Applied Control Systems

Modeling + state space systems + Model Predictive Control + feedback control + Python simulation: UAV quadcopter drone

Control of Dynamic Systems in Discrete time programmed in Arduino IDE

Modelling + state space system + PID + Model Predictive Control + Python simulation: lateral control for autonomous cars

The primary emphasis of this book is the modeling, analysis, and control of mechanical systems. The methods and results presented can be applied to a large class of mechanical control systems, including applications in robotics, autonomous vehicle control, and multi-body systems. The book is unique in that it presents a unified, rather than an inclusive, treatment of control theory for mechanical systems. A distinctive feature of the presentation is its reliance on techniques from differential and Riemannian geometry.

The primary emphasis of this book is the modeling, analysis, and control of mechanical systems. The methods and results presented can be applied to a large class of mechanical control systems, including applications in robotics, autonomous vehicle control, and multi-body systems. The book is unique in that it presents a unified, rather than an inclusive, treatment of control theory for mechanical systems. A distinctive feature of the presentation is its reliance on techniques from differential and Riemannian geometry.

Although framework technology has proven its worth as a software reuse technique in many domains, there have been reservations regarding its application in embedded systems, mostly due to limited CPU and memory resources. Recent hardware advances, however, have changed this picture.