Dynamic System Modelling and Analysis with MATLAB and Python

Dynamic System Modeling & Analysis with MATLAB & Python

A robust introduction to the advanced programming techniques and skills needed for control engineering

In Dynamic System Modeling & Analysis with MATLAB & Python: For Control Engineers, accomplished control engineer Dr. Jongrae Kim delivers an insightful and concise introduction to the advanced programming skills required by control engineers. The book discusses dynamic systems used by satellites, aircraft, autonomous robots, and biomolecular networks. Throughout the text, MATLAB and Python are used to consider various dynamic modeling theories and examples.

The author covers a range of control topics, including attitude dynamics, attitude kinematics, autonomous vehicles, systems biology, optimal estimation, robustness analysis, and stochastic system. An accompanying website includes a solutions manual as well as MATLAB and Python example code.

Dynamic System Modeling & Analysis with MATLAB & Python: For Control Engineers provides readers with a sound starting point to learning programming in the engineering or biology domains. It also offers:

• A thorough introduction to attitude estimation and control, including attitude kinematics and sensors and extended Kalman filters for attitude estimation

• Practical discussions of autonomous vehicles mission planning, including unmanned aerial vehicle path planning and moving target tracking

• Comprehensive explorations of biological network modeling, including bio-molecular networks and stochastic modeling

• In-depth examinations of control algorithms using biomolecular networks, including implementation

Dynamic System Modeling & Analysis with MATLAB & Python: For Control Engineers is an indispensable resource for advanced undergraduate and graduate students seeking practical programming instruction for dynamic system modeling and analysis using control theory.

Auteur

Jongrae Kim, PhD, is Associate Professor at the Institute of Design, Robotics & Optimization (iDRO), School of Mechanical Engineering, University of Leeds in the United Kingdom. He obtained his doctorate from the Department of Aerospace Engineering at Texas A&M University in the United States in 2002.