ویراساینس.
سند علمی

Learning Model Predictive Control for Iterative Tasks

Ugo Rosolia, Francesco Borrelli

چکیده

A Learning Model Predictive Controller (LMPC) for iterative tasks is presented. The controller is referencefree and is able to improve its performance by learning from previous iterations. A safe set and a terminal cost function are used in order to guarantee recursive feasibility and nonincreasing performance at each iteration. The paper presents the control design approach, and shows how to recursively construct terminal set and terminal cost from state and input trajectories of previous iterations. Simulation results show the effectiveness of the proposed control logic.

اسناد مشابه

  • Robust Learning Model Predictive Control for Uncertain Iterative Tasks: Learning From Experience

    سند علمی۲۰۱۷Ugo Rosolia, Xiaojing Zhang, Francesco Borrelli

    We present a Robust Learning Model Predictive Controller (RLMPC) for constrained uncertain systems performing iterative tasks. The proposed controller builds on earlier work of Learning Model Predictive Control (LMPC) for deterministic systems. The main idea behind RLMPC is to co

  • Learning Model Predictive Control for Iterative Tasks. A Data-Driven Control Framework

    سند علمی۲۰۱۷Ugo Rosolia, Francesco Borrelli

    A Learning Model Predictive Controller (LMPC) for iterative tasks is presented. The controller is referencefree and is able to improve its performance by learning from previous iterations. A safe set and a terminal cost function are used in order to guarantee recursive feasibilit

  • Robust Learning Model-Predictive Control for Linear Systems Performing Iterative Tasks

    مقاله‌ی دسترسی آزاد۲۰۲۲IEEE Transactions on Automatic Control['Ugo Rosolia', 'Xiao-Jing Zhang', 'Francesco Borrelli', '']

    In this article, a robust learning model-predictive controller (LMPC) for uncertain systems performing iterative tasks is presented. At each iteration of the control task, closed-loop state, input, and cost are stored used in design. This article first illustrates how to construc

  • Learning Model Predictive Control for Iterative Tasks: A Computationally Efficient Approach for Linear System

    سند علمی۲۰۱۷CoRRUgo Rosolia, Francesco Borrelli

    Abstract: A Learning Model Predictive Controller (LMPC) for linear system is presented. The proposed controller builds on previous work on nonlinear LMPC and decreases its computational burden for linear system. The control scheme is reference-free and is able to improve its perf

  • Iterative learning model predictive control for multi-phase batch processes

    سند علمی۲۰۱۵Youqing Wang, Donghua Zhou, Furong Gao

    Multi-phase batch process is common in industry, such as injection molding process, fermentation and sequencing batch reactor; however, it is still an open problem to control and analyze this kind of processes. Motivated by injection molding processes, the multi-phase batch proce

  • Extremum Seeking-based Iterative Learning Model Predictive Control (ESILC-MPC)

    سند علمی۲۰۱۵CoRRAnantharaman Subbaraman, Mouhacine Benosman

    In this paper, we study a tracking control problem for linear time-invariant systems, with model parametric uncertainties, under input and states constraints. We apply the idea of modular design introduced in [1], to solve this problem in the model predictive control (MPC) framew