Abstract: Learning Model Predictive Control (LMPC) is a data-driven approach to MPC that enhances closed-loop performance by leveraging data from successive task iterations to approximate the solution ...

Abstract: Artificial neural networks (ANNs) rely significantly on activation functions for optimal performance. Traditional activation functions such as ReLU and Sigmoid are commonly used. However, ...

This is a preview. Log in through your library . Abstract We define two functions f and g on the unit interval [0, 1] to be strongly conjugate $\operatorname{iff}$ there is an order-preserving ...

This is a preview. Log in through your library . Abstract Many data are suitably modeled by functions consisting of straight-line segments. These functions may be called piecewise-linear. Smooth ...