We propose a control system for humanoid robot reaching using a motor-motor mapping that is learnt online. The system combines endpoint closed-loop and open-loop visual servo control. The closed-loop component moves the eyes, head, arm, and torso, based on the position of the target and the robot’s hand, as seen by the robot’s head mounted cameras. The learned, open-loop component brings the ha...

This paper aims at proposing an integrated optimum design method of the structure-control combined system by using closed loop system redesign based on feedback control. The proposed method is constructed from two steps: in the rst step, output feedback control system is designed for an initial structure in order to realize the desired closed loop system's characteristics; and in the second ste...

Indirect methods for identification of linear plant models on the basis of closed-loop data are based on the use of (reconstructed) input signals that are uncorrelated with the noise. This generally requires exact (linear) controller knowledge. On the other hand, direct identification requires exact plant and noise modelling (system in the model set) in order to achieve accurate results, althou...

Most of real-time scheduling algorithms are open-loop algorithms as the scheduling decisions are based on the worst-case estimates of task parameters. They do not continuously observe the performance of the system and do not dynamically adjust the system parameters t o improve performance. In many cases, it is preferable to base scheduling decisions on average-case workload parameters and be re...

This paper deals with leader-following and leaderless consensus problems of high-order multi-input/multi-output (MIMO) multi-agent systems with unknown nonlinear dynamics in the presence of uncertain external disturbances. The agents may have different dynamics and communicate together under a directed graph. A distributed adaptive method is designed for both cases. The structures of the contro...

Due to the prediction loop, instability is a major difficulty in the design of a predictive quantizer. The conventional open-loop method enjoys good stability but suffers from poor performance. In contrast, the closed-loop method may be able to perform better but it can not guarantee a complete convergence and so it is unstable. Recently, the asymptotic closed-loop approach was proposed to bene...