electrical Motor Drives

Dear Colleagues, I am very happy to have this Special Issue of the journal Energies on the topic of Design and Control of Electrical Motor Drives published. Electrical motor drives are widely used in the industry, automation, transportation, and home appliances. Indeed, rolling mills, machine tools, high-speed trains, subway systems, elevators, electric vehicles, air conditioners, all depend on electrical motor drives.However, the production of effective and practical motors and drives requires flexibility in the regulation of current, torque, flux, acceleration, position, and speed. Without proper modeling, drive, and control, these motor drive systems cannot function effectively.To address these issues, we need to focus on the design, modeling, drive, and control of different types of motors, such as induction motors, permanent magnet synchronous motors, brushless DC motors, DC motors, synchronous reluctance motors, switched reluctance motors, flux-switching motors, linear motors, and step motors.Therefore, relevant research topics in this field of study include modeling electrical motor drives, both in transient and in steady-state, and designing control methods based on novel control strategies (e.g., PI controllers, fuzzy logic controllers, neural network controllers, predictive controllers, adaptive controllers, nonlinear controllers, etc.), with particular attention to transient responses, load disturbances, fault tolerance, and multi-motor drive techniques. This Special Issue include original contributions regarding recent developments and ideas in motor design, motor drive, and motor control. The topics include motor design, field-oriented control, torque control, reliability improvement, advanced controllers for motor drive systems, DSP-based sensorless motor drive systems, high-performance motor drive systems, high-efficiency motor drive systems, and practical applications of motor drive systems. I want to sincerely thank authors, reviewers, and staff members for their time and efforts. Prof. Dr. Tian-Hua Liu Guest Edito

A study on neural network based system identification with application to heating, ventilating and air conditioning (hvac)system

Recent efforts to incorporate aspects of artificial intelligence into the design and operation of automatic control systems have focused attention on techniques such as fuzzy logic, artificial neural networks, and expert systems. Although LMS algorithm has been considered to be a popular method of system identification but it has been seen in many situations that accurate system identification is not achieved by employing this technique. On the other hand, artificial neural network (ANN) has been chosen as a suitable alternative approach to nonlinear system identification due to its good function approximation capabilities i.e. ANNs are capable of generating complex mapping between input and output spaces. Thus, ANNs can be employed for modeling of complex dynamical systems with reasonable degree of accuracy. The use of computers for direct digital control highlights the recent trend toward more effective and efficient heating, ventilating, and air-conditioning (HVAC) control methodologies. The HVAC field has stressed the importance of self learning in building control systems and has encouraged further studies in the integration of optimal control and other advanced techniques into the formulation of such systems. In this thesis we describe the functional link artificial neural network (FLANN), Multi-Layer Perceptron (MLP) with Back propagation (BP) and MLP with modified BP called the emotional BP and Neuro fuzzy approaches for the HVAC System Identification. The thesis describes different architectures together with learning algorithms to build neural network based nonlinear system identification schemes such as Multi-Layer Perceptron (MLP) neural network, Functional Link Artificial Neural Network (FLANN) and ANFIS structures. In the case of MLP used as an identifier, different structures with regard to hidden layer selection and nodes in each layer have been considered. It may be noted that difficulty lies in choosing the number of hidden layers for achieving a correct topology of MLP neural identifier. To overcome this, in the FLANN identifier hidden layers are not required whereas the input is expanded by using trigonometric polynomials i.e. with cos(nπu) and sin(nπu), for n=0,1,2,…. The above ANN structures MLP, FLANN and Neuro-fuzzy (ANFIS Model) have been extensively studied

Dinamički odziv nove adaptivne modificirane povratne Legendrove neuronske mreže upravljanja sinkronim motorom s permanentnim magnetima za električni skuter

Because an electric scooter driven by permanent magnet synchronous motor (PMSM) servo-driven system has the unknown nonlinearity and the time-varying characteristics, its accurate dynamic model is difficult to establish for the design of the linear controller in whole system. In order to conquer this difficulty and raise robustness, a novel adaptive modified recurrent Legendre neural network (NN) control system, which has fast convergence and provide high accuracy, is proposed to control for PMSM servo-driven electric scooter under the external disturbances and parameter variations in this study. The novel adaptive modified recurrent Legendre NN control system consists of a modified recurrent Legendre NN control with adaptation law and a remunerated control with estimation law. In addition, the online parameter tuning methodology of the modified recurrent Legendre NN control and the estimation law of the remunerated control can be derived by using the Lyapunov stability theorem and the gradient descent method. Furthermore, the modified recurrent Legendre NN with variable learning rate is proposed to raise convergence speed. Finally, comparative studies are demonstrated by experimental results in order to show the effectiveness of the proposed control scheme.S obzirom da električni skuter pogonjen servo sustavom sa sinkroni motor s permanentnim magnetima ima nelinearnu dinamiku i vremenski promjenjive parametre, njegov dinamički model nije jednostavno odrediti u svrhu dizajniranja linearnog regulatora. Kako bi se riješio taj problem te povećala robusnost predložen je sustav upravljanja korištenjem adaptivne modificirane povratne Legendrove neuronske mreže za upravljanje skuterom pogonjenim servo sustavom sa sinkronim motorom uz prisustvo vanjskog poremećaja i promjenjivih parametara. Predloženo upravljanje ima brzu konvergenciju i visoku preciznost. Sustav upravljanja sastoji se od modificirane povratne Legendrove neuronske moreže s adaptivnim zakonom upravljanja i estimacijom. Dodatno, \u27on-line\u27 podešavanje parametara takvog sustava može se dobiti korištenjem Ljapunovljevog teorema o stabilnosti sustava i gradijente metode. Modificirana povratne Legendrove neuronska mreža s promjenjivim vremenom učenja predložena je za povećanje brzine konvergencije. Ispravnost predložene sheme upravljanja provjerena je eksperimentalno

A development study for a short range, low capacity digital microwave link

Includes bibliographical references.A specific request for development of a short-range, low capacity digital microwave transmission system has been received from the South African Dept. Posts and Telecommunications. The aim of this project is to initiate development work by determining the optimum system configuration and modulation technique to meet the design specifications. In addition, it is proposed to develop and construct an I.F. modulator/demodulator module using which simulation tests chosen modulation application may be performed in order to assess the scheme's feasibi1ity in this specific application

Motion design for high speed machines.

The dynamic performance of a programmable manipulator depends on both the motion profile to be followed and the feedback control method used. To improve this performance the manipulator trajectory requires planning at an advanced level and an efficient control method has to be used. The purpose of this study is to investigate high-level trajectory planning and trajectory tracing problems. It is shown that conventional trajectory planning methods where the motion curves are generated using standard mathematical functions are ineffective for general application especially when velocity and acceleration conditions are included. Polynomial functions are shown to be the most versatile for these applications but these can give curves with unexpected oscillations, commonly called meandering. In this study, a new method using polynomials is developed to overcome this disadvantage. A general motion design computer program (MOTDES) is developed which enables the user to produce motion curves for general body motion in a plane. The program is fully interactive and operates within a graphics environment. A planar manipulator is designed and 'constructed to investigate the practical problems of trajectory control particularly when operating at high speeds. Different trajectories are planned using MOTDES and implemented to the manipulator. The precise tracing of a trajectory requires the use of advanced control methods such as adaptive control or learning. In learning control, the inputs of the current cycle are calculated using the experience of the previous circle. The main advantage of learning control over adaptive control is its simplicity. It can be applied more easily in real time for high-speed systems. However, learning algorithms may cause saturation of the driving servo motors after a few learning cycles due to discontinuities being introduced into the command curve. To prevent this saturation problem a new approach involving the filtering of the input command is developed and tested