IEEE CDC 2020 Workshop

Compressed Sensing and Sparse Representation for Systems and Control

Overview

Sparsity is one of the major topics in machine learning and signal processing. Compressed sensing, also known as sparse representation, refers to the recovery of a high-dimensional but low-complexity vector (or signal) from a limited number of measurements. The notion of sparsity has also been attracting attention in control systems. In control systems, the sparsity in time is proposed for resource-aware control, such as event- (or self-) triggered control, where sensing and actuation is performed when needed. Also, optimal control called maximum hands-off control directly minimizes the time duration on which the control is active (i.e. L0 norm). Sparsity is also available for model reduction of control systems and networks.

In this workshop, we will review recent advances of sparsity methods in systems and control, and communications. We give lectures on

• tradeoffs between performance and complexity in control
• L0-optimal control and control node scheduling
• sparsity methods for wireless communications
• maximum hands-off control

List of Speakers

• Mihailo Jovanovic, University of Southern California
• Takuya Ikeda, The University of Kitakyushu
• Kazunori Hayashi, Kyoto University
• Ryo Hayakawa, Osaka University
• Masaaki Nagahara, Organizer of this workshop, The University of Kitakyushu

Program

Note: The time is UTC (or GMT; the time in UK). For the current UTC time, see here.

• 13:00-13:10: Opening Address
• 13:10-14:00
  • Controller architectures: tradeoffs between performance and complexity
  • Mihailo Jovanovic (University of Southern California)
• 14:00-14:50
  • Sparse optimal control with application to node selection problem
  • Takuya Ikeda (The University of Kitakyushu)
• 14:50-15:00: Break
• 15:00-15:50
  • Overloaded signal detection for communications systems via compressed sensing technique
  • Kazunori Hayashi (Kyoto University) and Ryo Hayakawa (Osaka University)
• 15:50-16:40
  • Maximum hands-off control
  • Masaaki Nagahara (The University of Kitakyushu)
• 16:40-16:50: Closing