FIGURE 9.7
• SIMULINK*
• SIGNAL PROCESSING
• CONTROL SYSTEM
• CURVE FITTING
• DATA ACQUISITION
• ROBUST CONTROL
• SYSTEM IDENTIFICATION
• OPTIMIZATION
• FUZZY LOGIC*
• NEURAL NETWORK*
• GENETIC ALGORITHM
MATLAB (The MathWorks, Inc.) [2] is an almost universally used piece of software for solving broad engineering problems that relate to various mathematical operations, data analysis, and graphical plots. These include arithmetic and logical operations; integration; differentiation; matrix manipulation; the solving of algebraic, differential, difference, and polynomial equations; Laplace and Fourier analysis and transforms; Z-transforms; regression and curve fitting; and interpolation. MATLAB supports a large number of toolboxes for problem solving. The toolboxes that are important for solving power electronics-related problems are listed in the figure. A toolbox can be defined as a subprogram in the MATLAB environment for solving specialized problems. Simulink is a simulation program with a graphical user interface (GUI). Signal Processing helps analysis of the time- and frequency-domain signals. Control System helps modeling, analysis, and design of control systems. System Identification helps generation of mathematical system models based on I/O data and provides tools for estimation and identification of signals and parameters. Fuzzy Logic, Neural Network, and Genetic Algorithm toolboxes help in the design of intelligent control and estimation of the system. Programs in different toolboxes can be interconnected to build and study a composite system. For example, a neural network designed with the Neural Network toolbox can be embedded in a Simulink-based drive simulation program, and system performance can then be studied. The toolboxes that will be discussed in the topic are indicated by an asterisk (*).