Enhancing Design of Visual-Servo Delayed System

A robust adaptive predictor is proposed to solve the time-varying and delay control problem of an overhead crane system with a stereo-vision servo. The predictor is based on the use of a recurrent neural network(RNN) with tapped delays, and is used to supply the real-time signal of the swing angle. There are two types of discrete-time controllers under investigation, i.e., the proportional-integral-derivative(PID) controller and the sliding controller. Firstly, a design principle of the neural predictor is developed to guarantee the convergence of its swing angle estimation. Then, an improved version of the particle swarm optimization algorithm, the parallel particle swarm optimization(PPSO) method is used to optimize the control parameters of these two types of controllers. Finally, a homemade overhead crane system equipped with the Kinect sensor for the visual servo is used to verify the proposed scheme. Experimental results demonstrate the effectiveness of the approach, which also show the parameter convergence in the predictor.

Distributed Recursive Projection Identification with Binary-Valued Observations

This paper investigates a distributed recursive projection identification problem with binaryvalued observations built on a sensor network,where each sensor in the sensor network measures partial information of the unknown parameter only,but each sensor is allowed to communicate with its neighbors.A distributed recursive projection algorithm is proposed based on a specific projection operator and a diffusion strategy.The authors establish the upper bound of the accumulated regrets of the adaptive predictor without any requirement of excitation conditions.Moreover,the convergence of the algorithm is given under the bounded cooperative excitation condition,which is more general than the previously imposed independence or persistent excitations on the system regressors and maybe the weakest one under binary observations.A numerical example is supplied to demonstrate the theoretical results and the cooperative effect of the sensors,which shows that the whole network can still fulfill the estimation task through exchanging information between sensors even if any individual sensor cannot.

Supporting multi-user real-time VBR video service using dynamic bandwidth management based on prediction

Real-time variable bit rate（VBR） video is expected to take a significant portion of multimedia applications.However,plentiful challenges to VBR video service provision have been raised for its characteristic of high traffic abruptness.To support multi-user real-time VBR video transmission with high bandwidth utilization and satisfied quality of service（QoS）,this article proposes a practical dynamic bandwidth management scheme.This scheme forecasts future media rate of VBR video by employing time-domain adaptive linear predictor and using media delivery index（MDI） as both QoS measurement and complementary management reference.In addition,to support multi-user application,an adjustment priorities classified strategy is also put forward.Finally,a test-bed based on this management scheme is established.The experimental results demonstrate that the scheme proposed in this article is efficient with bandwidth utilization increased by 20%-60% compared to a fixed service rate and QoS guaranteed.