Author Description

<p>Issues such as logistics, the coordination of different teams, and automatic control of machinery become more difficult when dealing with large, complex projects. Yet all these activities have common elements and can be represented by mathematics. Linking theory to practice, Industrial Control Systems: Mathematical and Statistical Models and Techniques presents the mathematical foundation for building and implementing industrial control systems. The book contains mathematically rigorous models and techniques generally applicable to control systems with specific orientation toward industrial systems.</p> <p></p> <p>An amalgamation of theoretical developments, applied formulations, implementation processes, and statistical control, the book covers: </p> <ul> <p> <li>Industrial innovations and systems analysis</li> <li>Systems fundamentals</li> <li>Technical systems</li> <li>Production systems</li> <li>Systems filtering theory</li> <li>Systems control</li> <li>Linear and nonlinear systems</li> <li>Switching in systems</li> <li>Systems communication</li> <li>Transfer systems</li> <li>Statistical experimental design models (factorial design and fractional factorial design)</li> <li>Response surface models (central composite design and Box–Behnken design)</li> <p></p></ul> <p>Examining system fundamentals and advanced topics, the book includes examples that demonstrate how to use the statistical designs to develop feedback controllers and minimum variance controller designs for industrial applications. Clearly detailing concepts and step-by-step procedures, it matches mathematics with practical applications, giving you the tools to achieve system control goals. </p>