Suboptimal model predictive control of a laboratory crane
Suboptimal model predictive control of a laboratory crane
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实验室起重机的次优模型预测控制
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
A. Kugi
中科院分区：
文献类型：
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作者：
K. Graichen;M. Egretzberger;A. Kugi
摘要提出了一种快速模型预测控制（MPC）方案，并将其应用于实验室五自由度起重机的控制。MPC方案考虑了控制约束，并且基于梯度投影方法，该方法允许单次迭代的时间和存储器有效计算。为了保证实时可行性，每个采样步骤使用固定数量的迭代。尽管这会导致次优解，但将其应用于非线性起重机模型揭示了该方法的性能以及高计算速度。通过实验室起重机的采样时间为2毫秒的标准实时硬件的实验表明，所提出的方法的可行性。
Abstract A fast model predictive control (MPC) scheme is presented and applied to a laboratory crane with five degrees–of–freedom. The MPC scheme accounts for control constraints and is based on the gradient projection method that allows for a time and memory efficient computation of the single iterations. To guarantee real-time feasibility, a fixed number of iterations is used per sampling step. Although this leads to a suboptimal solution, its application to the nonlinear crane model reveals the performance as well as the high computational speed of the method. The feasibility of the proposed approach is shown by means of experiments of a laboratory crane with a sampling time of 2 ms on a standard real-time hardware.