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Robotics 2018, 7(4), 66;

Model-Free Gradient-Based Adaptive Learning Controller for an Unmanned Flexible Wing Aircraft

School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON K1N 6N5, Canada
Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX 76019, USA
Author to whom correspondence should be addressed.
Received: 1 September 2018 / Revised: 19 October 2018 / Accepted: 20 October 2018 / Published: 23 October 2018
(This article belongs to the Special Issue Feature Papers)
PDF [810 KB, uploaded 24 October 2018]


Classical gradient-based approximate dynamic programming approaches provide reliable and fast solution platforms for various optimal control problems. However, their dependence on accurate modeling approaches poses a major concern, where the efficiency of the proposed solutions are severely degraded in the case of uncertain dynamical environments. Herein, a novel online adaptive learning framework is introduced to solve action-dependent dual heuristic dynamic programming problems. The approach does not depend on the dynamical models of the considered systems. Instead, it employs optimization principles to produce model-free control strategies. A policy iteration process is employed to solve the underlying Hamilton–Jacobi–Bellman equation using means of adaptive critics, where a layer of separate actor-critic neural networks is employed along with gradient descent adaptation rules. A Riccati development is introduced and shown to be equivalent to solving the underlying Hamilton–Jacobi–Bellman equation. The proposed approach is applied on the challenging weight shift control problem of a flexible wing aircraft. The continuous nonlinear deformation in the aircraft’s flexible wing leads to various aerodynamic variations at different trim speeds, which makes its auto-pilot control a complicated task. Series of numerical simulations were carried out to demonstrate the effectiveness of the suggested strategy. View Full-Text
Keywords: model-free control; flexible wing aircraft; reinforcement learning; optimal control model-free control; flexible wing aircraft; reinforcement learning; optimal control

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Abouheaf, M.; Gueaieb, W.; Lewis, F. Model-Free Gradient-Based Adaptive Learning Controller for an Unmanned Flexible Wing Aircraft. Robotics 2018, 7, 66.

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