We present differentiable predictive control (DPC) as a deep learning-based alternative to
the explicit model predictive control (MPC) for unknown nonlinear systems. In the DPC …

In this paper, a quantum trapezium-type inequality using a new class of function, the so-
called generalized ϕ-convex function, is presented. A new quantum trapezium-type …

Die effiziente Lösung von Optimierungsproblemen in Echtzeit bildet die Grundlage vieler
moderner Regelungs-und Schätzverfahren. So basieren die prädiktive Regelung sowie die …

In this paper, the study is focused on the quantum estimates of Ostrowski type inequalities
for q-differentiable functions involving the special function introduced by RK Raina which …

We propose to reduce the complexity of explicit MPC controllers by removing regions that
will never be reached during the closed-loop evolution from a given set of initial conditions …

We study the expressibility and learnability of solution functions of convex optimization and
their multi-layer architectural extension. The main results are:(1) the class of solution …

In this work, a study is conducted on the Hermite–Hadamard inequality using a class of
generalized convex functions that involves a generalized and parametrized class of special …

This work extends the theory of reciprocal diagrams in graphic statics to frameworks that are
invariant under finite group actions by utilizing the homology and representation theory of …

In 1864, JC Maxwell introduced a link between self-stressed frameworks in the plane and
piecewise linear liftings to 3-space. This connection has found numerous applications in …

Parametric convex programming has received a lot of attention, since it has many
applications in chemical engineering, control engineering, signal processing, etc. Further …