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第三十二届中国控制会议

作者： Xue Zhang Haibin Duan Xinge Gao Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical EngineeringBeihang University Advanced Engineering Robotics Faculty of EngineeringUniversity of BristolBristol BS81THU.K.

ISBN: (纸本)9781479900305

In this paper,we proposed a hybrid method in extracting the attitude parameters of unmanned aerial vehicle(UAV), which is based on computer vision and improved artificial bee colony(ABC) *** is used as a characteristic line, whose two parameters,Φandσare utilized to obtain UAV's parameters:roll angleΨand pitch angleθ.Defogging Algorithm is used to make the original pictures clearer and gain the transmission image for horizon *** UAV could obtain the horizon through improved ABC *** also analyzed the relationship between line parameters and UAV parameters and calculated the UAV *** results verified the feasibility and effectiveness of our presented approach.

关键词： unmanned aerial vehicle(UAV) computer vision artificial bee colony(ABC) horizon

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Visual tracking in four degrees of freedom using kernel projected measurement

Visual tracking in four degrees of freedom using kernel proj...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Fateme Bakhshande Hamid D. Taghirad Advanced Robotics and Automated Systems (ARAS) Industrial Control Center of Excellence (ICCE) Faculty of Electrical and Computer Engineering K. N. Toosi University of Technology Tehran Iran

Visual Servoing is generally comprised of feature tracking and control. According to the literature, no attempt has already been made to optimize these two parts together. In kernel based visual servoing method, the main objective is to combine and optimize the entire control loop. By kernel definition, a Lyapanov candidate function is formed and the control input is computed so that the Lyapanov stability can be verified. This is performed in four degrees of freedom. In the present study, previous kernel algorithm from the recorded literature has been implemented. We have used the KBVS for our purpose such that an object without any marker is tracked. This method is chosen because of its robustness, speed and featureless properties. Furthermore, in order to show the visual tracking performance, all four degrees of freedom have been synthesized. Experimental results verifies the effectiveness of this method implemented for four degrees of freedom movements.

关键词： Kernel Visualization Asymptotic stability

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Position based sliding mode control for visual servoing system

Position based sliding mode control for visual servoing syst...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： M. Parsapour S. RayatDoost H. D. Taghirad Advanced Robotics and Automated Systems (ARAS) Industrial Control Center of Excellence (ICEE) Faculty of Electrical and Computer Engineering K. N. Toosi University of Technology Tehran Iran

This paper presents a nonlinear controller for visual servoing system. Pose estimation is one of the fundamental issues in position-based visual servoing (PBVS) approach. A few researches have focused on controller synthesis under modeling uncertainty and measurement noise of estimated position. In this research, PD-type sliding surface is designed for tracking target. The control signal is obtained from the sliding surface and the stability of the algorithm is verified by Lyapunov theory. Moreover, a recent designed robust estimator based on unscented Kalman observer (UKO) cascading with Kalman filter (KF) is used to estimate the pose, velocity and acceleration of the target. The combination of the implemented estimator and the proposed controller provide a stable and robust structure in PBVS. The reported experimental results, verify the effectiveness of the proposed method in an industrial visual servoing system.

关键词： Estimation Measurement uncertainty Robustness Visualization Service robots Positron emission tomography

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Unsupervised 3D object classification from range image data by algorithmic information theory

Unsupervised 3D object classification from range image data ...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Alireza Norouzzadeh Ravari Hamid D. Taghirad Advanced Robotics and Automated Systems (ARAS) Industrial Control Center of Excellence (ICCE) Faculty of Electrical and Computer Engineering K. N. Toosi University of Technology Tehran Iran

The problem of unsupervised classification of 3D objects from depth information is investigated in this paper. The range images are represented efficiently as sensor observations. Considering the high-dimensionality of 3D object classification, little attention has been paid to the curse of dimensionality in the existing state-of-the-art algorithms. In order to remedy this problem, a low-dimensional representation is defined here. The sparse model of every range image is constructed from a parametric dictionary. Employing the algorithmic information theory, a universal normalized metric is used for comparison of Kolmogorov complexity based representations of sparse models. Finally, most similar objects are grouped together. Experimental results show efficiency and accuracy of the proposed method in comparison to a recently proposed method.

关键词： Dictionaries Accuracy

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Robust PID control of cable-driven robots with elastic cables

Robust PID control of cable-driven robots with elastic cable...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Mohammad A. Khosravi Hamid D. Taghirad Advanced Robotics and Automated Systems (ARAS) Industrial Control Center of Excellence (ICCE) Faculty of Electrical and Computer Engineering K. N. Toosi University of Technology Tehran Iran

In this paper robust PID control of fully-constrained cable-driven robots with elastic cables is studied in detail. To develop the idea, a robust PID control for cable-driven robots with ideal rigid cables is firstly designed and then, this controller is extended for the robots with elastic cables. To overcome vibrations caused by inevitable elasticity of cables, a composite control law is proposed based on singular perturbation theory. The proposed control algorithm includes robust PID control for corresponding rigid model and a corrective term. Using the proposed control algorithm the dynamics of the cable-driven robot is divided into slow and fast subsystems. Then, based on the results of singular perturbation theory, stability analysis of the total system is performed. Finally, the effectiveness of the proposed control law is investigated through several simulations on a planar cable-driven robot.

关键词： Robustness Robots Linear matrix inequalities

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A positive tensions PID controller for a planar cable robot: An experimental study

A positive tensions PID controller for a planar cable robot:...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Mohammad A. Khosravi Hamid D. Taghirad Reza Oftadeh Advanced Robotics and Automated Systems (ARAS) Industrial Control Center of Excellence (ICCE) Faculty of Electrical and Computer Engineering K. N. Toosi University of Technology Tehran Iran Intelligent Hydraulics and Automation Department (lHA) Tampere University of Technology Finland

In this paper design and control of planar cable-driven parallel robots are studied in an experimental prospective. Since in this class of manipulators, cable tensionability conditions must be met, feedback control of such robots becomes more challenging than for conventional robots. To meet these conditions, internal force control structure is introduced and used in addition to a PID control scheme to ensure that all cables remain in tension. A robust PID controller is proposed for partial knowledge of the robot, to keep the tracking errors bounded. Finally, the effectiveness of the proposed control algorithm is examined through experiments on K.N. Toosi planar cable-driven robot and it is shown that the proposed control structure is able to provide suitable performance in practice.

关键词： PD control Assembly Logic gates Servomotors Force

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Q-parameterization control for a class of DC motor

Q-parameterization control for a class of DC motor

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3rd International Conference on Intelligent Systems Modelling and Simulation, ISMS 2012

作者： Nawawi, S.W. Ibrahim, Zuwairie Khalid, Marzuki Control and Instrumentation Department Faculty of Electrical Engineering Universiti Teknologi Malaysia Johor Bahru Malaysia Centre for Artificial Intelligence and Robotics Faculty of Electrical Engineering Universiti Teknologi Malaysia Johor Bahru Malaysia

ISBN: (纸本)9780769546681

The DC motor speed control is commonly used in several robotic applications. Thus the controller design for the DC motor speed control is a compulsory to optimize the performance of the motor towards the system design specification. In this paper the DC motor mathematical model is obtained then Three linear controllers, which are PID, LQR, and Q-parameterization controllers are designed for controlling the DC motor speed. The performance of the control techniques is compared in terms of transient response and steady state error performance. The comparison amongst the controller shows that the Q-parameterization controller significantly reduces the transient response performance and also steady state error. © 2012 IEEE.

关键词： controllers

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Potential Function Based Multi-Agent Formation control in 3D Space

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IFAC Proceedings Volumes 2012年第22期45卷 682-689页

作者： Marko Bunic Stjepan Bogdan University of Zagreb Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering LARICS–Laboratory for Robotics and Intelligent Control Systems Zagreb Croatia

This paper presents the extension of the previously proposed method for multi-agent formation control based on potential function. The method derived for 2D space is extended to 3D. It has been shown that the control algorithm keeps all the properties of the original scheme in case of multi-agent formation moving in 3D. An adaptation mechanism that assures avoidance of unwanted stable equilibria, used in 2D, is implemented in the same form for 3D formations. The obtained simulation results demonstrate stable behavior of the system for various sets of parameters - the desired 3D formation is reached in finite time and maintained during trajectory execution.

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Robustness and Generalization of Model-Free Learning for Robot Kinematic control using a Nested-Hierarchical Multi-Agent Topology

Robustness and Generalization of Model-Free Learning for Rob...

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IEEE RAS & EMBS International Conference on Biomedical robotics and Biomechatronics

作者： John N. Karigiannis Costas S. Tzafestas Faculty of Electrical and Computer Engineering Division of Signals Control and Robotics National Technical University of Athens (NTUA)

ISBN: (纸本)9781457711992

This paper focuses on evaluating the robustness and knowledge generalization properties of a model-free learning mechanism, applied for the kinematic control of robot manipulation chains based on a nested-hierarchical multi-agent architecture. In the proposed topology, the agents correspond to independent degrees-of-freedom (DOF) of the system, managing to gain experience over the task that they collaboratively perform by continuously exploring and exploiting their state-to-action mapping space. Each agent forms a local (partial) view of the global system state and task progress, through a recursive learning process. By organizing the agents in a nested topology, the goal is to facilitate modular scaling to more complex kine-matic topologies, with loose control coupling among the agents. Reinforcement learning is applied within each agent, to evolve a local state-to-action mapping in a continuous domain, thus leading to a system that exhibits developmental properties. This work addresses problem settings in the domain of kinematic control of dexterous-redundant robot manipulation systems. The numerical experiments performed consider the case of a single-linkage open kinematic chain, presenting kinematic redundancies given the desired task-goal. The focal issue in these experiments is to assess the capacity of the proposed multi-agent system to progressively and autonomously acquire cooperative sensorimotor skills through a self-learning process, that is, without the use of any explicit model-based planning strategy. In this paper, generalization and robustness properties of the overall multi-agent system are explored. Furthermore, the proposed framework is evaluated in constrained motion tasks, both in static and non-static environments. The computational cost of the proposed multi-agent architecture is also assessed.

关键词： Multi-agent systems Generalization kinematics Agents Robot Robustness topology Learning processes

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A stochastic state prediction in AFM based nanomanipulation

A stochastic state prediction in AFM based nanomanipulation

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2012 9th IEEE International Conference on Mechatronics and Automation, ICMA 2012

作者： Wang, Zhiyu Liu, Lianqing Wang, Zhidong Dong, Zaili Yuan, Shuai Hou, Jing State Key Laboratory of Robotics Shenyang Institute of Automation CAS Shenyang 110016 China Faculty of Electrical and Control Engineering Liaoning Technical University Huludao 125105 China Dept. of Advanced Robotics Chiba Institute of Technology Chiba Japan Graduate School Chinese Academy of Sciences Beijing 100001 China

ISBN: (纸本)9781467312776

The reliability of AFM based nanomanipulation is one of the prerequisites for nano fabricating, thus uncertainties of the target nano-particle position need to be controlled within a pointed limits, which lead to two problem to be solved: one is how to describe state uncertainties at every different sample times;the other is how to deduce the next state uncertainty according to the current one. This paper provides a method to construct a stochastic predictive model to covering those problems. In the concrete, the predictive model uses Gaussian and Beta distribution as well as Mont Carlo Method to describe and deduce the state uncertainties respectively. The method is also applied to the process of pushing a nano-particle using AFM. © 2012 IEEE.

关键词： Stochastic systems

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