Nonlinear Optimal Line-Of-Sight Stabilization with Fuzzy Gain-Scheduling
A nonlinear optimal controller with a fuzzy gain
scheduler has been designed and applied to a Line-Of-Sight (LOS)
stabilization system. Use of Linear Quadratic Regulator (LQR)
theory is an optimal and simple manner of solving many control
engineering problems. However, this method cannot be utilized
directly for multigimbal LOS systems since they are nonlinear in
nature. To adapt LQ controllers to nonlinear systems at least a
linearization of the model plant is required. When the linearized
model is only valid within the vicinity of an operating point a gain
scheduler is required. Therefore, a Takagi-Sugeno Fuzzy Inference
System gain scheduler has been implemented, which keeps the
asymptotic stability performance provided by the optimal feedback
gain approach. The simulation results illustrate that the proposed
controller is capable of overcoming disturbances and maintaining a
satisfactory tracking performance.
[1] B. D. O. Anderson, and J. B. Moore, Optimal Control Linear Quadratic
Methods. Prentice Hall, 1990.
[2] J. P. Hespanha, "Lecture Notes on LQG/LQR controller design", 2005.
[3] J. M. Hilkert, "Inertially Stabilized Platform Technology", IEEE Control
Systems Magazine, 2008.
[4] P. J. Kennedy, "Direct Versus Line of Sight (LOS) Stabilization", IEEE
Transactions on Control Systems Technology, Vol. 11, No. 1, 2003.
[5] R. Palm and U. Rehfuess, "Fuzzy Controllers as Gain Scheduling
Approximators", Fuzzy Sets and Systems, Vol. 85, 1997.
[6] L. Sciavicco and B. Siciliano, Modelling and control of robot
manipulators, The McGraw-Hill Companies, Inc, 1996.
[7] K-J. Seong et Al., "The Stabilization Loop Design for a Two-Axis
Gimbal System Using LQG/LTR Controller", SICE-ICASE
International Joint Conference, Busan, Korea, 2006.
[8] S. Skogestad and I. Plostethwaite, Multivariable Feedback Control
Analysis and Design, John Wiley & Sons, 2001, pp. 355-368.
[9] P. Skoglar, "Modeling and control of IR/EO-gimbal for UAV
surveillance applications", Thesis, 2002.
[10] P. Wongkamchang and V. Sangveraphunsir, "Control of Inertial
Stabilization Systems Using Robust Inverse Dynamics Control and
Adaptive Control", Thammasat Int. J. Sc. Tech., Vol. 13, No. 2, 2008.
[11] B. Wu and X. Yu, "Evolutionary Design of Fuzzy Gain Scheduling
Controllers", Proceedings of the Congress on Evolutionary
Computation, 1999.
[1] B. D. O. Anderson, and J. B. Moore, Optimal Control Linear Quadratic
Methods. Prentice Hall, 1990.
[2] J. P. Hespanha, "Lecture Notes on LQG/LQR controller design", 2005.
[3] J. M. Hilkert, "Inertially Stabilized Platform Technology", IEEE Control
Systems Magazine, 2008.
[4] P. J. Kennedy, "Direct Versus Line of Sight (LOS) Stabilization", IEEE
Transactions on Control Systems Technology, Vol. 11, No. 1, 2003.
[5] R. Palm and U. Rehfuess, "Fuzzy Controllers as Gain Scheduling
Approximators", Fuzzy Sets and Systems, Vol. 85, 1997.
[6] L. Sciavicco and B. Siciliano, Modelling and control of robot
manipulators, The McGraw-Hill Companies, Inc, 1996.
[7] K-J. Seong et Al., "The Stabilization Loop Design for a Two-Axis
Gimbal System Using LQG/LTR Controller", SICE-ICASE
International Joint Conference, Busan, Korea, 2006.
[8] S. Skogestad and I. Plostethwaite, Multivariable Feedback Control
Analysis and Design, John Wiley & Sons, 2001, pp. 355-368.
[9] P. Skoglar, "Modeling and control of IR/EO-gimbal for UAV
surveillance applications", Thesis, 2002.
[10] P. Wongkamchang and V. Sangveraphunsir, "Control of Inertial
Stabilization Systems Using Robust Inverse Dynamics Control and
Adaptive Control", Thammasat Int. J. Sc. Tech., Vol. 13, No. 2, 2008.
[11] B. Wu and X. Yu, "Evolutionary Design of Fuzzy Gain Scheduling
Controllers", Proceedings of the Congress on Evolutionary
Computation, 1999.
@article{"International Journal of Information, Control and Computer Sciences:50546", author = "A. Puras Trueba and J. R. Llata García", title = "Nonlinear Optimal Line-Of-Sight Stabilization with Fuzzy Gain-Scheduling", abstract = "A nonlinear optimal controller with a fuzzy gain
scheduler has been designed and applied to a Line-Of-Sight (LOS)
stabilization system. Use of Linear Quadratic Regulator (LQR)
theory is an optimal and simple manner of solving many control
engineering problems. However, this method cannot be utilized
directly for multigimbal LOS systems since they are nonlinear in
nature. To adapt LQ controllers to nonlinear systems at least a
linearization of the model plant is required. When the linearized
model is only valid within the vicinity of an operating point a gain
scheduler is required. Therefore, a Takagi-Sugeno Fuzzy Inference
System gain scheduler has been implemented, which keeps the
asymptotic stability performance provided by the optimal feedback
gain approach. The simulation results illustrate that the proposed
controller is capable of overcoming disturbances and maintaining a
satisfactory tracking performance.", keywords = "Fuzzy Gain-Scheduling, Gimbal, Line-Of-SightStabilization, LQR, Optimal Control", volume = "5", number = "8", pages = "826-8", }