Navigation, Control, and Parameter Identification of an Unmanned Submersible

This paper provides an overview of a new autonomous submersible, its existing navigation and control algorithms, and a proposed parameter-adaptive control structure. Design details of an extended Kalman filter, to be used for both state estimation and explicit parameter identification, are presented.

[1]  M. Athans,et al.  Robustness and computational aspects of nonlinear stochastic estimators and regulators , 1977, 1977 IEEE Conference on Decision and Control including the 16th Symposium on Adaptive Processes and A Special Symposium on Fuzzy Set Theory and Applications.

[2]  Jervis J. Gennari,et al.  Naval Research Laboratory Deep Ocean Search and Inspection System. , 1974 .

[3]  Gerald J. Bierman,et al.  Numerical comparison of kalman filter algorithms: Orbit determination case study , 1977, Autom..

[4]  A. Jazwinski Stochastic Processes and Filtering Theory , 1970 .

[5]  M. A. Athans,et al.  The role and use of the stochastic linear-quadratic-Gaussian problem in control system design , 1971 .

[6]  Gerald J. Bierman,et al.  Measurement updating using the U-D factorization , 1975, 1975 IEEE Conference on Decision and Control including the 14th Symposium on Adaptive Processes.

[7]  Michael Athans,et al.  Optimal Control , 1966 .

[8]  Lennart Ljung,et al.  Theory and applications of self-tuning regulators , 1977, Autom..

[9]  Michael Athans,et al.  Gain and phase margin for multiloop LQG regulators , 1976, 1976 IEEE Conference on Decision and Control including the 15th Symposium on Adaptive Processes.

[10]  Karl Johan Åström,et al.  BOOK REVIEW SYSTEM IDENTIFICATION , 1994, Econometric Theory.

[11]  G. Bierman,et al.  Gram-Schmidt algorithms for covariance propagation , 1975, 1975 IEEE Conference on Decision and Control including the 14th Symposium on Adaptive Processes.

[12]  James Thomas Harris,et al.  Theory and Application of Self-Tuning Regulators , 1977 .