Ein suboptimaler Ansatz zur schnellen modellprädiktiven Regelung nichtlinearer Systeme

Zusammenfassung Der Beitrag stellt ein schnelles modellprädiktives Regelungsverfahren für nichtlineare Systeme mit Stellgrößenbeschränkungen vor. Das Verfahren berechnet in jedem Abtastschritt eine suboptimale Lösung des unterlagerten Optimierungsproblems, die über die Laufzeit des Prozesses inkrementell verbessert wird. Des Weiteren zeichnet sich das Verfahren durch eine feste Anzahl an Iterationen pro Abtastschritt aus und ist rechenzeit- und speichereffizient implementierbar. Die Echtzeitfähigkeit und Regelgüte sowie die inkrementelle Verbesserung des Verfahrens werden für einen Verladekran im Labormaßstab mit einer Abtastzeit von 2 ms verdeutlicht. Abstract The paper describes a fast Model Predictive Control (MPC) scheme for nonlinear systems subject to control constraints. The MPC scheme computes a suboptimal solution of the underlying optimal control problem that is incrementally refined over the runtime of the process. The MPC scheme uses a fixed number of iterations in each sampling step and allows for a time and memory efficient computation of the single iterations. The control performance, the real-time feasibility as well as the incremental improvement of the MPC scheme are demonstrated for a laboratory overhead crane with a sampling time of 2 ms.

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