Title :
A model-predictive satisficing approach to a nonlinear tracking problem
Author :
Curtis, J. Willard ; Beard, Randal W.
Author_Institution :
Dept. of Electr. & Comput. Eng., Brigham Young Univ., Provo, UT, USA
Abstract :
In this paper we use the recently introduced concept of satisficing decision theory in conjunction with a receding horizon optimization technique to achieve suitable tracking for a nonholonomic robot system. The satisficing approach creates a family of "universal formulas" parameterized by two functions. A model predictive scheme is employed to generate these two functions in a way that minimizes the quadratic cost at the next time step. By always choosing an element of the satisficing set, global stability is guaranteed
Keywords :
decision theory; minimisation; model reference adaptive control systems; nonlinear control systems; optimal control; predictive control; quadratic programming; robots; tracking; global stability; model predictive scheme; model-predictive control; model-predictive satisficing approach; nonholonomic robot; nonholonomic robot system; nonlinear tracking problem; quadratic cost minimization; receding horizon optimization technique; satisficing decision theory; tracking control; universal formulas; Control systems; Cost benefit analysis; Cost function; Decision theory; Lyapunov method; Nonlinear control systems; Nonlinear systems; Predictive models; Robots; Stability;
Conference_Titel :
Decision and Control, 2001. Proceedings of the 40th IEEE Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-7061-9
DOI :
10.1109/.2001.980148
