Abstract
High-precision positioning of two underwater mobile robots is investigated in this work. To achieve good performance in underwater communication, control algorithms are implemented to maintain the position of the receiver robot aligned with that of the transmitter in the presence of measurement noise and process uncertainty. Although recent research works have successfully integrated control algorithms with Extended Kalman Filter (EKF) estimator to track the desired position of the transmitter, other aspects besides the convergence to the equilibrium point such as operational constraints and input constraints were not taken into account within these controllers. Such inability of these control algorithms may degrade the performance of the controlled process. Motivated by the above considerations, a tracking Model Predictive Control (MPC) with an EKF-based estimator is developed to both estimate the process states online and drive the actual system to the desired equilibrium point while meeting input and state constraints. The closed-loop stability and the recursive feasibility of the proposed tracking MPC scheme are rigorously proved. To demonstrate the applicability of the proposed control design, the performance of the tracking MPC with that of the conventional Proportional (P), Proportional Integral Derivative (PID), and Linear Quadratic Regulator (LQR) controllers are compared.
Highlights
I N the past years, a large number of research efforts have been dedicated to developing Optical Wireless Communication (OWC) systems that attain optimal performance
OWC is commonly used in communication systems, keeping the line of sight of the laser beam aligned between the transmitter and receiver is always a challenging task for OWC systems
Motivated by the above consideration, we introduce a Model Predictive Control (MPC) scheme based on Extended Kalman Filter (EKF) for two-dimensional underwater transceiver alignment
Summary
I N the past years, a large number of research efforts have been dedicated to developing Optical Wireless Communication (OWC) systems that attain optimal performance. The development of state estimation and control strategies was significantly undertaken in the past decades to improve and enhance the performance of the PAT systems. These strategies need to account for certain communication system criteria: (a) large range of signal tracking (b) high accuracy (c) fast response (d) simple architecture (e) low cost. An MPC strategy is developed to optimize the path at which the closed-loop state approaches the equilibrium (i.e., the desired angle at which the maximum intensity of the transmitted signal can be received) while satisfying several operational constraints.
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