A novel approach for the optimal control of autonomous underwater vehicles

• Autorzy: Yim S. , Oh J.

Warianty tytułu

PL

Nowe podejście do sterowania optymalnego autonomicznych pojazdów podwodnych

• Języki publikacji: EN

Abstrakty

EN

The SDRE (State-Dependent Riccati Equation) is a technique recently proposed as a nonlinear control method. Despite the benefits due to its flexibility, the SDRE places high demand on the computational load of real-time applications, which is one of its most important drawbacks. This paper discusses a new nonlinear feedback controller for autonomous underwater vehicles (AUVs), which eventually converges to a conventional SDRE-based optimal controller. The proposed controller is derived by direct forward integration of an SDRE. This enables fast computation and so is applicable to real-time situations. For a state-dependent system, the proposed controller may be an alternative candidate to a conventional SDRE-based optimal controller if the system is slow-varying to different states. To cope with fast-varying systems, we introduced a deviation index, which indicates the extent of deviation of the proposed controller from the solution of a conventional SDRE-based one. Whenever the index exceeds a designated bound, the controller is initialised to the conventional SDRE optimal value. Using the deviation index, a designer can achieve a compromise between computation time and optimality. We applied the proposed controller to a numerical model of an AUV called ODIN, a well-known nonlinear, relatively high order, and slow-varying system. The global position/attitude regulation, tracking problems, and fault tolerance properties were examined in the simulation to show the effectiveness of the proposed controller.

PL

Technika SDRE (równania Riccatiego zależnego od stanu) została ostatnio zaproponowana do celów syntezy sterowania nieliniowego. Niezależnie od swoich zalet, związanych z elastycznością, technika SDRE pociąga za sobą wysoki nakład obliczeniowy, co, zwłaszcza w przypadku zastosowań czasu rzeczywistego, stanowi poważne obciążenie. W artykule rozważono nowy rodzaj sterowania nieliniowego w pętli sprzężenia zwrotnego dla autonomicznych pojazdów podwodnych (AUV), które zbiega do konwencjonalnego sterowania opartego na SDRE. Sterowanie to jest wyprowadzone poprzez bezpośrednie całkowanie SDRE. Pozwala to na szybkie dokonywanie obliczeń i może być stosowane w czasie rzeczywistym. W układach zależnych od stanu zaproponowane sterowanie może być alternatywą do konwencjonalnych rozwiązań opartych na SDRE jeśli układ jest wolno zmienny w stosunku do stanów. Aby rozszerzyć zastosowanie na układy szybko zmienne, wprowadza się wskaźnik pokazujący rozbieżność między zaproponowanym sterowaniem a rozwiązaniem konwencjonalnego sterowania opartego na SDRE. Wtedy, gdy wskaźnik ten przekracza założoną wielkość progową, sterowanie jest inicjalizowane zgodnie z optymalna wartością według SDRE. Posługując się wartościami zaproponowanego wskaźnika projektant może osiągać kompromis między czasem obliczeń a stopniem optymalności. Zastosowano nową metodę do modelu numerycznego AUV o nazwie ODIN, który jest reprezentowany przez nieliniowy, wolno zmienny układ wysokiego rzędu. W trakcie symulacji, w celu pokazania efektywności zaproponowanego sterowania zbadano takie aspekty jak regulacja co do położenia i kierunku, nadążanie oraz odporność na błędy.

Słowa kluczowe

EN

SDRE; AUV; optimal control

PL

AUV; SDRE; równanie Riccatiego zależne od stanu; sterowanie optymalne; pojazd podwodny autonomiczny

• Wydawca: Systems Research Institute, Polish Academy of Sciences
• Czasopismo: Control and Cybernetics
• Rocznik: 2003
• Tom: Vol. 32, no 1
• Strony: 127--146
• Opis fizyczny: Bibliogr. 32 poz.

Twórcy

autor

Yim S.

• Machine Control Laboratory, Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Kusong-Dong, YusungGu, Taejeon 305-701, South Korea/Korea Płd

autor

Oh J.

• Machine Control Laboratory, Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Kusong-Dong, YusungGu, Taejeon 305-701, South Korea/Korea Płd

Bibliografia

• ANTONELLI G. , CACCAVA LE F ., CHIAVERINI S. and Fusco G. (2001) A novel adaptive control law for autonomous underwater vehicles. Proc ee dings of the 2001 IEEE International Conference of Robotics f3 Automation, 447-452 .
• ANTONELLI G., CHIAVERINI S., SARKAR N. and WEST M. (1999) Adaptive control of an autonomous underwater vehicles. Experimenta l results on ODIN. Computational Intelligence in Robotics and Automation , Proceedings. 1999 IEEE International Symposium, 64- 69.
• BOSKOVIC D.M. and KRSTIC M. (1999) Global attitude/position regulation for underwater vehicles. International Journal of Systems Science, 3, (9) , 939-946.
• CALLIER F.M., WINKIN J. and WILLEMS J.L. (1994) Convergence of the time-invariant Riccati differential equation and LQ-problem: mechanisms of attraction . International Journal of Control, 59, ( 4), 983- 1000.
• CHOI S.K. , YUH J .K. and TAKASHIGE G.Y. (1995) Development of the omni-directional intelligent navigator. IEEE Robotics and Automation Magazine, 44-53.
• CLOUTIER J.R. and ZIPFEL P.H. (1999) Hypersonic guidance via the state-dependent Riccati equation control method. IEEE International Conference on Control Applications, 219-223.
• FJELLSTAD O.E. and FOSSEN H.l . (1994) Position and attitude tracking of AUV s: A quaternion feedback approach. IEEE Journal of Oceanic Engineering, 19, (4) 512- 518.
• HAESSIG D. and FRIEDLAND B. (1997) A method for simultaneous state and param e ter estimation in nonlinear systems. Proceedings of the American Control Conference, 947-951.
• HAMMETT K.D., HALL C .D. and RIDGELY D. B . (1998) Controllability issues in nonlinear state-dependent Riccati equation control. Journal of Guidance, Control, and Dynamics, 21, (5) 767- 773.
• HAYASE M., YAMAZAKI Y. and RIJANTO E. (200 0) Nonlinear optimal control: Principle of local optimality. Industrial Technology 2000. Proceedings of IEEE International Conference, 2, 202- 20 5.
• HEALEY A.J . and LIENARD D. (1993) Multivariable sliding-mode control for autonomous diving and steering of unman ned underwater vehicles. IEEE Journal of Oceanic Engin eering, 18, (3) 327- 339.
• HULL R.A., CLOUTIER J.R., MRACEK C .P . and STANSBERY D.T . (1998) State dependent Riccati equation solution of the toy nonli near optimal control problem. Proceedings of the American Control Conference, 1658-1663.
• ISHII K., Fum T. and URA T. (1998) Neural network system for on-line controller adaptation and its app lication to underwater robot. Proceedings of 1998 IEEE Internati onal Conference on Robotics and Automation, 756-761.
• JAZWINSKI A.H. (1965) Qua dr atic and higher-order feedback gains for control of nonlinear systems. AIAA Journal, 3, 925- 935.
• KATEBI M.R. and GR IM BLE M.J. (1999) Integrated control, guidance and diagnosis for reconfigurable autonomous underwater vehicle control. International Journal of Systems Science, 30, (9), 1021- 1032.
• LANGSON W. and ALLEYNE A. (1997) Infinit e horizon optimal control of a class of nonlinear systems. Proceedings of the American Control Conference , 3017- 3022.
• LANGSON W. and ALLEYNE A. (1999) A stability result with application to nonlinear regulation: The ory and experiments. Proceedings of the American Control Conference, 3051- 3056.
• McCAFFREY D. and BANKS S.P. (2001) Lagrangian manifolds and asymptotically optimal stabilizing feedback control. Systems f3 Control Letters, 43, (3) 219- 224.
• McLAINT W . and BEARD R.W. (1998) Successive galerkin approximations to the nonlinear optima l cont rol of an underwa ter robotic vehicle. Proceedings of the 1998 IEEE International conference on Robotics and Automation, 762- 767.
• MRACEK C.P. and CLOUT IER J .R. (1998) Control designs for the nonlinear benchmark problem via the state-dependent Riccati equation method. International Journal of Robust and Nonlinear Control, 8, 401 - 433.
• PARK J.H ., CHUNG W.K . and YUH J.K. (2000) Nonlinear Optimal PID Control of autonomous underwater vehicles. Underwater Technology, 2000. UT 00. Proceedings of the 2000 International Symposium, 193- 198.
• PONDERT .K. and SARK AR N. (1999) Fault tolerant decomposition of thruster forces of an autonom ous underwater vehicle. Proceedings of the 1999 IEEE Optimal control of autonomous underwater ve hicles 145
• REID W.T. (1970) Monotoneity properties of solutions of Hermitian Riccati matrix differential equations. SIAM Journal of Mathematical Analysis, 1, (2) 195- 213.
• RODRIGUES 1., TAVARES P. and PRADO M . (1996) Sliding mode control of an AUV in the diving and steering planes. Oceans '96, MTS/ IEEE Prospects for the 21st Century. Conference Proceedings, 2, 576- 583.
• RusNAK I. (1998) Closed-form solution for the Ka lman filter gains of time-varying systems. IEEE Transaction on Aerospace and Electronic systems, 34, (2) 635- 639.
• SERRANI A. and ZANOLI S.M. (1998) Designing guidance and control schemes for AUVs using an integrated simulation environment. Proc ee dings of the 1998 IEEE International Conference on Control Applications, 1079- 1083.
• SHAMMA J.S. and C LOUTIER J.R .. (2001) Existence of SDRE Stabilizing Feedback. Proceedings of the American Control Conference 2001, 4253- 4257.
• SILVERMAN L.M. and ANDERSON B.D.O. (1968) Controllability, observability and stability of linear systems. SIAM Journal of Control, 6, (1) 121- 130.
• WONHAM W . M. (1968) On a matrix Riccati equation of stochastic control. SIAM Journal of Control, 6 , (4) 681 - 697.
• YOERGER D.R. and SLOTINE J. J.E . (1990) Robust trajectory control of underwater vehicles. IEEE Journal of Oceanic Engineering, 10, ( 4) 462-470.
• YUH J .K. (1994) Learning control of underwater robotic vehicles. IEEE control System Magazine, 15 , (2) 39--46 .
• YUH J .K. (1995) A learning control system for unmanned underwater vehicles. Oceans '9 5. MTS/IEEE. Challenges of our Changing Global Environment . Conference Proceedings, 2, 1029- 1032.