3 accepted papers
Designing a cost function for nonlinear model predictive control (MPC) with a sparse/binary stage cost is challenging. This paper proposes a novel MPC approach with a scheduled quadratic stage cost function that approximates the true stage cost in order to optimally control a nonlinear system with a…
A letter entitled “Gaussian Process Online Learning With a Sparse Data Stream” suggests an approach for extending the infinite-horizon Gaussian processes (IHGPs, [1]) to deal with a sparse data stream. We point out that there is an error in differentiating the discrete algebraic Riccati equation (DA
Learning the uncertain dynamical environments for online learning and prediction from noisy sensory measurement streams is essential for various tasks in robotics. Recently, Gaussian process (GP) online learning such as an infinite-horizon Gaussian process (IHGP) has shown effectiveness to cope with…