This paper presents a constraint aggregation approach for Nonlinear Model Predictive
Control (NMPC). Constraint aggregation functions provide an approximation of the feasible …

Climate change enforces the implementation of sustainable industrial production with a
special focus on pollution reduction, resource management, and energy savings. These …

Inactive constraints do not contribute to the solution of an optimal control problem, but
increase the problem size and burden the numerical computations. We present a novel …

We provide insights into the structure of the set of active constraints arising for optimal
solutions to nonlinear model predictive control problems along a shrinking horizon. The …

In this paper, a novel control strategy based on model predictive control is proposed for
tracking the trajectory of unmanned aerial vehicles (UAV). First, the dynamic model of an …

The nonlinear program arising in nonlinear model predictive control can be simplified by
constructing candidate active sets for the successor state. Instead of modifying the …

We present the design, training, and implementation of a nonlinear autoregressive neural
network for the control of a multi-input, multi-output hydraulic plant. The network mimics the …

The tracking control of an unmanned autonomous vehicle (UA V) is one of the key factors
determining the performance and effectiveness of autonomous navigation. A controller …

Meine Tätigkeit als Wissenschaftler am Lehrstuhl für Regelungssystemtechnik der Fakultät
Elektrotechnik und Informationstechnik der Technischen Universität Dortmund hat mir die …