Target Tracking by Neural Predictive Control of Autonomous Surface Vessel for Environment Monitoring and Cargo Transportation Applications

The intelligent control of autonomous vehicles has become one of the priority fields in development of Cyber-Physical Systems (CPS). Paper focuses on development of methodology of modeling and simulation of nonlinear system of an Autonomous Surface Vessel (ASV) together with neural predictive control in Simulink/MATLAB software environment. The simulations have been presented for two maneuvers: direct approaching the destination area and circular movement around the target position. Simulation results confirm the high-performance quality of neural predictive control approach. Future practical application of this theoretical study is associated with ASV “Nymo” developed in Tallinn University of Technology for environment monitoring and cargo transportation tasks.