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Dynamics Control of Fishing Robots

Research Project

Project/Area Number 07660338
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeSingle-year Grants
Section一般
Research Field 農業機械学
Research InstitutionTokyo University of Fisheries

Principal Investigator

TODA Masayoshi  Tokyo Univ.of Fisheries, Dept.of Marine Science and Technology, assistant professor, 海洋生産学科, 助手 (70262342)

Co-Investigator(Kenkyū-buntansha) YADA Sadami  Tokyo Univ.of Fisheries, Dept.of Marine Science and Technology, professor, 海洋生産学科, 教授 (60230249)
Project Period (FY) 1995 – 1997
Project Status Completed (Fiscal Year 1997)
Budget Amount *help
¥2,200,000 (Direct Cost: ¥2,200,000)
Fiscal Year 1997: ¥400,000 (Direct Cost: ¥400,000)
Fiscal Year 1996: ¥1,500,000 (Direct Cost: ¥1,500,000)
Fiscal Year 1995: ¥300,000 (Direct Cost: ¥300,000)
Keywordsunderwater robot / nonlinear system / robust control / linearization / scaled H^* control / 非線形フィードバック / μ設計 / モデリング / 数値計算 / ダイナミクス / 差分法 / 境界要素法 / グリーン関数
Research Abstract

In the large context of developing a unique manipulator for the fishing and oceanic industry use, in this research term, the control problem considering the dynamics of submerged objects has been considered : we call this manipulator "a fishing robot". In particular, the nonlinear property in such dynamics was focused on, and then the systematic approach to the nonlinear control system synthesis was investigated.
As a nonlinear control approach, the combination of the exact linearization via nonlinear state feedback and linear robust control technique was adopted. When some model is extracted from the real physical plant, there must be some gaps between the model and the real plant such as unmodeled dynamics, parameter errors, and so on. So linearization process must be disturbed by these gaps or the sensor noise. Hence, we assume the incompletely linearized plant to be some linear plant subject to the structured uncertainties, and then, apply the linear robust control technique to it.
Considering the structured uncertainties, the scaled H^* control approach was adopted. In this control problem framework, we has proposed the following approaches,
1) explicit representation of sensor noise as the structured uncertainties,
2) reduction of the structured uncertainty dimension with the consideration of non-correlation among the uncertainties,
3) nonlinear feedback gains with the consideration of the sign of real parameter uncertainties.
To evaluate these approaches, a series of simulations were conducted considering the simple SISO system where polynomial nonlinear terms exist. In these trials, these approach were successful respectively.

Report

(4 results)
  • 1997 Annual Research Report   Final Research Report Summary
  • 1996 Annual Research Report
  • 1995 Annual Research Report

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Published: 1995-04-01   Modified: 2016-04-21  

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