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This paper proposes a new enhanced method based on one-dimensional direct linear transformation for estimating vehicle movement states in video sequences. The proposed method utilizes a contoured structure of target vehicles, and the data collection procedure is found to be relatively stable and effective, providing a better applicability. The movements of vehicles in the video are captured by active calibration regions while the spatial consistency between the vehicle's driving track and the calibration information are in sync. The vehicle movement states in the verification phase are estimated using the proposed method first, and then the estimated states are compared with the actual movement states recorded in the experimental test. The results show that, in the case of camera perspective of 90 degrees, in all driving states of low speed, high speed, or deceleration, the error between estimated speed and recorded speed is less than 1.5%, the error of accelerations is less than 7%, and the error of distances is less than 2%; similarly, in the case of camera perspective of 30 degrees, the errors of speeds, distances, and accelerations are less than 4%, 5%, and 10%, respectively. It is found that the proposed method is superior to other existing methods., 1. Introduction As the video image records the vehicles' motions within the monitoring range and can provide objective raw data for further quantitative analysis, video surveillance equipment has been applied [...]

An active disturbance rejection formation tracking problem is studied herein. Aiming at the time-varying formation tracking problem with external disturbance, a distributed control strategy of formation tracking based on extended state observer is presented. Considering the unknown state and external disturbance of single agent, a special extended state observer is produced which uses the output of neighbors. Subsequently, the extended state observer output–based formation protocol is designed to implement a predetermined formation. In addition, the necessary and sufficient condition of formation tracking control is obtained by taking full advantage of matrix transformation and Lyapunov theory. In the end, there are three simulation instances to verify the validity and feasibility of this method, which is mentioned in this article. [ABSTRACT FROM AUTHOR]

In this article, a robust extended state Kalman filter estimation algorithm for nonlinear complex networks is designed, fully considering the state coupling and colored noise among system nodes. The innovative measurement information subtraction method at adjacent moments deals with colored noise, making it more in line to meet engineering requirements. The states information of system nodes is redundant, and the collected data are processed by the quantizer, which greatly reduces the impact of network bandwidth constraints. Based on the bounds of the dynamic change rate of the nonlinear function rather than the bounds of the procedure itself, the upper bound of the error covariance is obtained, and real-time gain optimization is realized. Finally, the rationality and accuracy of the estimator are verified by simulation. According to the control variable method, the effects of the quantization density and quantization level of the quantizer on the stability of system are briefly demonstrated. [ABSTRACT FROM AUTHOR]

A feasible method in evaluating the protection effect and corrosion state of marine cathodic protection (CP) systems is collecting sufficient electric potential data around a submarine pipeline and then establishing the mapping relations between these data and corrosion states of pipelines. However, it is difficult for scientists and researchers to obtain those data accurately due to the harsh marine environments and absence of dedicated potential measurement device. In this paper, to alleviate these two problems, firstly, the theory of dimension and conductivity scaling (DACS) physical scale modeling of marine impressed current cathodic protection (ICCP) systems is generalized to marine CP systems, secondly, a potential measurement device is developed specially and analogue experiment is designed according to DACS physical scale modeling to verify the feasibility of the measuring system. The experimental results show that 92 percent of the measurement errors are less than 0.25mv, thereby providing an economical and feasible measuring system to get electric potential data around an actual submarine pipeline under CP.

To monitoring the subsea pipeline in real-time, a special potentiometric sensor array and a potential prediction model are presented in this paper. Firstly, to measure the potential of seawater, a special potentiometric sensor array with Ag/AgCl all-solid-state reference electrodes is first developed in this paper. Secondly, according to the obtained distribution law of electric field intensities a prediction model of the pipeline potentials is developed. Finally, the potentiometric sensor array is applied in sink experiment and the prediction model is validated by the sink measurements. The maximum error for pipeline potential prediction model is 1.1 mV. The proposed non-contact monitoring method for subsea pipeline can predict the potential of sea pipeline in real-time, thus providing important information for further subsea pipeline maintenance.