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Force-feedback based active compliant position control strategy for a hydraulic quadruped robot

Journal of Beijing Institute of Technology 2015年第4期24卷 546-552页

作者：王立鹏王军政马立玲陈光荣杨超峰 Key Laboratory of Intelligent Control and Decision of Complex System School of AutomationBeijing Institute of Technology

Most existing legged robots are developed under laboratory environments and, corre- spondingly, have good performance of locomotion. The robots＇ ability of walking on rough terrain is of great importance but is seldom achieved. Being compliant to external unperceived impacts is cru- cial since it is unavoidable that the slip, modeling errors and imprecise information of terrain will make planned trajectories to be followed with errors and unpredictable contacts. The impedance control gives an inspiration to realize an active compliance which allows the legged robots to follow reference trajectories and overcome external disturbances. In this paper, a novel impedance force/ position control scheme is presented, which is based on Cartesian force measurement of leg＇ s end effector for our hydraulic quadruped robot The simulation verifies the efficiency of the impedance model, and the experimental results at the end demonstrate the feasibility of the proposed control scheme.

关键词： active compliance impedance control force feedback contact force constrains space

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Localization and mapping in urban area based on 3D point cloud of autonomous vehicles

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Journal of Beijing Institute of Technology 2016年第4期25卷 473-482页

作者：王美玲李玉杨毅朱昊刘彤 Key Laboratory of Intelligent Control and Decision of Complex System School of AutomationBeijing Institute of Technology

In order to meet the application requirements of autonomous vehicles, this paper proposes a simultaneous localization and mapping （SLAM） algorithm, which uses a VoxelGrid filter to down sample the point cloud data, with the combination of iterative closest points （ICP） algorithm and Gaussian model for particles updating, the matching between the local map and the global map to quantify particles＇ importance weight. The crude estimation by using ICP algorithm can find the high probability area of autonomous vehicles＇ poses, which would decrease particle numbers, increase algorithm speed and restrain particles＇ impoverishment. The calculation of particles＇ importance weight based on matching of attribute between grid maps is simple and practicable. Experiments carried out with the autonomous vehicle platform validate the effectiveness of our approaches.

关键词： simultaneous localization and mapping （SLAM） Rao-Blackwellized particle filter （ RB-PF） VoxelGrid filter ICP algorithm Gaussian model urban area

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Optimal Tuning of Plant-Friendly PID controllers

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Journal of Beijing Institute of Technology 2010年第3期19卷 331-336页

作者：史大威王军政马立玲 Key Laboratory of Complex System Intelligent Control and Decision School of AutomationBeijing Institute of Technology

A plant-friendly proportional-integral-derivative （PID） controller optimization framework is proposed to make tradeoffs among set-point response,controller output variations and *** objective function is chosen as the weighted sum of the integral of squared time-weighted error and the integral of squared timeweighted derivative of the control variable with respect to set-point response,while the robustness of the system is guaranteed by constraints on gain and phase *** to the complex structure of the constraints,the problem is solved by genetic *** analysis show the proposed method could efficiently reduce the controller output variations while maintaining a short settling *** on the simulation results,iterative tuning rules for the weighting factor in the objective function are obtained,which allows efficient simple proportional-integral（PI） tuning formulae to be derived.

关键词： PID control plant-friendliness genetic algorithm constrained optimization

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Cloud control Systems

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IEEE/CAA Journal of Automatica Sinica 2015年第2期2卷 134-142页

作者： Yuanqing Xia School of Automation Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

The concept of cloud control systems is discussed in this paper, which is an extension of networked control systems (NCSs). With the development of internet of things (IOT), the technology of NCSs has played a key role in IOT. At the same time, cloud computing is developed rapidly, which provides a perfect platform for big data processing, controller design and performance assessment. The research on cloud control systems will give new contribution to the control theory and applications in the near future. © 2014 Chinese Association of Automation.

关键词： Big data Cloud computing Computation theory control systems control theory controllers Data handling Distributed computer systems Embedded systems Internet of things

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On Event-triggered Adaptive Robust control 36

On Event-triggered Adaptive Robust Control

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第36届中国控制会议

作者： Yuan Huang Junzheng Wang Dawei Shi State Key Laboratory of Intelligent Control and Decision of Complex Systems

ISBN: (纸本)9781538629185

In this work,an event-triggered adaptive robust controller（ET-ARC） design is considered for a continuous-time nonlinear system combined with structural uncertainties and parameter *** the event-trigger scheme,the controller only can obtain the sampled date of the output measurement at some certain instants determined by the designed triggering condition and therefore the performance of the ET-ARC depends on the triggering condition ***,in this work,for the adaptive robust control scheme,an event-triggered transmission strategy is proposed,which relies on the output measurement of the nonlinear ***,based on this strategy,the design idea of the adaptive robust controller is presented such that the tracking performance is ***,based on a more general assumption,we provide a possible formation of control signal which satisfies the requirement proposed.

关键词： Adaptive robust control event-triggered transmission parameter estimation

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Event-triggered attitude tracking for rigid spacecraft

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Science China(Information Sciences) 2019年第12期62卷 178-193页

作者： Deheng CAI Hengguang ZOU Junzheng WANG Yuan HUANG Dawei SHI State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology China Academy of Space Technology

This study aims to investigate the problem of attitude control for a spacecraft with inertial uncertainties, external disturbances, and communication restrictions. An event-triggered active disturbance rejection control approach is proposed for attitude tracking of the spacecraft. An event-triggered mechanism is introduced together with an extended state observer to jointly monitor the system states and total disturbances. The observation error is proved to be uniformly bounded. Based on the proposed control scheme,the integrated tracking system is shown to be asymptotically stable, implying successful attitude tracking of the spacecraft for the desired motion. Numerical results illustrate the effectiveness of the control strategy in achieving satisfactory tracking performance with a reduced data-transmission cost.

关键词： spacecraft attitude tracking active disturbance rejection control event-triggered control extended state observer

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Multi-Objective Cooperative Salvo Attack Against Group Target

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Journal of Systems Science & complexity 2018年第1期31卷 244-261页

作者： ZENG Jie DOU Lihua XIN Bin School of Automation State Key Laboratory of Intelligent Control and Decision of Complex SystemsBeijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology

This paper proposes a solution for the problem of cooperative salvo attack of multiple cruise missiles against targets in a group. Synchronization of the arrival time of missiles to hit their common target, minimizing the time consumption of attack and maximizing the expected damage to group targets are taken into consideration simultaneously. These operational objectives result in a hierarchical mixed-variable optimization problem which includes two types of subproblems, namely the multi-objective missile-target assignment（MOMTA） problem at the upper level and the time-optimal coordinated path planning（TOCPP） problems at the lower level. In order to solve the challenging problem, a recently proposed coordinated path planning method is employed to solve the TOCPP problems to achieve the soonest salvo attack against each target. With the aim of finding a more competent solver for MOMTA, three state-of-the-art multi-objective optimization methods（MOMs）,namely NSGA-II, MOEA/D and DMOEA-εC, are adopted. Finally, a typical example is used to demonstrate the advantage of the proposed method. A simple rule-based method is also employed for comparison. Comparative results show that DMOEA-εC is the best choice among the three MOMs for solving the MOMTA problem. The combination of DMOEA-εC for MOMTA and the coordinated path planning method for TOCPP can generate obviously better salvo attack schemes than the rule-based method.

关键词： Coordinated path planning missile-target assignment multi-missile salvo attack multiobjective optimization

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Deep reinforcement learning for optimal denial-of-service attacks scheduling

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Science China(Information Sciences) 2022年第6期65卷 98-106页

作者： Fangyuan HOU Jian SUN Qiuling YANG Zhonghua PANG State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Key Laboratory of Fieldbus Technology and Automation of Beijing North China University of Technology

We consider an optimal denial-of-service(DoS) attack scheduling problem of N independent linear time-invariant processes, where sensors have limited computational capability. Sensors transmit measurements to the remote estimator via a communication channel that is exposed to DoS attackers. However,due to limited energy, an attacker can only attack a subset of sensors at each time step. To maximally degrade the estimation performance, a DoS attacker needs to determine which sensors to attack at each time step. In this context, a deep reinforcement learning(DRL) algorithm, which combines Q-learning with a deep neural network, is introduced to solve the Markov decision process(MDP). The DoS attack scheduling optimization problem is formulated as an MDP that is solved by the DRL algorithm. A numerical example is provided to illustrate the efficiency of the optimal DoS attack scheduling scheme using the DRL algorithm.

关键词： optimal denial-of-service attack scheduling optimization limited energy deep reinforcement learning

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Model and Simulation of Multipath Error in DLL for GPS Receiver

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Chinese Journal of Electronics 2014年第3期23卷 508-515页

作者： CHENG Lan CHEN Jie XIE Gang Taiyuan University of Technology Education Ministry Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology

Although different multipath error models of Delay lock loop(DLL) used in GPS receiver are established, they have never been put together for comparison. Furthermore, no universal simulation method is developed to get a fair comparison among these models. A new model with implicate expression is hence proposed for the coherent DLL and the noncoherent Dot-product(DOT) power mode DLL. Meanwhile, a new simulation method based on the anonymous function in Matlab, which is especially suitable for models with implicit expression,is also proposed to compare the new model with the existing ones. The theoretical analysis and simulation results show that the existing models are the special case of the proposed one. The new simulation method can be used for the comparison of different multipath error models and the multipath error analysis of other DLLs for which only the implicit model is available.

关键词： Delay lock loop(DLL) Multipath Multipath error model Positioning system

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Adaptive robust control for four-motor driving servo system with uncertain nonlinearities

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control Theory and Technology 2017年第1期15卷 45-57页

作者： Wei ZHAO Xuemei REN Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing 100081 China

A novel adaptive robust control （ARC） is presented for the four-motor driving servo systems with the uncertain nonlinearities and actuation failures, such that the load tracking control is achieved with the proximate optimal-time. By applying the proposed scheme, several control objectives are achieved. First, the nonlinear synchronization algorithm is presented to maintain the velocity synchronization of each motor, which provides fast convergence without chatting. Moreover, the time-varying bias torque is applied to eliminate the effect of backlash and reduce the waste of energy. Then, the ARC is designed to achieve the proximate optimal-time output tracking with the transient performance in L2 norm, where the friction and actuation failures are addressed by the adaptive scheme based on the norm estimation of unknown parameter vector. Finally, the extensive simulated and experimental results validate the effectiveness of the proposed method.

关键词： Four-motor driving servo systems adaptive robust control velocity synchronization control friction backlash,actuation failures

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