SECTION II: Systems
Richard C. Dorf · 2018
R.D. Harbor, R.G. Jacquot, J.E. McInroy, D.P. Atherton ........................................................... 11-1 12 Navigation Systems M. Kayton .............................................................................................. 12-1 13 Environmental Effects K. Blades, B. Allenby, M.M. Blazek ................................................. 13-1 14 Robotics T.A. Lasky, T.C. Hsia, H.E. Jenkins, M.L. Nagurka, T.R. Kurfess, N.G. Odrey ................................................................................................................................... 14-1 15 Aerospace Systems C.R. Spitzer, D.A. Martinec, C.T. Leondes, V. Tuzlukov, W-S. Yoon, Y.D. Kim ................................................................................................................... 15-1 16 Embedded Systems G. Martin, L. Lavagno, H. Hansson, M. Nolin, T. Nolte, K. Thramboulidis ......................................................................................................................... 16-1 17 Welding and Bonding G.E. Cook, R. Crawford, D.R. DeLapp, A.M. Strauss..................... 17-1 18 Human-Computer Interaction E.P. Rozanski, A.R. Haake................................................. 18-1 19 Decision Diagram Technique S.N. Yanushkevich, V.P. Shmerko ........................................ 19-1 20 Vehicular Systems L.S. Boehmer ............................................................................................ 20-1 William L. Brogan Gordon K.F. Lee Andrew P. Sage Hitay O ¨ zbay Charles L. Phillips Royce D. Harbor Raymond G. Jacquot John E. McInroy Derek P. Atherton A naive trial-and-error approach to the design of a control system might consist of constructing a controller, installing it into the system to be controlled, performing tests, and then modifying the controller until satisfactory performance is achieved. This approach could be dangerous and uneconomical, if not impossible. A more rational approach to control system design uses mathematical models. A model is a mathematical description of system behavior, as influenced by input variables or initial conditions. The model is a stand-in for the actual system during the control system design stage. It is used to predict performance; to carry out stability, sensitivity, and trade-off studies; and answer various ‘‘what-if ’’ questions in a safe and efficient manner. Of course, the validation of the model, and all conclusions derived from it, must ultimately be based upon test results with the physical hardware.