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A Dual-Motor Joint Model for Humanoid Robots

A Dual-Motor Joint Model for Humanoid Robots

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第25届中国控制与决策会议

作者： Jingtao Xue Xiaopeng Chen Ye Tian Zhangguo Yu Fei Meng Qiang Huang IRI School of Mechatronic Engineering Beijing Institute of Technology Key Laboratory of Biomimetic Robots and Systems Ministry of Education Key Laboratory of Intelligent Control and Decision of Complex System

ISBN: (纸本)9781467355339

To make humanoid robots walking fast, it's important to improve driving force of their leg joints. Usually, each joint of humanoid robots is driven by a single motor. Dual-motor joint, on the other hand, is one of the candidate solutions to meet the power requirement needed for fast walking. This paper proposed a new dual-motor control model. In the model, two motors are treated as a single control plant instead of two parallel control plants. With the usage of current distributor, the control model can pump different current to each motor freely so as to eliminate the unbalance of the load imposed on each motor. Simulation and experiment show that the proposed model works well under high joint load and it can be used on a fast walking humanoid robot.

关键词： Humanoid robot, dual motor, control model

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Mars entry trajectory tracking via constrained multi-model predictive control

Mars entry trajectory tracking via constrained multi-model p...

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Chinese control Conference (CCC)

作者： Chao Wu Shihua Li Jun Yang Lei Guo Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing Jiangsu CN School of Automation Science and Electrical Engineering Beihang University & Institute of Instrument Science and Opto-Electronics Engineering Beijing CN

Tracking law designed for future Mars entry missions is investigated in this article. For precision landing, the nonlinear entry dynamics, complex uncertainties and input saturation constraints are unavoidable problems. Facing these challenges, the Mars entry trajectory tracking scheme via constrained multi-model predictive control (CMPC) is employed. The CMPC is made up of some constrained predictive control (CPC) in different time domain during the Mars entry mission. Each constrained predictive controller consists of a linearized prediction model (obtained by linearizing at different operating point), feedback correction for active model mismatch rejection caused by the complex uncertainties, and constrained rolling optimization for a smooth control input under a saturation constraint. Monte Carlo simulations demonstrate the effectiveness and excellence of the proposed method under the saturation constraint of input and uncertainties of initial state and aerodynamic parameters such as atmospheric density, ballistic coefficient and lift-to-drag ratio.

关键词： Mars Aerodynamics Uncertainty Trajectory Predictive models Vehicles Predictive control

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Synchronization of Kuramoto Oscillators with Non-identical Natural Frequencies: a Quantum Dynamical Decoupling Approach

Synchronization of Kuramoto Oscillators with Non-identical N...

引用

IEEE Annual Conference on Decision and control

作者： Zhifei Zhang Alain Sarlette Zhihao Ling SYSTeMS research group Faculty of Engineering and Architecture Ghent University Technologiepark Zwijnaarde 914 9052 Zwijnaarde(Ghent) Belgium Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology No.130 Meilong Road Shanghai 200237 China

ISBN: (纸本)9781467360890

This paper proposes a method to counter the drift associated to unknown non-identical natural frequencies in the Kuramoto model of coupled oscillators. Inspired by the quantum dynamical decoupling technique, it builds on a time-varying variant of the dynamics to effectively bring the oscillator phases closer to the same value. This allows effective synchronization despite arbitrarily large differences in natural frequencies. For two agents admitting instantaneous position exchanges, we exactly compute how the relative phase converges to a stable periodic fixed point. The latter tends to zero when the dynamics switches at a faster rate. With continuous state evolutions, using a related dynamic controller instead of instantaneous jumps, we show with a Lyapunov function that exact phase synchronization is obtained. We generalize the method to multiple oscillators with instantaneous state exchanges, that can be implemented by cycling through a predefined or random sequence of exchanges. Simulation results illustrate the effectiveness of the algorithms.

关键词： Natural frequencies Oscillators DECOUPLING phase synchronization coupled oscillators dynamics quanta

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Regularized Latent Least Square Regression for cross pose face recognition

Regularized Latent Least Square Regression for cross pose fa...

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23rd International Joint Conference on Artificial Intelligence, IJCAI 2013

作者： Cai, Xinyuan Wang, Chunheng Xiao, Baihua Chen, Xue Zhou, Ji State Key Laboratory of Management and Control for Complex Systems Institute of Automations Chinese Academy of Science Beijing China

ISBN: (纸本)9781577356332

Pose variation is one of the challenging factors for face recognition. In this paper, we propose a novel cross-pose face recognition method named as Regularized Latent Least Square Regression (RLLSR). The basic assumption is that the images captured under different poses of one person can be viewed as pose-specific transforms of a single ideal object. We treat the observed images as regressor, the ideal object as response, and then formulate this assumption in the least square regression framework, so as to learn the multiple pose-specific transforms. Specifically, we incorporate some prior knowledge as two regularization terms into the least square approach: 1) the smoothness regularization, as the transforms for nearby poses should not differ too much;2) the local consistency constraint, as the distribution of the latent ideal objects should preserve the geometric structure of the observed image space. We develop an alternating algorithm to simultaneously solve for the ideal objects of the training individuals and a set of pose-specific transforms. The experimental results on the Multi-PIE dataset demonstrate the effectiveness of the proposed method and superiority over the previous methods.

关键词： Face recognition

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Online model-free RLSPI algorithm for nonlinear discrete-time non-affine systems

Online model-free RLSPI algorithm for nonlinear discrete-tim...

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20th International Conference on Neural Information Processing, ICONIP 2013

作者： Zhu, Yuanheng Zhao, Dongbin State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783642420412

Policy iteration, as one kind of reinforcement learning methods is applied here to solve the optimal problem of nonlinear discrete-time non-affine system with continuous-state and continuous-action space. By applying action-value function or Q function, the implementation of policy iteration avoids the dependence on system dynamics. Online model-free recursive least-squares policy iteration (RLSPI) algorithm is proposed with continuous policy approximation. It is the first attempt to develop online LSPI algorithm for nonlinear discrete-time non-affine systems with continuous policy. A nonlinear discrete-time system is simulated to verify the efficiency of our algorithm. © Springer-Verlag 2013.

关键词： Iterative methods

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Nonlinear metric learning with deep independent subspace analysis network for face verification

Nonlinear metric learning with deep independent subspace ana...

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作者： Cai, Xinyuan Wang, Chunheng Xiao, Baihua Shao, Yunxue State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Face verification is the task of determining whether two given face images represent the same person or not. It is a very challenging task, as the face images, captured in the uncontrolled environments, may have large variations in illumination, expression, pose, background, etc. The crucial problem is how to compute the similarity of two face images. Metric learning has provided a viable solution to this problem. Until now, many metric learning algorithms have been proposed, but they are usually limited to learning a linear transformation. In this paper, we propose a nonlinear metric learning method, which leams an explicit mapping from the original space to an optimal subspace using deep Independent Subspace Analysis (ISA) network. Compared to the linear or kernel based metric learning methods, the proposed deep ISA network is a deep and local learning architecture, and therefore exhibits more powerful ability to learn the nature of highly variable dataset. We evaluate our method on the Labeled Faces in the Wild dataset, and results show superior performance over some state-of-the-art methods.© 2013 The Institute of Electronics, Information and Communication Engineers.

关键词： Learning algorithms

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Global Stability of Cascaded systems with Non-smooth Continuity

Global Stability of Cascaded Systems with Non-smooth Continu...

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第三十二届中国控制会议

作者： Ma Li Li Xuebing Ding Shihong Zhang Jun School of Electrical and Information Engineering Jiangsu University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSoutheast University

ISBN: (纸本)9781479900305

The local/global Lipschitz continuity is always required when considering the stability of the cascaded systems. Different from the exiting methods proposed in the literature,this paper gives a method to deal with non-smooth cascaded *** using iISS property,some sufficient conditions for global asymptotic stability of the cascaded systems are derived. Then,based upon this,an interesting result of finite-time stability for cascaded systems is further *** proposed methods are verified by some academic examples.

关键词： Cascaded systems Stability Finite-time control

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Non-Gaussian Approximation Iterative Receiver for MIMO-OFDM Vehicular Networks

Non-Gaussian Approximation Iterative Receiver for MIMO-OFDM ...

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17th International IEEE Conference on Intelligent Transportation systems & The Asia-Pacific Council on systems Engineering Conference 2014

作者： Shuangshuang Han Liuqing Yang Xiang Cheng Shichao Chen Fenghua Zhu Zhongdong Yu Haitao Xie Qingdao Academy of Intelligent Industries State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Electronics Engineering and Computer Science Peking University Guang Zhou Communication Information Construction Investment and Operation Co.Ltd.

Multiple-Input Multiple-Output- Orthogonal Frequency Division Multiplexing(MIMO-OFDM) is adopted to vehicular networks to increase the capacity,reliability and *** this paper,iterative demodulation and decoding algorithms are studied to approach the capacity of MIMOOFDM vehicular *** analysing the drawbacks of the Gaussian approximation on the interference cancellation,NonGaussian approximation is proposed to enhance the performance of interference cancellation based detectors with large *** results demonstrate that the proposed non-Gaussian algorithm can achieve a significant performance gain over existing ones with high order constellations.

关键词： Gaussian Non-Gaussian Approximation Iterative Receiver for MIMO-OFDM Vehicular Networks

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Decentralized Filtering a Multi-Agent System with Local Parametric Couplings Based On Kalman Filter

Decentralized Filtering a Multi-Agent System with Local Para...

引用

第25届中国控制与决策会议

作者： Yini Lv Hongbin Ma Mengyin Fu Chenguang Yang Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institution of Technology School of Computing and Mathematics Plymouth University

ISBN: (纸本)9781467355339

In this paper, decentralized filtering of multiagent systems with coupling uncertainties is proposed and investigated. The considered multi-agent system is composed of many agents, each of which evolves with a discrete-time stochastic linear time-varying dynamics, and every agent can be locally influenced by its neighbor agents. Therefore the states evolution of each agent is not only related with its previous states but also related with its neighbors' previous states in the linear dynamic system. Communication limitations existing in the considered multi-agent system restrict that each agent can only observe its own measurements (outputs) and its neighbor agents' outputs while the states are invisible to any agent. Because of communication limitations and information constraints, without knowing the coupling gains of the local interactions, it is not easy for each agent to estimate its states by traditional kalman filter or other state observers, which were extensively discussed in the literature. In this preliminary study, for the considered coupled linear discrete-time multiagent system with uncertain linear local couplings, based on the key idea of state augmentation and the certainty-equivalence principle borrowed from the area of adaptive control, we propose an efficient decentralized kalman filtering scheme, for each agent, to simultaneously estimate the unknown states and coupling parameters, and extensive simulations are conducted, which have clearly verified the effectiveness of the proposed decentralized filtering scheme.

关键词： multi-agent system, kalman filter, parametric couplings, parameter estimation, states estimation, decentralized filtering

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Unmanned Aerial Vehicles (UAV) Heading Optimal Tracking control Using Online Kernel-based HDP Algorithm

Unmanned Aerial Vehicles (UAV) Heading Optimal Tracking Cont...

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International Joint Conference on Neural Networks

作者： Fuxiao Tan Derong Liu Xinping Guan Bin Luo School of Computer and Information Fuyang Teachers College State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University School of Computer Science and Technology Anhui University

ISBN: (纸本)9781479914821

UAV can work in places that are dangerous, or not easy to reach for humans. However, due to active control and operating difficulties, it is still a challenge to develop fully autonomous flight in complex environments. This paper applies a novel heuristic dynamic programming for the UAV heading optimal tracking controller design, using kernel-based heuristic dynamic programming (KHDP). Kernel-based HDP is developed by integrating kernel methods and approximately linear dependence (ALD) analysis with the critic learning of HDP algorithm. Compared with conventional HDP where neural networks are widely used and their features were manually designed, the proposed algorithm can obtain better generalization capability and learning efficiency through applying the sparse kernel machine into the critic learning process of HDP algorithm. Simulation and experimental results of UAV heading optimal tracking control problems demonstrate the effectiveness of the proposed kernel-based HDP algorithm.

关键词： Kernel Algorithm design and analysis Heuristic algorithms Equations Vectors Approximation algorithms Mathematical model

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