A basic building block approach to CMOS design of analog neuro/fuzzy systems

Outlines a systematic approach to design fuzzy inference systems using analog integrated circuits in standard CMOS VLSI technologies. The proposed circuit building blocks are arranged in a layered neuro/fuzzy architecture composed of 5 layers: fuzzification, T-norm, normalization, consequent, and output. Inference is performed by using Takagi and Sugeno's (1989) IF-THEN rules, particularly where the rule's output contains only a constant term-a singleton. A simple CMOS circuit with tunable bell-like transfer characteristics is used for the fuzzification. The inputs to this circuit are voltages while the outputs are currents. Circuit blocks proposed for the remaining layers operate in the current-mode domain. Innovative circuits are proposed for the T-norm and normalization layers. The other two layers use current mirrors and KCL. All the proposed circuits emphasize simplicity at the circuit level-a prerequisite to increasing system level complexity and operation speed. A 3-input, 4-rule controller has been designed for demonstration purposes in a 1.6 /spl mu/m CMOS single-poly, double-metal technology. We include measurements from prototypes of the membership function block and detailed HSPICE simulations of the whole controller. These results operation speed in the range of 5 MFLIPS (million fuzzy logic inferences per second) with systematic errors below 1%

Regression between headmaster leadership, task load and job satisfaction of special education integration program teacher

Managing school is a daunting task for a headmaster. This responsibility is exacerbated when it involves the Special Education Integration Program (SEIP). This situation requires appropriate and effective leadership in addressing some of the issues that are currently taking place at SEIP such as task load and job satisfaction. This study aimed to identify the influence of headmaster leadership on task load and teacher job satisfaction at SEIP. This quantitative study was conducted by distributing 400 sets of randomized questionnaires to SEIP teachers across Malaysia through google form. The data obtained were then analyzed using Structural Equation Modeling (SEM) and AMOS software. The results show that there is a significant positive effect on the leadership of the headmaster and the task load of the teacher. Likewise, the construct of task load and teacher job satisfaction has a significant positive effect. However, for the construct of headmaster leadership and teacher job satisfaction, there was no significant positive relationship. This finding is very important as a reference to the school administration re-evaluating their leadership so as not to burden SEIP teachers and to give them job satisfaction. In addition, the findings of this study can also serve as a guide for SEIP teachers to increase awareness of the importance of managing their tasks. This study also focused on education leadership in general and more specifically on special education leadership

High performance position control for permanent magnet synchronous drives

In the design and test of electric drive control systems, computer simulations provide a useful way to verify the correctness and efficiency of various schemes and control algorithms before the final system is actually constructed, therefore, development time and associated costs are reduced. Nevertheless, the transition from the simulation stage to the actual implementation has to be as straightforward as possible. This document presents the design and implementation of a position control system for permanent magnet synchronous drives, including a review and comparison of various related works about non-linear control systems applied to this type of machine. The overall electric drive control system is simulated and tested in Proteus VSM software which is able to simulate the interaction between the firmware running on a microcontroller and analogue circuits connected to it. The dsPIC33FJ32MC204 is used as the target processor to implement the control algorithms. The electric drive model is developed using elements existing in the Proteus VSM library. As in any high performance electric drive system, field oriented control is applied to achieve accurate torque control. The complete control system is distributed in three control loops, namely torque, speed and position. A standard PID control system, and a hybrid control system based on fuzzy logic are implemented and tested. The natural variation of motor parameters, such as winding resistance and magnetic flux are also simulated. Comparisons between the two control schemes are carried out for speed and position using different error measurements, such as, integral square error, integral absolute error and root mean squared error. Comparison results show a superior performance of the hybrid fuzzy-logic-based controller when coping with parameter variations, and by reducing torque ripple, but the results are reversed when periodical torque disturbances are present. Finally, the speed controllers are implemented and evaluated physically in a testbed based on a brushless DC motor, with the control algorithms implemented on a dsPIC30F2010. The comparisons carried out for the speed controllers are consistent for both simulation and physical implementation

Fuzzy Controllers

Trying to meet the requirements in the field, present book treats different fuzzy control architectures both in terms of the theoretical design and in terms of comparative validation studies in various applications, numerically simulated or experimentally developed. Through the subject matter and through the inter and multidisciplinary content, this book is addressed mainly to the researchers, doctoral students and students interested in developing new applications of intelligent control, but also to the people who want to become familiar with the control concepts based on fuzzy techniques. Bibliographic resources used to perform the work includes books and articles of present interest in the field, published in prestigious journals and publishing houses, and websites dedicated to various applications of fuzzy control. Its structure and the presented studies include the book in the category of those who make a direct connection between theoretical developments and practical applications, thereby constituting a real support for the specialists in artificial intelligence, modelling and control fields

Simplified fuzzy logic control of sinusoidal permanent magnet synchronous motor drives

Fuzzy Logic Control (FLC) is suitable for a controller design when the system is difficult to model mathematically due to its complexity, nonlinearity and imprecision. It is widely used in high performance drives to obtain precise speed control irrespective of load disturbances and parameter variations. The purpose of this project is to investigate and evaluate speed performance of the FLC in vector controlled Sinusoidal Permanent Magnet Synchronous Motor (SPMSM) drives. The SPMSM is controlled by a vector control technique operating like a separately excited DC motor. The mathematical model of SPMSM drives is simulated using the MATLAB Simulink program. The standard FLC which comprise of 49 rules is initially designed based on common criteria. From investigation on the FLC tuning, two simplified FLCs are designed based on fuzzy rules reduction with systematic and reasonable approaches. The efficacies of the FLC simplification are determined by conducting a comparative analysis between standard FLC and simplified FLCs over a wide range of operating conditions. This is based on simulation approach including various initial step speed commands, load disturbance, step reduction in speed command, inertia variations, and speed reversal operation. The FLCs are developed using the Fuzzy Logic Toolbox in MATLAB. The simulation results show that the simplified FLCs obtain comparable performance with the standard FLC in some cases while in others, they perform better than the standard FLC. The simulation results are further evaluated by an experimental investigation. The FLC, co-ordinate transformation and hysteresis current controllers are implemented in the software using Simulink, Fuzzy logic Toolbox and Real-time interface. The hardware implementation consisting of digital signal processor, voltage source inverter, resolver-to-linear DC converter, current sensors and SPMSM are equipped with a speed resolver. As a result, the simplified FLCs are capable to obtain high performance standards with simple rules, less complex structure, less computation time besides solving the limitation of processor and memory resources

Implementation of a cost-effective fuzzy MPPT controller on the Arduino board

This paper presents the implementation of a fuzzy controller on the Arduino Mega board, for tracking the maximum power point of a photovoltaic (PV) module; using low cost materials. A dc-dc converter that incorporates a driver circuit to control the turning on and offof the Mosfet transistor was designed. The controller was evaluated in a PV system consisting of a 65 W PV module and a 12 V/55Ah battery. The results demonstrate the superiority of the fuzzy controller compared to the traditional P & O algorithm, in terms of efficiency and oscillations around the operating point

Dynamic voltage scaling based on supply current tracking using fuzzy Logic controller

It has been demonstrated that dynamic voltage and frequency scaling (DVFS) leads to a considerable saving in dynamic and static power of a processor. In this paper, we present an adaptive framework that can be used to dynamically adjust supply voltage and frequency of a processor under different application workloads. Voltage scaling decisions are made by a fuzzy logic (FL) block based on variations of the processor's workload. By observing the supply-current of the processor and also its variation rate, the FL block can drive the processor to operate at the lowest possible voltage and also the corresponding minimum frequency, in which a specific application can meet all of its deadlines under time-constrained operation. As the voltage can change at the same time as the workload varies, significant savings in both dynamic and static power are achieved. Simulation results show that our approach outperforms a PID controller under distinct working loads