Python and Scilab for Control Systems Engineering

Python and Scilab for Control Systems Engineering is a comprehensive practical guide to modelling, simulating, analysing and designing control systems using open-source computational tools. The book begins with the fundamentals of control systems and progressively develops transfer functions, state-space representations, time-domain analysis, frequency-domain analysis, stability, root locus, controllability, observability, controller design and digital implementation. Python is developed through its scientific computing ecosystem, including NumPy, SciPy, Matplotlib, SymPy, pandas, scikit-learn and the python-control library. Scilab is developed through its programming environment, Control System Toolbox and Xcos graphical modelling and simulation environment. The book follows a complete engineering workflow from problem definition and mathematical modelling through simulation, performance evaluation, controller design, validation, implementation and maintenance. Programming examples, exercises, mini-projects, research problems and detailed solutions make the book suitable for classroom teaching as well as independent study. Applications include robotics, process control, aerospace, automotive systems, power systems, manufacturing, medical devices, digital twins, machine learning and cyber-physical systems. The book is intended for undergraduate and postgraduate students, teachers, researchers and practicing engineers across electrical, electronics, instrumentation, mechanical, mechatronics, robotics and aerospace engineering. It also provides a practical pathway for engineers who wish to explore open-source alternatives to proprietary control-engineering software.