豊橋技術科学大学

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Sano, Shigenori

Affiliation Department of Mechanical Engineering
Concurrent post Information and Media Center
Title Associate Professor
Fields of Research Control Engeering / System Identification
Degree Doctor in Engineering(Nagoya University)
Academic Societies Department of Mechanical Engineering
E-mail sano@me
Please append ".tut.ac.jp" to the end of the address above.
Laboratory website URL http://www.rm.me.tut.ac.jp
Researcher information URL(researchmap) Researcher information

Research

In recent years, advanced control strategies can be realized due to computers and peripherals with high performance and low cost. Therefore, it is more important to make a good model for the advanced control system design by the identification.
Under the back ground, my research interests are now in:

  1. Trajectory planning and control for mobile robot
  2. Modeling and control of a polymer actuator
  3. Experimental design for system identification
  4. Behavior acquisition by learning and control

Theme1:Trajectory planning and control for mobile robot

Overview
Mobile Robot

Recently, necessity of mobile robot is increasing at various situation, so mobile robots are studied actively. we study the control system for mobile robots(human operated type and autonomous type) such as the generatatio of the optimal trajectory, the correction of trajectory for obstacle avoidance and the operational support.

Keywords

mobile robot, trajectory planning, obstacle avoidance, operational support

Theme2:Modeling and control of a polymer actuator

Overview
polymer actuator

It's studied actively about an actuator newly in recent years. A polyer actuator is also the one. I'm aiming at realization of self-sensing actuator and the cooperation control using IPMC (Ionic polymer metal composite) actuator in this research.

Keywords

polymer actuator, self-sensing actuator

Theme3:Experimental design for system identification

Overview

When a control system is designed, it's important to get a good model. As it is important to choose the model structure and the distinction technique suitable for a distinction target for it, it is also important to acquire the data to independ enoughly and to have little affect on disturbance and an unmodeled dynamics. In this research, we aim at obtaining the such data based on the priori information.

Keywords

System identification, Experimental design for identification, least square method, unmodeled dynamics Linear matrix inequality

Title of class

Physics 1b / Robotics
Machine Fundamental Experiments of Engineering / Creative Experiment for Mechanical Engineering
Mechanism and Motion of Robots
Engineering of Intelligent Robotics


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