We present two dual control approaches to the model maintenance problem based on
adaptive model predictive control (mpc). The controllers employ systematic self-excitation …

Model predictive control has become an increasingly popular control strategy thanks to the
ability to handle constrained systems. Obtaining the required models through system …

This study introduces a novel semi-active control scheme, where the linear-quadratic
regulator (LQR) is combined with an unscented Kalman filter (UKF) observer, for the real …

The main problem of a closed-loop re-identification procedure is that, in general, the
dynamic control and identification objectives are conflicting. In fact, to perform a suitable …

Dual control aims to concurrently learn and control an unknown system. However, actively
learning the system conflicts directly with any given control objective for it will disturb the …

Identification of systems operating in closed loop is an important problem in industrial
applications, where model-based control is used to an increasing extent. For model-based …

This study proposes an active nonlinear control strategy for effective vibration mitigation in
nonlinear dynamical systems characterized by uncertainty. The proposed scheme relies on …

We present a novel approach to performing closed-loop system identification with minimal
deterioration of output regulation. The adaptive control algorithm excites the system to …

Abstract Recently, a linear Model Predictive Control (MPC) suitable for closed-loop re-
identification was proposed, which solves the potential conflict between the persistent …

Advanced process control and its prevalent enabling technology, model predictive control
(MPC), can today be regarded as the industry best practice for optimizing production. e …