论文信息 - UTILIZING PRIOR KNOWLEDGE IN ROBUST OPTIMAL EXPERIMENT DESIGN

UTILIZING PRIOR KNOWLEDGE IN ROBUST OPTIMAL EXPERIMENT DESIGN

Abstract In this paper we propose a new approach to robust optimal experiment design. The key departure from earlier work is that we specifically account for the fact that, prior to the experiment, we possess only partial knowledge of the system. We also give a detailed analysis of the solution for a simple case and propose a concave optimization algorithm that can be applied more generally.

[1] S. Arimoto,et al. Optimum input test signals for system identification—an information-theoretical approach , 1971 .

[2] G. Goodwin,et al. Optimal test signal design for linear S.I.S.O. system identification , 1973 .

[3] Martin B. Zarrop,et al. Optimal experiment design for dynamic system identification , 1977 .

[4] D. B. Reid. Optimal inputs for system identification , 1972 .

[5] V. Levadi. Design of input signals for parameter estimation , 1966 .

[6] R. Mehra. Optimal inputs for linear system identification , 1974 .

[7] W. J. Studden,et al. Theory Of Optimal Experiments , 1972 .

[8] A. Wald. On the Efficient Design of Statistical Investigations , 1943 .

[9] W. J. Studden,et al. Optimal Experimental Designs , 1966 .

[10] P. Whittle. Some General Points in the Theory of Optimal Experimental Design , 1973 .

[11] J. Kiefer,et al. The Equivalence of Two Extremum Problems , 1960, Canadian Journal of Mathematics.

[12] David R. Cox. Planning of Experiments , 1958 .

[13] Håkan Hjalmarsson,et al. From experiment design to closed-loop control , 2005, Autom..

[14] H. Wynn. Results in the Theory and Construction of D‐Optimum Experimental Designs , 1972 .