Nonlinear model predictive control of a wave energy converter based on differential flatness parameterisation
Nonlinear model predictive control of a wave energy converter based on differential flatness parameterisation
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DOI：
10.1080/00207179.2015.1088173
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发表时间：
2017-01
影响因子：
2.1
通讯作者：
Guang Li
中科院分区：
文献类型：
--
作者：
Guang Li
摘要针对波浪能转换器（WEC）的非线性模型预测控制问题，提出了一种快速约束优化方法。这种方法的优点在于它利用了WEC模型的微分平坦性。这可以减少所得到的非线性规划问题（NLP）的维数从连续约束最优控制的WEC使用伪谱方法。使用这种方法的计算负担的减轻，有助于促进经济实施的非线性模型预测控制策略的WEC控制问题。该方法适用于非线性WEC模型，非凸目标函数和非线性约束，这是常见的WEC控制问题。数值模拟证明了这种方法的有效性。
ABSTRACT This paper presents a fast constrained optimization approach, which is tailored for nonlinear model predictive control of wave energy converters (WEC). The advantage of this approach relies on its exploitation of the differential flatness of the WEC model. This can reduce the dimension of the resulting nonlinear programming problem (NLP) derived from the continuous constrained optimal control of WEC using pseudospectral method. The alleviation of computational burden using this approach helps to promote an economic implementation of nonlinear model predictive control strategy for WEC control problems. The method is applicable to nonlinear WEC models, nonconvex objective functions and nonlinear constraints, which are commonly encountered in WEC control problems. Numerical simulations demonstrate the efficacy of this approach.