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The current paper presents an inclusive survey about the AC to DC and DC to DC converters for brushed DC Motor Drives. An essential number of different AC to DC and DC to DC topologies and control techniques, applied on the brushed DC motor drives are presented. This extensive literature review exposes advantages, disadvantages and limitations besides giving the basic operating principles of various topologies and control techniques.

A novelGlobal Chassis Control(GCC) system based on a multilayer architecture with three levels: top: decision layer, middle: control layer, and bottom: system layer is presented. The main contribution of this work is the development of a data-based classification and coordination algorithm, into a single control problem. Based on a clustering technique, the decision layer classifies the current driving condition. Afterwards, heuristic rules are used to coordinate the performance of the considered vehicle subsystems (suspension, steering, and braking) using local controllers hosted in the control layer. The control allocation system uses fuzzy logic controllers. The performance of the proposed GCC system was evaluated under different standard tests. Simulation results illustrate the effectiveness of the proposed system compared to an uncontrolled vehicle and a vehicle with a noncoordinated control. The proposed system decreases by 14% the braking distance in the hard braking test with respect to the uncontrolled vehicle, the roll and yaw movements are reduced by 10% and 12%, respectively, in the Double Line Change test, and the oscillations caused by load transfer are reduced by 7% in a cornering situation.

The work presented herein illustrates the use of computational intelligence and optimization approaches for improving the fuzzy controller's performance in architectural heating, ventilation, and air conditioning system (HVAC). The primary purpose of the performed research is to find a method to moderate the energy use without compromising the comforts of the inhabitants. The control design used to meet this purpose includes the predicted mean vote (PMV) and predicted percentage dissatisfied (PPD) indices. The software of choice for evaluating PMV and PPD is EnergyPlus. Whereas, for the fuzzy controller and the evolutionary optimization framework, the co-simulation tool with building controls virtual test bed (BCVTB) is used in conjunction with Simulink. The ensuing comparison between EnergyPlus's thermal control of HVAC and our fuzzy approach is the outcome of the present research. NPRP Grant# (NPRP 5-209-2-071) from the Qatar National Research Fund (a member of Qatar Foundation). Scopus

In recent years, Multi-Objective Evolutionary Algorithms (MOEAS) that consider diversity as an objective have been used to tackle single-objective optimisation prob- lems. The ability to deal with premature convergence has been greatly improved with these schemes. However, they usually increase the number of free parameters that need to be tuned. To improve results and avoid the tedious hand- tuning of algorithms, the use of automated parameter con- trol approaches that are able to adapt parameter values dur- ing the course of an evolutionary run are becoming more common in the field of Evolutionary Computation (EC). This research focuses on the application of parameter control approaches to diversity-based moeas. Two external parame- ter control methods are investigated; a novel method based on Fuzzy Logic and a recently proposed Hyper-heuristic. These are compared to an internal control method that uses self- adaptation. An extensive comparison of the three methods is carried out using a set of single-objective benchmark prob- lems of diverse complexity. Analyses include comparisons to a wide range of schemes with fixed parameters and to a single-objective approach. The results show that the fuzzy logic and hyper-heuristic methods are able to find similar or better solutions than the fixed parameter methods for a sig- nificant number of problems, with considerable savings in computational resources and time, whereas the self-adaptive strategy provides little benefit. Finally, we also demonstrate that the controlled diversity-based moea outperforms the single-objective scheme in most cases, thus showing the ben- efits of solving single-objective problems through diversity-based multi-objective schemes.

Building management system (BMS) has the ability to monitor and control buildings’ mechanical and electrical equipment including namely heating, ventilating and air conditioning (HVAC), lighting, power, fire and security systems. BMS can also provide indoor thermal comfort within commercial buildings including industrial and institutional buildings and able to reduce energy consumption. However most of HVAC systems are controlled by using conventional controller whose functions are based on ON/OFF controller and Proportional-Integral-Derivative (PID) controllers. These controllers are not the ultimate solution to save energy because the operations of HVAC systems are nonlinear. Thus, the implementation of fuzzy logic controllers within smart buildings will be more efficient which consequently will save more energy and money. This paper reviews, investigates and evaluates the use of fuzzy logic controller in HVAC systems and light controllers for smart buildings in subtropical Australia. Additionally, it highlights the recent developments in BMS controllers including its conceptual basis, capabilities and limitations.

The aim of this paper is to propose an effective technique which employs a proportional-integral Fuzzy logic controller for the thrust regulation of small scale turbojet engines, capable of ensuring high performance in terms of response speed, precision and stability. Fuzzy rules have been chosen by logical deduction and some specific parameters of the closed loop control have been optimized using a numerical simulator, so as to achieve rapidity and stability of response, as well as absence of overshoots. The proposed Fuzzy logic controller has been tested on the Pegasus MK3 microturbine: the high response speed and precision of the proposed thrust control, revealed by the simulations, have been confirmed by several experimental tests with step response. Its stability has been demonstrated by means of the frequency response analysis of the system. The proposed thrust control technique has general validity and can be applied to any small-scale turbojet engine, as well as to microturbines for electricity production, provided that thrust being substituted with the net mechanical power.

Nowadays fuzzy logic controllers have been successfully applied to a wide range of engineering control processes. Several tasks have to be performed in order to design an intelligent control system of this kind for a concrete application. One of the most important and difficult ones is the extraction of the expert known knowledge of the controlled system. The aim of this paper is to present an evolutionary process based on genetic algorithms and evolution strategies for learning the fuzzy-logic-controller knowledge base from examples in three different stages. The process allows us to generate two different kinds of knowledge bases, descriptive and approximate ones, depending on the scope of the fuzzy sets giving meaning to the fuzzy-control-rule linguistic terms, taking preliminary linguistic-variable fuzzy partitions as a base. The performance of the method proposed is shown by measuring the accuracy of the fuzzy logic controllers designed in the fuzzy modeling of three three-dimensional surfaces presenting different characteristics, and by comparing them with others generated by means of three methods based on Wang and Mendel's knowledge-base generation process.

Fuzzy Logic Controllers are a specific model of Fuzzy Rule Based Systems suitable for engineering applications for which classic control strategies do not achieve good results or for when it is too difficult to obtain a mathematical model. Recently, the International Electrotechnical Commission has published a standard for fuzzy control programming in part 7 of the IEC 61131 norm in order to offer a well defined common understanding of the basic means with which to integrate fuzzy control applications in control systems. In this paper, we introduce an open source Java library called jFuzzyLogic which offers a fully functional and complete implementation of a fuzzy inference system according to this standard, providing a programming interface and Eclipse plugin to easily write and test code for fuzzy control applications. A case study is given to illustrate the use of jFuzzyLogic., McGill Uninversity, Genome Quebec, Spanish Government TIN2011-28488, Andalusian Government P10-TIC-6858

The paper proposes two novel approaches for the simplification of multi-input fuzzy logic controllers (FLCs). By these approaches either a hierarchical or parallel structure is derived for a multi-input FLC, leading to the implementation of faster controllers with reduced memory demand. Both these features can be profitably used in the realisation of hardware and software effective fuzzy logic controllers for the industrial field applications. Experimental tests and comparative considerations are also included in the paper. >

The present paper describes the design of a hybrid actuation control concept, a fuzzy logic proportional-integral-derivative plus a conventional on-off controller, for a new morphing mechanism using smart materials as actuators, which were made from shape memory alloys (SMA). The research work described here was developed for the open loop phase of a morphing wing system, whose primary goal was to reduce the wing drag by delaying the transition (from laminar to fully turbulent flows) position toward the wing trailing edge. The designed controller drives the actuation system equipped with SMA actuators to modify the flexible upper wing skin surface. The designed controller was also included, as an internal loop, in the closed loop architecture of the morphing wing system, based on the pressure information received from the flexible skin mounted pressure sensors and on the estimation of the transition location.The controller’s purposes were established following a comprehensive presentation of the morphing wing system architecture and requirements. The strong nonlinearities of the SMA actuators’ characteristics and the system requirements led to the choice of a hybrid controller architecture as a combination of a bi-positional on-off controller and a fuzzy logic controller (FLC). In the chosen architecture, the controller would behave as a switch between the SMA cooling and heating phases, situations where the output current is 0A or is controlled by the FLC.In the design phase, a proportional-integral-derivative scheme was chosen for the FLC. The input-output mapping of the fuzzy model was designed, taking account of the system’s error and its change in error, and a final architecture for the hybrid controller was obtained. The shapes chosen for the inputs’ membership functions were s -function, π-function, and z -function, and product fuzzy inference and the center average defuzzifier were applied (Sugeno).