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A Nonlinear Model Predictive Controller (NMPC) for trajectory tracking of surface vessels which takes care of input saturation is designed based on a 3DOF dynamic model. NMPC calculates the future control inputs (propeller speed and rudder angle of the vessel) based on the present state variables by optimizing a cost function. The cost function incorporates input constraints as well as state errors in determining the control inputs is exploited. The identification tests are performed in an outdoor pool on a robotic boat which has an onboard PC104 computer and a navigation sensor. The data from experiments are used to determine the six model parameters. A NMPC is designed based on the identified model to track a sine wave. The performance of the controller is demonstrated through simulations via MATLABs Simulink program and tested on a real robotic boat. The experimental results show for input saturation case the control inputs remain within the saturation limits in extreme maneuvers, the vessel recovers from saturation, and the vessel follows the trajectory very closely when the inputs are not saturated.
About the author
Yaswanth Siramdasu has graduated with a master degree from the University of Alabama in Huntsville in 2012. He is currently a Ph.D student at Virginia Tech working in Center for Tire Research (CenTiRe). His research interests are vehicle dynamics and chassis control systems.
