Xiangzhou Wang

A multiple autocorrelation analysis method for motor imagery EEG feature extraction

A novel multiple autocorrelation method for single trial EEG feature extraction was proposed. The time courses of ERD/ERS during motor imagery were investigated by calculating multiple autocorrelation before power spectrum analysis. Then the averaged power spectrums on specific frequency bands were sent to a K-nearest classifier to validate the separability between different classes. Compared with the result of power spectrum, the multiple autocorrelation performed better in attenuating noise and enhancing the separability between different classes with a small quantity of electrodes (C3 and C4). The maximum 90.0% accuracy tested on dataset of BCI-competition 2003 for motor imagery is achieved.

Gaze tracking system for teleoperation

Conventional control interfaces such as joystick, keyboard, and mouse are widely used in teleoperation. However, they are not operated by some users such as who have disabled hands. This paper proposed an eye gaze tracking system for teleoperation. The eye gaze tracking system is based on non-intrusive, visible light, iris center corneal reflection (ICCR) and 2-D mapping-based gaze estimation. In addition, this paper also presented a simple and effective 2-D mapping-based calibration method in order to users with head movement. The calibration verification of five users shows the average errors of our proposed gaze tracker on the x- and y directions are 13.3 and 16.4 pixels, respectively. Through the teleoperation test of robotic car within fixed experimental area, the gaze tracking system achieved a good control result.

Diesel engine modeling based on recurrent neural networks for a hardware-in-the-loop simulation system of diesel generator sets

Abstract The electronic speed governors are widely used in diesel generator sets (DGS). To develop and debug electronic speed governor, the best option is to build a hardware-in-the-loop (HIL) simulation system. In the HIL simulation system, the physical diesel engine is replaced with its mathematical model for reducing the cost and producing less emissions. To meet the requirement of closing to the real environment, the performance of mathematical model representatives is very important. This paper presents a diesel engine modeling method based on recurrent neural networks (RNNs). This mathematical model is identified and estimated using the real data from one physical DGS. The experimental results showed that the proposed model accurately reproduced the diesel engine output characteristics with the changes of electrical power loads. To validate the proposed model, the simulation experiment was conducted on the established HIL simulation system. In the simulation experiment, the rack displacement and rotational speed were measured from the physical part of the HIL simulation system. The simulation result has been confirmed that the proposed model could well simulate the loading and unloading processes of the DGS.

THE RESEARCH FOR DISSOLVED OXYGEN FUZZY PID CONTROL SYSTEM BASED ON ADJUSTMENT FACTORS IN BIOLOGICAL CULTURE

The dissolved oxygen (DO) concentration in the culture solution plays an important role within the process of biological culture. The stable and accurate control of DO can maintain the normal survival and growth of microbes, cells, and tissue. However, the DO system is a typical control system with a large inertia, a longer lag time and a certain degree of uncertain control. The fuzzy PID controller with adjustment factors is presented in this paper. The paper details the structure of the biological culture system and establishes the DO control model based on the material balance formulate. The control rules of the fuzzy PID controller and adjustment factors controller according to the hypothetical process of the DO control are discussed. The idea of variable universe is introduced to design the control algorithm. The antiinterference and dynamic tracking simulations are performed in this paper. Compared with simple PID controller and conventional fuzzy PID controller, the proposed controller has been enhanced in several the performances.