Closed-loop feedback sparsification under parametric uncertainties
Closed-loop feedback sparsification under parametric uncertainties
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参数不确定性下的闭环反馈稀疏化
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
N. Motee
中科院分区：
文献类型：
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作者：
Reza Arastoo;MirSaleh Bahavarnia;M. Kothare;N. Motee
研究了参数不确定系统的输出反馈控制器稀疏化问题。我们开发了一个优化方案，最大限度地减少性能恶化，从一个性能良好的预先设计的集中式控制器，同时增强稀疏模式的反馈增益。为了提高时间接近的预先设计的控制系统和它的sparsified对应，我们还纳入了一个额外的约束到问题的制定，使控制系统的输出被强制留在附近的预先设计的系统的输出。结果表明，由此产生的非凸优化问题可以等价地转化为一个秩约束问题。然后，我们制定了一个双线性最小化问题，以获得一个次优的解决方案，满足任意公差的秩约束。最后，IEEE 39节点新英格兰电力网络的次优稀疏控制器综合被用来展示我们所提出的方法的有效性。
We consider the problem of output feedback controller sparsification for systems with parametric uncertainties. We develop an optimization scheme that minimizes the performance deterioration from that of a well-performing pre-designed centralized controller, while enhancing sparsity pattern of the feedback gain. In order to improve temporal proximity of the pre-designed control system and its sparsified counterpart, we also incorporate an additional constraint into the problem formulation such that the output of the controlled system is enforced to stay in the vicinity of the output of the pre-designed system. It is shown that the resulting non-convex optimization problem can be equivalently reformulated into a rank-constrained problem. We then formulate a bi-linear minimization problem to obtain a sub-optimal solution which satisfies the rank constraint with arbitrary tolerance. Finally, a sub-optimal sparse controller synthesis for IEEE 39-bus New England power network is used to showcase the effectiveness of our proposed method.