Towards Efficient Learning-Based Model Predictive Control via Feedback Linearization and Gaussian Process Regression
Jack Caldwell,Joshua A. Marshall,Jack Caldwell,Joshua A. Marshall
This paper presents a learning-based Model Predictive Control (MPC) methodology incorporating nonlinear predictions with robotics applications in mind. In particular, MPC is combined with feedback linearization for computational efficiency and Gaussian Process Regression (GPR) is used to model unknown system dynamics and nonlinearities. In this method, MPC predicts future states by leveraging a GP...
