| Budget Amount *help |
¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2016: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2015: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2014: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Outline of Final Research Achievements |
In this research, we introduced the model predictive control into network systems to improve their convergence performance against environmental changes. In this research, we focused on sensor network systems for collecting environmental information with potential-based routing that is one of self-organizing routing methods. In this routing method, it is known that each node calculates its own potential value based on local information and it takes much time to converge the calculation. By giving an optimal control input from an external controller to a part of nodes, the calculation time for potential of all nodes can be greatly reduced without losing the advantages of self-organizing method.
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