Abstract. Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of nonlinear dynamic systems. The Gaussian processes can h...
Abstract— This paper presents a generalized Model Predictive Direct Torque Control scheme with an extended horizon, which is composed of multiple hinges (groups of switch transit...
Abstract. In this paper we show how hybrid control and modeling techniques can be put to work for solving a problem of industrial relevance in Surface Mount Technology (SMT) manufa...
Leandro G. Barajas, Ashish Kansal, Abhinav Saxena,...
Abstract. While traditional approaches to machine learning are sensitive to highdimensional state and action spaces, this paper demonstrates how an indirectly encoded neurocontroll...
Context-free approaches to static analysis gain precision over classical approaches by perfectly matching returns to call sites-a property that eliminates spurious interprocedural...