2006 Fiscal Year Final Research Report Summary
Elucidation of Information and Control Performance Limitation in Control System : Unification of Control Theory, Information Theory and Signal Processing
| Project/Area Number |
16560379
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Control engineering
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| Research Institution | The University of Tokyo |
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Principal Investigator |
TSUMURA Koji The University of Tokyo, Graduate School of Information Science and Technology, Associate Professor, 大学院情報理工学系研究科, 助教授 (80241941)
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| Co-Investigator(Kenkyū-buntansha) |
HARA Shinji The University of Tokyo, Graduate School of Information Science and Technology, Professor, 大学院情報理工学系研究科, 教授 (80134972)
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| Project Period (FY) |
2004 – 2006
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| Keywords | networked control / information / information theory / system identification / adaptive control / congestion control / TCP / IP / quantization |
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| Research Abstract |
System identification via quantized data : In this research, we deal with system identification by using quantized data and derive the necessary information for parameter estimation. We can derive the optimal quantizer under the case that the generation of I/O data is probabilistic and the error is hard bound.
Networked control : We derive a suboptimal subband coding for feedback control systems. We also deal with adaptive control problem with quantized signals for discrete and continuous time systems and show stabilizing controllers. Furthermore, we consider the case of packet losses in the data transmission, and give the corresponding results.
Approximation and stabilization under the limitation of memory : We propose bit memory systems for describing the complexity of dynamical systems. We consider approximation or stabilization problem under constraints of the bit length of the memory and derive its lower or upper bounds.
Congestion control of network : We deal with congestion control of packets in computer networks with TCP/IP. We can derive the parameterization of the stabilizing controllers and succeed to give the optimal controllers.
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