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In this paper, using a neural-network-based online learning optimal control approach, a novel decentralized control strategy is developed to stabilize a class of continuous-time nonlinear interconnected large-scale systems. First, optimal controllers of the isolated subsystems are designed with cost functions reflecting the bounds of interconnections. Then, it is proven that the decentralized control...
We describe an algorithm for calculating the linearization of the dynamics for arbitrary constrained mechanical systems in generalized coordinates without using symbolic equations. Linearizations of dynamics are useful tools for controllability and stability analysis and can be used to generate locally stabilizing controllers for linear and non-linear systems. However, the computational expense for...
In this paper, we present the dynamic grid quorum, a technique for reducing the power consumption of large-scale storage systems. The key idea is to skew the workload towards a small number of quorums by means of a novel optimization algorithm. Moreover, this system allows reconfiguration by exchanging nodes without any data migration so as to reallocate high-capacity nodes to busier quorums. We demonstrate...
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