Abstract
In this paper, an algorithm for submersible autonomous robotic vehicle (SARV) is proposed using a derivative feedback-based optimal control technique to track the yaw orientation. The optimal control law is obtained by using a linear quadratic regulator (LQR). A linear matrix inequalities (LMI) approach is used to develop a control algorithm and the realization is carried out using semi-definite programming (SDP). An optimal control action is subjected to a derivative controller for smooth tracking of desired yaw. It is found that energy consumption exerted due to the control input is reduced because of the derivative controller. YALMIP toolbox is used to solve the LMI using MATLAB/Simulink in realizing the control law. The simulation results exhibit that the control algorithm is capable of tracking the desired yaw. A difference in tracking of yaw in the presence of derivative feedback and the absence of derivative feedback is clearly shown and discussed. It is also shown that the tracking of desired yaw has a better performance in terms of derivative feedback.
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Vadapalli, S., Mahapatra, S. (2023). State Derivative Optimal Control Law for Submersible Autonomous Robotic Vehicle in Steering Plane. In: Chakraborty, B., Biswas, A., Chakrabarti, A. (eds) Advances in Data Science and Computing Technologies. ADSC 2022. Lecture Notes in Electrical Engineering, vol 1056. Springer, Singapore. https://doi.org/10.1007/978-981-99-3656-4_13
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DOI: https://doi.org/10.1007/978-981-99-3656-4_13
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