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13th IFAC Symposium on Large Scale Complex systems: Theory and Applications, LSS 2013

作者： Hou, Zhongsheng Zhu, Yuanming Advanced Control Systems Lab School of Electronic and Information Engineering Beijing Jiaotong University Beijing China

This work presents a new data driven model free adaptive controller by virtue of the gradient information of the available plant model. Our approach is novel in the sense that we use the measured data to directly design the controller, and predict the system output using the plant model if the plant model is available. Whereas, the traditional model based control approach uses the measured data to identify the plant model firstly, and then uses the model to design and analyze the controller design based on this identified model. The main contribution is that this novel scheme opens a way for the data driven control method utilizing the plant model if the plant model is available. The theoretical analysis and the simulation results demonstrate the effectiveness and superiorities of the proposed method. © IFAC.

关键词： controllers

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An Improved Full-Form-Dynamic-Linearization based MFAC for a Class of Nonlinear systems with Exogenous Disturbance 34

An Improved Full-Form-Dynamic-Linearization based MFAC for a...

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第三十四届中国控制会议

作者： JIN Shangtai HOU Mengxue Advanced Control Systems Lab Beijing Jiaotong University School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University

ISBN: (纸本)9781467374439

In this paper, an improved full-form–dynamic–linearization(i FFDL) based model free adaptive control(MFAC) scheme(i FFDL-MFAC) is proposed for a class of discrete-time nonlinear systems with exogenous disturbance. The novel i FFDL data model is built along the dynamic operation points of the controlled plant using the concept called pseudo gradient(PG), where the exogenous disturbance is regarded as an element of pseudo gradient and it can be estimated merely using measured input and output data of the controlled plant. Then, the MFAC scheme is designed based on the proposed i FFDL data model according to a cost function of control input. By virtue of the proposed i FFDL method, the possible complicated behavior of the PG for the original nonlinear system caused by the exogenous disturbance may be better captured and dispersed. As a result, the proposed i FFDL-MFAC can deal with the exogenous disturbance more effectively and gives better control performance comparing with the prototype MFAC. Simulation results illustrate the correctness and effectiveness of the i FFDL-MFAC scheme.

关键词： Data driven control,Model free adaptive control,Nonlinear system,Dynamic linearization

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Guest Editorial for Special Issue on Extensions of Reinforcement Learning and Adaptive control

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IEEE/CAA Journal of Automatica Sinica 2014年第3期1卷 225-226页

作者： Frank L.Lewis Warren Dixon Zhongsheng Hou Tansel Yucelen Institute of Measurement&Control PE TexasU.K IEEE Control Systems Society(CSS) Operations for the Executive Committee of the IEEE CSS Board of Governors the Harbin Institute of Technology the Advanced Control Systems Lab Beijing Jiaotong University the Department of Automatic Control in School of Electronic and Information Engineering Beijing Jiaotong University Mechanical and Aerospace Engineering Department at the Missouri University of Science and Technology Advanced Systems Research Laboratory at the Missouri University of Science and Technology

ADAPTIVE control is a proven method for learning feedback controllers for systems with unknown dynamic models,exogenous disturbances,nonzero setpoints,and unmodeled *** control has been applied for years in process co... 详细信息

关键词： Special issues and sections Learning (artificial intelligence) Adaptive control Feedback

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A statistical analysis of model free adaptive control with measurement disturbance

A statistical analysis of model free adaptive control with m...

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作者： Bu, Xuhui Hou, Zhongsheng Jin, Shangtai Advanced Control Systems Lab. Beijing Jiaotong University Beijing 100044 China

ISBN: (纸本)9787894631046

This work is considered with the robustness of model free adaptive control (MFAC) systems with measurement disturbances. By using statistical analysis, it is possible to investigate the influence of the measurement disturbance with statistical properties. Aiming to suppress the measurement disturbance, a modified MFAC algorithm with a decreasing gain is also proposed. Through rigorous analysis, it is shown that the modified algorithm has better robustness to measurement disturbances. The analysis is supported by simulations.

关键词： Adaptive control systems

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Decentralized model-free adaptive control for signalized intersections network

Decentralized model-free adaptive control for signalized int...

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13th IFAC Symposium on Large Scale Complex systems: Theory and Applications, LSS 2013

作者： Li, Yongqiang Hou, Zhongsheng Hao, Jiangen Advanced Control Systems Lab School of Electronics and Information Engineering Beijing Jiaotong University Beijing 100044 China

Signalized intersections network consists of signalized intersections, which is characterized by large scale level. Decentralized control scheme is appropriate to deal with such systems, whose design and application are simpler and more practical than centralized controllers. The same as other large scale systems, it is difficult to get an accurate model of signalized intersections network;meanwhile, it has its own characteristics. The prominent one is that interactions between intersections (subsystems) are easily measured. Considering the two characteristics, we propose a new decentralized control method based on MFAC scheme. Thanks to MFAC scheme, the mechanism model is not needed. Because interactions are easily measured, our method views interactions as measurable disturbances. This just partially uses information of interactions because we do not attempt to force interactions to be some desired values. Using PARAMICS, the simulation study verifies the effectiveness of our control method. © IFAC.

关键词： Decentralized control

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Robust control for Missile with Lateral Jet and Aerodynamic Surfaces 29

Robust Control for Missile with Lateral Jet and Aerodynamic ...

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第29届中国控制与决策会议

作者： Xiangfei Deng Xiangbin Liu Jinpeng Zhang School of Electronic Information Engineering Beijing Jiaotong University Advanced Control Systems Lab School of Electronic Information EngineeringBeijing Jiaotong University

ISBN: (纸本)9781509046584

In this paper,a robust blending control algorithm of tail fin and reaction jet of autopilot is proposed for the pitch control of a *** missile dynamic is a nonlinear system with uncertainties,which is existed in both aerodynamic force and moment generation terms in the equations of *** bound of the uncertainties are known,which is used to attenuate uncertainties by robust part in the control law,which guarantees the whole missile system with satisfying control performance both in transient state and steady *** dual control allocator is designed to manipulate the tail fin and reaction jet of the missile work cooperatively when the deflection of aerodynamic rudder is in its limitation deflection and cannot supply enough torque via attitude deflection *** stability analyses is provided for the closed-loop system in this ***,numerical simulations are given to illustrate the effectiveness of the proposed robust control law.

关键词： Robust control Blending principle Missile autopilot Dual control allocator

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Improving Spiking Neural Network Performance Using Astrocyte Feedback for Farsi Digit Recognition 31

Improving Spiking Neural Network Performance Using Astrocyte...

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31st International Conference on Electrical Engineering, ICEE 2023

作者： Nazari, Malihe Bahrami, Fariba Yazdanpanah, Mohammad Javad School of Electrical and Computer Engineering College of Engineering University of Tehran Human Motor Control and Computational Neuroscience Lab Advanced Control Systems Lab Tehran Iran School of Electrical and Computer Engineering College of Engineering University of Tehran Human Motor Control and Computational Neuroscience Lab Tehran Iran School of Electrical and Computer Engineering College of Engineering University of Tehran Advanced Control Systems Lab Tehran Iran

ISBN: (纸本)9798350312560

The third generation of neural networks is called spiking neural networks. Spiking neural networks can not only answer all the problems that can be solved by common neural networks, they can also be computationally more powerful than them. Also, these networks are closer to the biological reality of neurons. According to these reasons, spiking neural networks have received much attention in recent years. In addition to neurons, other elements are also used in spiking neural networks, whose connection with neurons has been proven biologically. These elements are called astrocytes. In this study, we have used astrocyte local feedback in a spiking neural network to improve the accuracy of the network in a digit recognition process. To reach this goal, we use the network proposed by Diehl et al in 2015, then we added astrocyte local feedback to this network. We run the network in both states. The classification accuracy of the network in the absence of astrocytes was 88.48% on Farsi handwritten digits. After adding astrocyte local feedback, it is observed that astrocytes control the activity of neurons and modified the weight of connections based on neuron activity. In this state classification accuracy reached 90.26%. The idea was to create a neural network for learning, where, inspired by the physiological role of astrocytes at the tripartite synapse improves the performance of the neural network and we demonstrate that systems that include neurons and astrocytes perform better than systems incorporating only neurons. © 2023 IEEE.

关键词： Neurons

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Data-driven Predictive Terminal Iterative Learning control for a Class of Discrete-time Nonlinear systems

Data-driven Predictive Terminal Iterative Learning Control f...

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第三十二届中国控制会议

作者： JIN Shangtai HOU Zhongsheng CHI Ronghu Advanced Control Systems Lab School of Electronic & Information EngineeringBeijing Jiaotong University School of Automation & Electronic Engineering Qingdao University of Science & Technology

ISBN: (纸本)9781479900305

In this paper,a novel data-driven predictive terminal iterative learning control(DDPTILC) scheme is proposed for a class of unknown discrete-time nonlinear systems by combining the advantages of predictive control and terminal iterative learning *** design and analysis of the proposed DDPTILC merely depends on the real-time measured I/O data without requiring any model *** mathematical analysis shows the efficiency of the proposed DDPTILC scheme.

关键词： Data-driven control Predictive control Terminal ILC Discrete-time nonlinear systems

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Iterative Learning Identification Using Quantized Observations 6

Iterative Learning Identification Using Quantized Observatio...

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2017 IEEE 6th Data Driven control and Learning systems Conference (DDCLS’17)

作者： Xuhui Bu Jian Liu Zhongsheng Hou School of Electrical Engineering & Automation Henan Polytechnic University Advanced Control Systems Lab. School of Electronics and Information EngineeringBeijing Jiaotong University

ISBN: (纸本)9781509054626

This paper develops a novel iterative learning parameter identification algorithm for a class of single parameter systems with multi-threshold quantized observations. The identification algorithm is constructed along the iteration axis and it can incorporate the parameter identification ability and the learning ability to deal with unknown time-varying parameters. Based on the recursive form of the estimation error along the iteration axis, it is proved that the convergence of parameter estimation can be guaranteed over the whole finite time interval. A numerical example is given to demonstrate the effectiveness of the algorithms.

关键词： Iterative Learning Parameter Identification Quantized Observations Time-varying Parameters

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Quantized Feedback control for a class of 2-D systems with Missing Measurements 34

Quantized Feedback Control for a class of 2-D Systems with M...

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第三十四届中国控制会议

作者： Bu Xuhui Cheng Zihao Hou Zhongsheng School of Electrical Engineering & Automation Henan Polytechnic University Advanced Control Systems Lab. School of Electronics and Information EngineeringBeijing Jiaotong University

ISBN: (纸本)9781467374439

In this paper, the quantized feedback control problem is investigated for a class of network-based 2-D systems described by Roesser model with data missing. It is assume that the states of the controlled system are available and there are quantized by logarithmic quantizer before being communicated. Moreover, the data missing phenomena is modeled by a Bernoulli distributed stochastic variable taking values of 1 and 0. A sufficient condition is derived in virtue of the method of sector-bounded uncertainties, which guarantees that the closed-loop system is stochastically stable. Based on the condition, quantized feedback controller can be designed by using linear matrix inequalities technique. The simulation example is given to illustrate the proposed method.

关键词： 2-D systems networked control systems quantized control missing measurements H_∞ control

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