In this paper, we present the use of optimal estimation and control algorithms to guide and control an autonomous glider to reach a desired target state zone. The optimal estimation technique is based on an Extended Kalman Filter that uses quaternion orientation representation and online calibration techniques in order to enhance the state estimation algorithm. The control scheme is based on a LQR tracker control law that uses a linearized time invariant representation of the plant. The optimal control law guides the glider nonlinear dynamics based on a set of continuous parameterized parabolic reference curves that allows the glider to reach the final state zone in a natural way using low energy consumption.

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