In this paper, two event-triggered nonlinear model predictive control(NMPC) strategies based on Lyapunov function method for discrete-time nonlinear systems with bounded disturbances and state-dependent uncertainties ...
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Large amounts of data are produced in system operation, and how to extract effective information from these data has become an important research topic in the industrial application. Dimensionality reduction is a way ...
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Large amounts of data are produced in system operation, and how to extract effective information from these data has become an important research topic in the industrial application. Dimensionality reduction is a way to refine the data. Because of the low efficiency of the existing methods, these methods can't discover the internal structure of the data. Regarding these problems, a distributed method of dimensionality reduction based on clustering is proposed, which includes the following steps:(1) Clustering the data into some small classes according to the similarity between the data variables; (2) reducing the dimension of data in a small class after being clustered respectively; (3) merging the data after being reduced dimension; (4) classifying the data after being merged by support vector machine (SVM). The data in the simulation is the test data, and the results show that the methods proposed in this paper are better than the existing dimensionality reduction methods.
Intersection detection is a critical capacity for an Unmanned Ground Vehicle (UGV) to drive safely in structured urban environment. Large-scale intersections stamped on maps have plenty of features for detection while...
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Due to the limited visual field of UGV, it is difficult to detect the accessible zone in a wide range of area in real time. This paper proposes a UAV-aided autonomous road network construction method where roads are p...
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Recently deep learning based architectures have been widely deployed in many problems of artificial *** deep learning models, Convolutional Neural Networks(CNN) have been reported in numerous successful applications...
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Recently deep learning based architectures have been widely deployed in many problems of artificial *** deep learning models, Convolutional Neural Networks(CNN) have been reported in numerous successful applications such as object recognition, and natural language processing. The convolutional neural networks are trained by back-propagating the classification error using the Back-Propagation(BP) algorithm, which requires a large amount of data and slows the training process. To overcome these difficulties, a new fast and accurate approach based on Extreme Learning Machine(ELM) to train any convolutional neural network has been proposed. The developed framework(ELM-CNN) is based on the concept of autoencoding to learn the convolutional filters with biases, by reconstructing the normalized input and the intercept term. In this paper, systematic comparison with traditional back-propagation based training method(BP-CNN) has been made with respect to two aspects qualitative and quantitative. The experimental results on the popular MNIST dataset show that the ELM-CNN algorithm achieves competitive results in terms of generalization performance and up to 16 times faster than the back-propagation based training of CNN.
With the development of aeronautics and astronautics, the response speed of servo system need be faster. First, In order to improve the dynamic quality of servo system, the exponential and power reaching law, which co...
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With the development of aeronautics and astronautics, the response speed of servo system need be faster. First, In order to improve the dynamic quality of servo system, the exponential and power reaching law, which combines the advantages of the exponential reaching law and the power reaching law, is introduced. Second, the chattering of the sliding mode controller(SMC) with the exponential and power reaching law for discrete systems is investigated. Finally, the adaptive sliding mode controller(ASMC) with the exponential and power reaching law is introduced. The stability of the ASMC with the exponential and power reaching law for discrete systems is analyzed, and the simulation of this approach on one joint of a six degrees of freedom robot is carried out. The experimental results indicate that the ASMC with the exponential and power reaching law is effective in reducing the time of arriving the sliding mode surface. The experimental results also indicate that the ASMC with the exponential and power reaching law may make output error reach zero in a shorter time.
In this work, we propose a new scheme to estimate the algebraic connectivity of the graph describing the network topology of a multi-agent system. We consider network topologies modeled by undirected graphs. The main ...
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Stroke is mainly caused by the brain damage due to the acute cerebral vascular disease and its primary disease,which can make upper limb or lower limb on one side of the body *** rehabilitation training is the most ef...
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ISBN:
(纸本)9781509046584
Stroke is mainly caused by the brain damage due to the acute cerebral vascular disease and its primary disease,which can make upper limb or lower limb on one side of the body *** rehabilitation training is the most effective way to regain the Activities of Daily Living(ADL).Based on the concept of humanoid and modular design,this paper outlines the design process of humanoid ***,kinematics and dynamics are calculated in different coordinate frames,which makes simulation and control algorithms are more complex and not intuitive,for the forked-tree structure rehabilitation robot,a modified geometric description method of DH parameters is proposed to solve the problem of inconsistent frames,the whole body Jacobian matrix of this structure is derived and used for the inverse kinematics,and the singular configurations of redundant manipulator are *** important design criteria of humanoid robot is discussed,and the realization of the mechanical design is ***,the experimental results show that the humanoid robot can effectively carry out multiple parts rehabilitation training.
T0616. The temperature accuracy of the steel coil is directly affected the production quality of the steel plate. In the annealing furnace temperature controlsystem, strip temperature control is mainly decided by var...
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This paper presents a general six degrees of freedom(6-DOF) robot arm controlsystem based on Linux and field-programmable gate array(FPGA).The system provides a friendly human-computer interaction *** can complete pa...
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This paper presents a general six degrees of freedom(6-DOF) robot arm controlsystem based on Linux and field-programmable gate array(FPGA).The system provides a friendly human-computer interaction *** can complete palletizing,handling and other processes through simple programming of the interactive *** adopt industrial personal computer(IPC) as the controller to accomplish the kinematics calculation,design motion control board connected with the controller and the servo system,and use the servo system to implement the motion of the robot *** kinematics calculation and trajectory generation based on cubic polynomial are developed based on the Linux system,which improves the portability of the *** a normal method is adopted in updating trajectory points to improve *** control board is designed based on FPGA,which with the characteristic of parallel computing raises the running speed of the robot arm.
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