Adaptive critic based neurocontroller for autolanding of aircrafts

Saini, Gurinder; Balakrishnan, S. N.

doi:10.1109/acc.1997.609699

Cited by 24 publications

(3 citation statements)

References 3 publications

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“…An important part of an autopilot is the control of an aircraft's longitudinal dynamics, and the most puzzling work of longitudinal autopilot is the automatic landing task. Many control researchers have developed several methodologies to achieve auto-landing flight control design, including PID (Ebrahimi and Coleman, 2001; Ha and Kim, 2005;Iiguni and Akiyoshi, 1998), LQR (Kim, et al, 2005), intelligent control (Iiguni and Akiyoshi, 1998), neural networks (Izadi, et al, 2003;Jorgenson and Schley, 1990;Juang and Cheng, 2001;Saini and Balakrishnan, 1997), fuzzy logic (Nho and Agarwal, 2000), and H∞ synthesis (Kaminer and Khargonekar, 1990;Li, et al, 2004;Niewoehner and Kaminer, 1996;Ochi and Kanai, 1999;Shue and Agarwal, 1999). Some of the designs of auto-landing used classical control techniques; these are the stability augmentation of the inner loop and the path tracking of the outer loop (Kaminer and Khargonekar, 1990;Jorgenson and Schley, 1990;Iiguni and Akiyoshi, 1998).…”

Section: Introductionmentioning

confidence: 99%

Glidepath Command Generation and Tracking for Longitudinal Autolanding

Tsai

2008

IFAC Proceedings Volumes

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Section: Introductionmentioning

confidence: 99%

Glidepath Command Generation and Tracking for Longitudinal Autolanding

Tsai

2008

IFAC Proceedings Volumes

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“…In our previous study we have used this methodology to solve linear and even nonlinear problems [1] [2][13] [14], some other people have also contributed to this research area [ll]. Although these papers have shown impressive results, so far there is no analysis on the mechanics of the method.…”

Section: Introductionmentioning

confidence: 99%

Convergence analysis of adaptive critic based optimal control

Liu

Balakrishnan

2000

Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334)

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Adaptive critic based neural networks have been found to be powerful tools in solving various optimal control problems. The adaptive critic approach consists of two neural networks which output the control values and the Lagrangian multipliers associated with optimal control. These networks are trained successively and when the outputs of the two networks are mutually consistent and satisfy the differential constraints, the controller network output produces optimal control. In this paper, we analyze the mechanics of convergence of the network solutions. We establish the necessary conditions for the network solutions to converge and show that the converged solution is optimal.

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“…However, in the nonlinear model highly nonlinear modeling errors and unknown parameter errors still exist. In order to deal with the uncertainties, various adaptive control theories are introduced: neural network, parameter adaptation, fuzzy logic, and genetic algorithm [11][12][13][14][15][16]. Saini et al compared adaptive critic based neural networks with the PID controller in the aircraft landing [11].…”

Section: Et Al Constructed a Linear Fractional Model Whichmentioning

confidence: 99%

Constrained Adaptive Backstepping Controller Design for Aircraft Landing in Wind Disturbance and Actuator Stuck

Yoon¹,

Kim²,

Park³

2012

International Journal of Aeronautical and Space Sciences

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An adaptive backstepping controller is designed for the automatic landing of a fixed-wing aircraft. The backstepping control scheme is adopted by using the nonlinear six degree-of-freedom dynamics of the aircraft during the landing phase. The adaptive law is integrated along with the backstepping controller in order to estimate the aircraft modeling errors as well as the external disturbance. The dynamic constraints of the states and the actuator inputs are taken into account in the parameter adaptation. This is done to prevent an aggressive adaptation and to provide reliable control commands. Numerical simulations were performed to verify the performance of the proposed control law for the landing of the aircraft with the presence of gust and actuator stuck.

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Adaptive critic based neurocontroller for autolanding of aircrafts

Cited by 24 publications

References 3 publications

Glidepath Command Generation and Tracking for Longitudinal Autolanding

Glidepath Command Generation and Tracking for Longitudinal Autolanding

Convergence analysis of adaptive critic based optimal control

Constrained Adaptive Backstepping Controller Design for Aircraft Landing in Wind Disturbance and Actuator Stuck

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