A theory of satisficing decisions and control

The existence of an optimal control policy and the techniques for finding it are grounded fundamentally in a global perspective. These techniques can be of limited value when the global behaviour of the system is difficult to characterize, as it may be when the system is nonlinear, when the input is constrained, or when only partial information is available regarding system dynamics or the environment. Satisficing control theory is an alternative approach that is compatible with the limited rationality associated with such systems. This theory is extended by the introduction of the notion of strong satisficing to provide a systematic procedure for the design of satisficing controls. The power of the satisficing approach is illustrated by applications to representative control problems.

[1]  John T. Wen,et al.  Improving the performance of stabilizing controls for nonlinear systems , 1996 .

[2]  K. Glover,et al.  A game theoretic approach to moving horizon control , 1993 .

[3]  James B. Rawlings,et al.  Discrete-time stability with perturbations: application to model predictive control , 1997, Autom..

[4]  Arthur E. Bryson,et al.  Applied Optimal Control , 1969 .

[5]  A. G. Butkovskiy,et al.  Optimal control of systems , 1966 .

[6]  Nak Yong Ko,et al.  A view-time based potential field method for moving obstacle avoidance , 1995, SICE '95. Proceedings of the 34th SICE Annual Conference. International Session Papers.

[7]  J. Mendel.  Fuzzy logic systems for engineering: a tutorial , 1995, Proc. IEEE.

[8]  Shinzo Takatsu,et al.  Characterization of satisficing decision criterion , 1979, Inf. Sci..

[9]  H. Simon,et al.  The sciences of the artificial (3rd ed.) , 1996 .

[10]  Darryl Morrell,et al.  Convex Bayes decision theory , 1991, IEEE Trans. Syst. Man Cybern..

[11]  Shinzo Takatsu,et al.  Latent satisficing decision criterion , 1981, Inf. Sci..

[12]  K. Glover,et al.  Robust performance and adaptation using receding horizon H/sub /spl infin// control of time varying systems , 1995, Proceedings of 1995 American Control Conference - ACC'95.

[13]  W.C. Stirling.  Coordinated intelligent control via epistemic utility theory , 1993, IEEE Control Systems.

[14]  Michael A. Goodrich,et al.  A Theory of Satisficing Control , 1996 .

[15]  D. Mayne,et al.  Moving horizon observers and observer-based control , 1995, IEEE Trans. Autom. Control..

[16]  Huibert Kwakernaak,et al.  Linear Optimal Control Systems , 1972 .

[17]  Yasuhiko Takahara,et al.  On a qualitative theory of satisfactory control , 1972, Inf. Sci..

[18]  H. Michalska,et al.  Receding horizon control of nonlinear systems , 1988, Proceedings of the 28th IEEE Conference on Decision and Control,.

[19]  Pradeep K. Khosla,et al.  Real-time obstacle avoidance using harmonic potential functions , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[20]  H. Simon,et al.  A Behavioral Model of Rational Choice , 1955 .

[21]  Bernard P. Zeigler,et al.  Designing fuzzy net controllers using genetic algorithms , 1995 .

[22]  Wynn C. Stirling,et al.  A satisficing fuzzy logic controller , 1996, Proceedings of IEEE 5th International Fuzzy Systems.

[23]  Zvi Shiller,et al.  Optimal obstacle avoidance based on the Hamilton-Jacobi-Bellman equation , 1994, IEEE Trans. Robotics Autom..

[24]  Herbert A. Simon,et al.  The Sciences of the Artificial , 1970 .

[25]  Donald E. Kirk,et al.  Optimal Control Theory , 1970 .

[26]  Roderic A. Grupen,et al.  The applications of harmonic functions to robotics , 1993, J. Field Robotics.

[27]  Shinzo Takatsu,et al.  Decomposition of satisficing decision problems , 1980, Inf. Sci..

[28]  Philip N. Johnson-Laird,et al.  The computer and the mind - An introduction to cognitive science [Book Review] , 1989, Proceedings of the IEEE.

[29]  B. Wayne Bequette,et al.  Nonlinear model‐predictive control: Closed‐loop stability analysis , 1996 .

[30]  V. I. Utkin,et al.  Sliding mode control for an obstacle avoidance strategy based on an harmonic potential field , 1993, Proceedings of 32nd IEEE Conference on Decision and Control.

[31]  E. Cox,et al.  Fuzzy fundamentals , 1992, IEEE Spectrum.

[32]  O. Hernández-Lerma,et al.  Error bounds for rolling horizon policies in discrete-time Markov control processes , 1990 .

[33]  Isaac Levi,et al.  The Enterprise Of Knowledge , 1980 .

[34]  Shinzo Takatsu,et al.  Algebraic properties of satisficing decision criterion , 1979, Inf. Sci..

[35]  Mihajlo D. Mesarovic.  Systems Theoretic Approach to Formal Theory of Problem Solving , 1970 .

[36]  Isaac Levi,et al.  Decisions and revisions: Truth, fallibility and the growth of knowledge , 1984 .

[37]  J. Richalet,et al.  Industrial applications of model based predictive control , 1993, Autom..