Control Basics for Mechatronics

As a Cambridge Mathematics Scholar, John completed the mathematics tripos in two years, then spent his third year studying electronics. Following a Graduate Apprenticeship, he designed algorithms and electronics for aircraft control systems. He then returned to Cambridge to complete his doctoral research on Predictive Control. He remained in Cambridge as a Fellow of Sidney Sussex College. Eight years later he moved to a Readership at Portsmouth Polytechnic, now Portsmouth University and later became Professor of Robotics. He led groups researching the ‘Craftsman Robot’ and walking robots. He helped found companies designing embedded electronics for domestic appliances and nuclear test equipment. In1992 John moved to Toowoomba, Australia, where he applied machine vision to precision tractor guidance. He co-founded the National Centre for Engineering in Agriculture of the University of Southern Queensland. This year he was joint organiser of the twenty-sixth annual conference on Mechatronics and Machine Vision in Practice, a series which he inaugurated in 1994.

1. Why Do You Need Control Theory? 2. Modelling Time .3. A Simulation Environment 4. Step Length Considerations. 5. Modelling a Second-Order System .6. The Complication of Motor Drive Limits. 7. Practical Controller Design 8. Adding Dynamics to the Controller 9. Sensors and Actuators. 10. Analogue Simulation. 11. Matrix State Equations. 12. Putting It into Practice. 13. Observers 14. More about the Mathematics 15. Transfer Functions 16. Solving the State Equations 17. Discrete Time and the z Operator. 18. Root locus. 19. More about the Phase Plane. 20. Optimisation and an Experiment. 21. Problem Systems. 22. Final Comments.