Written in a clear, logical and concise manner, this comprehensive resource provides discussion on essential mathematical tools, required for upgraded system performance. Understanding of basic principles and governing laws is essential to reduce complexity of the system, and this guide offers detailed discussion on analytical and numerical techniques to solve mathematical model equations. Important concepts including nonlinear algebraic equations, initial value ordinary differential equations (ODEs) and boundary value ODEs are discussed in detail. The concepts of optimization methods and sensitivity analysis, which are important from subject point of view, are explained with suitable examples. Numerous problems and MATLAB®/Scilab exercises are interspersed throughout the text. Several case studies involving full details of simulation are offered for better understanding. The accompanying website will host additional MATLAB®/Scilab problems, model question papers, simulation exercises, tutorials and projects. This book will be useful for students of chemical engineering, mechanical engineering, instrumentation engineering and mathematics.
|Publisher:||Cambridge University Press|
|Product dimensions:||7.56(w) x 9.80(h) x 0.63(d)|
About the Author
M. Chidambaram received his Ph.D. from the Indian Institute of Science Bangalore in 1984. He has written five books and published 165 research papers in journals in the field of process control. He served as Director of the National Institute of Technology, Tiruchirappalli during the period 2005-10. Having more than 25 years of teaching experience, he is presently working as a Professor in the Department of Chemical Engineering at the Indian Institute of Technology, Madras. His areas of interest includes Instrumentation and process control, computer control of processes, process analysis and simulation. He previously published the book titled Relay Autotuning for Identification and Control (Cambridge, 2014).
Table of ContentsList of tables; List of figures; Preface; 1. Introduction to mathematical modelling; 2. Model development for simple systems; 3. Model development for complex systems; 4. Analytical solutions of model equations; 5. Numerical solutions of model equations; 6. Modelling and simulation: case studies; 7. Discrimination of mathematical models; 8. Sensitivity analysis; 9. Optimization methods; 10. Simulation using MATLAB®/Scilab; 11. Model based control; References; Index.