Neural and Fuzzy Logic Control of Drives and Power Systems*Introduces cutting-edge control systems to a wide readership of engineers and students *The first book on neuro-fuzzy control systems to take a practical, applications-based approach, backed up with worked examples and case studies *Learn to use VHDL in real-world applications Introducing cutting edge control systems through real-world applications Neural networks and fuzzy logic based systems offer a modern control solution to AC machines used in variable speed drives, enabling industry to save costs and increase efficiency by replacing expensive and high-maintenance DC motor systems. The use of fast micros has revolutionised the field with sensorless vector control and direct torque control. This book reflects recent research findings and acts as a useful guide to the new generation of control systems for a wide readership of advanced undergraduate and graduate students, as well as practising engineers. The authors guide readers quickly and concisely through the complex topics of neural networks, fuzzy logic, mathematical modelling of electrical machines, power systems control and VHDL design. Unlike the academic monographs that have previously been published on each of these subjects, this book combines them and is based round case studies of systems analysis, control strategies, design, simulation and implementation. The result is a guide to applied control systems design that will appeal equally to students and professional design engineers. The book can also be used as a unique VHDL design aid, based on real-world power engineering applications. |
Contents
Modern control systems design using CAD techniques | 10 |
Electric motors and power systems | 18 |
Elements of neural control | 56 |
Neural FPGA implementation | 77 |
Fuzzy logic fundamentals | 113 |
VHDL fundamentals | 123 |
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Common terms and phrases
activation function adr_cosy Ai(k algorithm amplitude analogue angular frequency applications architecture ASIC bits block calculated circuit complexity component configuration constant control strategy control system corresponding current control d_in d_out declared defined defuzzification design unit diagram electrical elsif end process engine entity equation error esyn FPGA Fuzzify fuzzy logic fuzzy logic controller fuzzy set hardware implementation Higher-order subneurone hyperplane inductance estimation induction motor input signals interface layer linguistic values load logic gates machine membership functions method modulation MOVLW MOVWF netlist neural network neurone operation optimisation output voltage output_file package parameters performed port power electronic procedure reference frame result rotor speed sampling sensorless simulation sine wave slip angular frequency space vector speed control statement stator current std_logic std_logic_vector(8 downto structure subnetwork subquadrants switching synchronous threshold level torque variable VHDL voltage Voronoi cells Voronoi diagram waveform weights Xilinx
Popular passages
Page 301 - An adaptive current control scheme for PWM synchronous motor drives: analysis and simulation,