Intelligent Control and Robotics for Mechatronic Systems

This book brings together four contributions spanning that range, from the mathematics of learned control laws through to a surgical manipulator that must place an instrument within a fraction of a millimetre while returning meaningful tactile information to the surgeon. Control and robotics are the two faces of the same mechatronic problem. A controller decides what a machine should do next; a robot is the machine that must do it, in contact with an uncertain world and, increasingly, with people. A shared concern runs through them: intelligence in a mechatronic system is only useful if it can be trusted and executed. The opening chapter develops machine learning for real-time control from first principles and insists throughout that a learned model must satisfy a hard timing deadline, admit a stability argument and sit behind a verified safety filter before it can be deployed. The surgical robotics chapter treats safety architecture and regulatory evidence as engineering requirements rather than afterthoughts. The chapter on symbolic analysis takes the opposite route to the same end, deriving closed-form transfer functions so that behaviour can be understood analytically rather than inferred from simulation output. The book closes on diagnosis, with a review of vibration-based fault diagnosis that is unusually candid about its own field's evaluation practices. Read together, the four chapters describe a discipline in which learning, analysis and mechanism design are complementary rather than competing, each developed in enough depth to be used.