In this paper, an effective motion comparison method based on segmented multi-joint line graphs combined with the SIFT feature matching method is proposed. Firstly, the multi-joint 3D motion data are captured using th...
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This paper studies the problem of designing insensitive H∞ output-feedback controllers for linear discrete-time systems. The designed controllers are insensitive to additive/multiplicative controller coefficient vari...
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The wind is the main factor to influence the propagation of gas in the atmosphere. Therefore, the wind signal obtained by anemometer will provide us valuable clues for searching gas leakage sources. In this paper, the...
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This contribution presents a new methodology for the online identification, which allows the modeling of the stationary and dynamic behavior of nonlinear combustion engines with many input and output variables in shor...
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This contribution presents a new methodology for the online identification, which allows the modeling of the stationary and dynamic behavior of nonlinear combustion engines with many input and output variables in short time with an appropriate model structure. The used models are local polynomial model trees. The necessary enhancements and adaptations of the identification algorithm for local polynomial model trees for the online methodology are presented. To enable an online identification, not only the parameters but also the structure of the models has to be adapted to the ongoing measuring procedure at a test bench. This structure adaptation methods use iteratively recorded measured data for the determination of an optimized model partition and regressor selection regarding the quality and complexity of the model. This maximizes the iterative improvement of the mathematical model, leading to a reduced test bench time. The applicability of the developed methodology is shown for the identification of a model from both, an artificial test function as well as a real diesel engine.
In traditional biomechanical analysis of upper limb, the high-precision motion data and lifelike human models are needed. It is obvious that those processes are costly and time-consuming. In this paper, a novel and si...
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The visualization of layer distribution of furnace burden in the time-radial-height dimension was presented based on array radar measured data. Abnormal data mining and data sampling method were adopted to obtain vali...
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This paper proposes a stator flux and rotor speed estimation method for induction motor (IM) based on extended complex Kalman filter (ECKF). A complex-valued model is adopted that allows a simpler and more effective s...
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This paper presents Barrier Lyapunov Based control of a dual-arm exoskeleton system by using the relative Jacobian technique. Two upper exoskeletons operates in a constrained region of the operational space, whose end...
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Minimum entropy control has been proven to be an effective method in control of non-Gaussian stochastic systems. In this case, the entropy is proposed as a generalization of the variance measure to characterize the ra...
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Minimum entropy control has been proven to be an effective method in control of non-Gaussian stochastic systems. In this case, the entropy is proposed as a generalization of the variance measure to characterize the randomness of the process. Minimum entropy corresponds to small uncertainty (or derivation), but it cannot guarantee the tracking error approaching to zero. Therefore, mean square error also should be added in the criterion. In this paper, by using a simple example, the method of generating a representative approximation of the Pareto optimal control set is investigated in both analytical and numerical ways. And simulation results show the feasibility of the proposed double-objective optimal control method.
Because the new approach cannot be applied directly in the hot-rolled strip laminar cooling process, a simulation is necessary to verify the new approach effectively which can improve the strip quality and production ...
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