Controller tuning with Bayesian optimization and its acceleration: Concept and experimental validation

This work discusses a data-driven approach to controller parameter tuning based on Bayesian optimization. In particular, we propose to design the prior mean function based on a model of the plant. By encoding the information on the model, the optimization needs a much fewer iterations than standard approaches. The effectiveness of the proposed method is demonstrated with a practical experiment.     

Sparse control for continuous-time systems

In this survey article, we give a comprehensive review of sparse control for continuous-time systems, called maximum hands-off control. The maximum hands-off control is the optimal control, for which we introduce fundamental properties such as necessary conditions, existence, and equivalence to the optimal control. We also show an efficient numerical computation algorithm for the maximum hands-off control based on the time discretization and ADMM (alternating direction method of multipliers). A numerical example is shown with an available MATLAB program.     

Image‐based visual target following for a nonholonomic wheeled mobile robot with a single fixed camera

This paper addresses the problem of visual target following for a nonholonomic wheeled mobile robot with a single fixed camera. For the problem, we propose a control scheme composed of vision‐based trajectory planning and tracking control. We present online trajectory planning based on image‐based visual servoing. The key idea is to compensate the target object motion. In particular, we focus on visual feature motion resulting from the target object motion. Tracking control to the generated trajectory can therefore achieve visual target following precisely even if the target object is moving. Our proposed scheme can be applied to, e.g. robotic systems for autonomous guard and observation. The effectiveness of the control system is evaluated experimentally. © 2012 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.