Shuquan Wang

Technology and Engineering Center for Space Utilization

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Hanspeter Schaub

University of Colorado Boulder

Aixue Wang

Harbin Institute of Technology

Guangcheng Ma

Harbin Institute of Technology

Long Zhang

Chinese Academy of Sciences

Bingyu Xu

Chinese Academy of Sciences

Hongwei Xia

Harbin Institute of Technology

Lingchao Zhu

Shanghai Maritime University

Hongjun Yang

Beijing Academy of Artificial Intelligence

Yusen Zhang

Shandong University

Zongfeng Li

Technology and Engineering Center for Space Utilization

Cooperative Institutions

Chinese Academy of Sciences

University of Chinese Academy of Sciences

Technology and Engineering Center for Space Utilization

Wuhan Institute of Physics and Mathematics

Sun Yat-sen University

Harbin Institute of Technology

Jinzhou Medical University

Huazhong University of Science and Technology

Zhejiang University

Sun Yat-sen University Cancer Center

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A Path Planning Approach Based on Q-learning for Robot Arm

Mengyu Ji Long Zhang Shuquan Wang

A path planning method based on Q-learning is proposed for robot arm. As reinforcement learning, Q-learning is widely used in the field of mobile robot navigation due to its simple and well-developed theory. However, most of researchers avoid using it for solving the robot arm path planning problem because it has to take each joints motion into account. In this study, approximate regions instead of accurate measurements are used to define new state space and joint actions. Moreover, the reward function takes the distance from current position of robots' end-effector to the goal position into account. The experimental simulation shows that the Q-learning approach is efficient and has ability to plan a collision free path for robot arm when the order of magnitude of state space is below 10 ⁴ . Furthermore, the experimental results indicate that the number of obstacles affects the calculation time for the same iterations. The more obstacles, the less calculation time the algorithm needs. The weight coefficient in the reward function affects the convergence speed and the quality of the solutions.

Position (finance)

Arm solution

Robot end effector

Configuration space

10.1109/icras.2019.8809005

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Citations (14)

Establishment and Preliminary Application of a Single-tube Nested PCR Assay for Detection of Goat Eperythrozoon

Progress in Veterinary Medicine (2013)

Shuquan Wang

To establish a single-tube nested PCR assay for detection to Liaoning Cashmere goat Eperythrozoon,according to the published Eperythrozoon 16 S rRNA gene sequence in GenBank,two pairs of primers were designed to establish nested PCR assay for detecting the disease caused by goat Eperythrozoon.The results of verification experiments showed that the targeted gene fragment was 681 bp in length and homology of nested PCR product was 97.6%-99.2%,and this detection method had no cross reaction with M.wenyoni,Eperythrozoon suis,Sheep Mycoplasma pneumonia,Swine Mycoplasma pneumonia,E.coli.The sensitivity reached to 14.8 fg DNA.The 43.2% positive rate in 74 clinical samples by the single-tube nested PCR assay was higher than those by routine PCR and blood smear.The results revealed that the single-tube nested PCR assay had higher specificity,sensitivity,and can be used as an effective detection method of goat Eperythrozoon.

Mycoplasma pneumonia

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Applying VOF method to analyze effect of wave and permeable piled wharf

Port & Waterway Engineering (2009)

Shuquan Wang

With the 2-D numerical wave channel model established by the VOF method,this paper calculated the wave transmission coefficient of the permeable piled wharf and compared it with the physical model experiment results,and those by the Wiegel Kriebel formula.In order to reduce the re-reflection of wave-maker,absorbed numerical wave-maker boundary condition was established on the left end of the flume. The predicted wave transmission coefficient agreed well with the experiments and the results of Wiegel Kriebel.

Wharf

Wave flume

Transmission coefficient

Breakwater

Flume

Reflection coefficient

Reflection

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Deep Neural Networks Based Real-time Optimal Control for Lunar Landing

IOP Conference Series Materials Science and Engineering (2019)

Lingchao Zhu Jian Ma Shuquan Wang

Abstract Recent research on deep learning control, a new control algorithm based on machine learning able to learn deep architectures, has shown excellent performance on robots and drones. With the development of intelligent control like deep learning and reinforcement learning, accuracy, real-time, adaptability, robustness and autonomy of control algorithm have been achieved by the intelligent controls. Traditional control methods have difficulties to achieve nice performance in complex situations. Deep learning offers powerful algorithms to real-time search near-optimal controllers of lunar landing spacecraft with nonlinear dynamics. In terms of lunar landing control system, deep architectures offer the possibility to get an approximate solution of co-state equation without time-consuming iterative process. Furthermore, real-time optimal thrust during lunar landing may be derived directly through deep neural networks. As a single infrastructure for machine learning in both production and research, TensorFlow is chosen for training the deep artificial neural networks in this paper. Numerical simulations demonstrate the effectiveness of deep neural networks. The results of deep neural networks based optimal control are contrasted with traditional optimal algorithm, whose main idea is to track the pre-designed optimal trajectory by ground station. This research provides an effective approach to cope with the lunar landing problem.

Robustness

Adaptability

10.1088/1757-899x/608/1/012045

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Citations (11)

Single crater-aided inertial navigation for autonomous asteroid landing

Advances in Space Research (2018)

Yu Meng Shuang Li Shuquan Wang Xiangyu Huang

10.1016/j.asr.2018.09.035

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Citations (10)

Relative Lambert Problem of Near Coplanar Long-Range Relative Motion

2018 IEEE CSAA Guidance, Navigation and Control Conference (CGNCC) (2018)

Qingang Mao Shuquan Wang Zhen Zhao

The relative Lambert problem based on a near-coplanar long-range relative motion in circular reference orbit is investigated. The relative Lambert problem consists of determining the relative velocity given relative positions at two known times. As for the short distance relative Lambert problem, an analytic solution is obtained by using matrix inversion based on the Clohessy-Wiltshire equation. Then a second-order relative motion Lambert solver is derived from the second-order Clohessy-Wiltshire equation. However, the admissible relative distance between spacecrafts is still far smaller than the semi-major axis of the chief spacecraft. This paper aims to enlarge the admissible relative distance. To solve the corresponding relative Lambert problem, a time-explicit analytic description of a near-coplanar long-range relative motion in circular reference orbit is introduced to provide a two-pulse relative transfer strategy. It is worth pointing out that the angle between the inertial position vector of the chief and the inertial position vector of the deputy can be any value, which means the admissible relative distance can be very large. The choice of the transfer time is also important. As a result of the existence of singular points, the transfer time should be far away from these singular points. In addition, the transfer time should ensure that the initial impulse meets the corresponding condition of the analytical solution to the long range relative motion. Four numerical results show that the proposed method to solve the relative Lambert problem is indeed effective and feasible.

Relative velocity

Relative Motion

Circular orbit

10.1109/gncc42960.2018.9019036

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2艇Lorentz力形成動力学と制御【Powered by NICT】

IEEE Conference Proceedings (2016)

Zhang Siyang Shuquan Wang

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Optimal anti-interception orbit design based on genetic algorithm

International Journal of Computational Science and Engineering (2019)

Renfu Li Renfu Li Shuquan Wang

The space defence three-player problem with impulsive thrust is studied in this work. Interceptor spacecraft and anti-interceptor spacecraft have only one chance to manoeuvre while target spacecraft just keeps running in the target orbit without the ability to manoeuvre. Based on Lambert theorem, space defence three-player problem is modelled and divided into two layers. The internal layer is interception problem that interceptor spacecraft tries to intercept target spacecraft. The external layer is anti-interception problem that anti-interceptor spacecraft tries to defend against interceptor spacecraft. Because it can get the global solution and does not need the gradient information which is required in traditional optimisation methods, the genetic algorithm is employed to solve the resulting parameter optimisation problem in interception/anti-interception problem. Numerical simulation is provided to verify the availability of the obtained solution, and the results show that this work is useful to some practical applications.

Interception

Orbit (dynamics)

10.1504/ijcse.2019.099645

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Adaptive neural network control of hypersonic flight vehicle with actuator constraints

2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) (2020)

Aixue Wang Shuquan Wang

An adaptive neural network controller based on the back-stepping is developed for a generic hypersonic flight vehicle. The controller addresses two main problems, including model uncertainty and input saturations. First, the longitudinal dynamic model is transformed into an altitude subsystem and a velocity subsystem with the strict feedback form. Then, the combination of the adaptive neural network controller via the back-stepping method and command filter is utilized to track the altitude and velocity command. The stability analysis of the closed-loop system is proved based on Lyapunov's stability theorem. Simulation results display that the proposed controller is robust in terms of parametric uncertainty and meets the performance requirements with input saturation.

Hypersonic flight

10.1109/auteee50969.2020.9315589

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Synchronized Attitude and Position Control for Spacecraft Tracking Non-Cooperative Space Object

2018 IEEE CSAA Guidance, Navigation and Control Conference (CGNCC) (2018)

Mengyu Ji Shuquan Wang Zhen Zhao

This paper investigates the synchronized position and attitude tracking control of a spacecraft tracking a space object. The objective of the control is to make the spacecraft stay at a certain distance above a specific surface of the space object. Dual quaternion is utilized to describe the spacecraft's orbit an d attitude coupled equations of motion. A generalized PD controller is developed to fulfill the control objective. Stability is proved by the Lyapunov's stability theory and the Barbarat's lemma. Numerical simulations illustrate the effectiveness of the tracking control scheme.

Position (finance)

Tracking (education)

10.1109/gncc42960.2018.9019114

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Citations (2)