The applications of two typical swarm intelligence algorithms in the optimization of the reentry trajectory for the hypersonic gliding vehicles are discussed in our paper. A trajectory optimization strategy based on t...
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This paper investigates modeling and control problems of the speed governing system of a hydro-generator unit with one upstream surge tank, driven by a Francis turbine. This governing system is organized into four mai...
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Hammerstein models are popular in describing nonlinear chemical processes. The general control strategy for Hammerstein models is the nonlinearity inversion method, which is unfortunately inapplicable to Hammerstein s...
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The principal lateral motion of an aircraft is described by a minimum of fourth order coupled state variable model. It is interesting to investigate how a decoupling controller can be designed. The Youla-parametrizati...
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ISBN:
(纸本)9780889868632
The principal lateral motion of an aircraft is described by a minimum of fourth order coupled state variable model. It is interesting to investigate how a decoupling controller can be designed. The Youla-parametrization is a simple method to design controllers. The KB-parametrization is a successful extension of this method for two-degree-of freedom (2DOF) systems. The paper extends this methodology for multivariable case and applies to the decoupling lateral control.
A novel structure identification procedure for discrete event systems described by Petri nets are proposed in this paper for model-based diagnostic purposes that utilize the notions and tools of process mining. The id...
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ISBN:
(纸本)9780889868632
A novel structure identification procedure for discrete event systems described by Petri nets are proposed in this paper for model-based diagnostic purposes that utilize the notions and tools of process mining. The identification of the structurally different discrete event system models describing a system in its normal and/or faulty modes was used for model-based isolation of the considered faulty modes. From the available process mining techniques that allow for the automatic construction of process models in Petri net form based on event logs, the genetic algorithm-based structure identification procedure has been found to be most capable of identifying the characteristic structural elements of the faulty models. The proposed procedures are illustrated on a simple example of an operated parking gate automaton with two faulty modes.
Abstract We consider an optimal control problem for networked control systems, where the loop is closed via a lossy, distributed network with an acknowledgment mechanism. The network is distributed in the sense that t...
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Abstract We consider an optimal control problem for networked control systems, where the loop is closed via a lossy, distributed network with an acknowledgment mechanism. The network is distributed in the sense that there are different sets of sensors and actuators that each communicate individually with the controller. We assume that all packets, i.e., the measurement packets, the control packets and the acknowledgment packets are sent over the lossy network and thus are subject to loss. We derive suboptimal controllers with respect to a quadratic cost criterion for the general case and optimal controllers for the case that all states are perfectly measured over a single link. Additionally, we present stability criteria for both cases.
For the design and development of a vision sensor for the ground test, a method of 3D reconstruction of feature point on large scale object surface from a single image is proposed. By establishing the math model of th...
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For the design and development of a vision sensor for the ground test, a method of 3D reconstruction of feature point on large scale object surface from a single image is proposed. By establishing the math model of the 3D coordinate of feature point on the object surface and using the spatial ray through feature point, the 3D coordinate of the feature point can be determined using single image. According to the characteristics, the object surface can be classified into three types: high order surface type, block plane type and block surface type, while the corresponding location methods are introduced. The accuracy of three different 3D reconstruction methods is compared by simulation experiments. By the measurement precision of 1/10000 in the range of 8000 mm×8000 mm, it is proved that the proposed method is suitable for 3D reconstruction of feature point on large scale object surface.
Based on the rotor field oriented control principle and space vector PWM technology, a vector control speed regulation algorithm applied to embroidery machines is developed based on DSP. Combined with the theoretical ...
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Based on the rotor field oriented control principle and space vector PWM technology, a vector control speed regulation algorithm applied to embroidery machines is developed based on DSP. Combined with the theoretical analysis, a kind of Anti-Windup PI controller is adopted based on output feedback calculations, and a discrete simulation model of the vector control speed regulation system is built on Matlab/Simulink platform. After the completion of the system hardware design, the entire control system software design and programming are completed based on the TMS320F2801 fixed-point DSP. Results of simulation and experiments show that the designed system meets the needs of a practical application in spindle actuator of the embroidery machine.
An important issue in the classification of electromyography signals is the classifier design. For surface electromyography signals in the acquisition process of serious interference by the noise, in particular freque...
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Atmospheric 3rd line diesel oil solidifying point is an important quality index, which cannot be measured in real time, in petroleum industry. Due to the great nonlinear characteristic of distillation columns, common ...
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Atmospheric 3rd line diesel oil solidifying point is an important quality index, which cannot be measured in real time, in petroleum industry. Due to the great nonlinear characteristic of distillation columns, common statistic methods, such as PCR and PLS, based on linear projection, are not able to estimate such a quality index effectively. In this paper, Adaptive kernel based Relevance Vector Machine (aRVM) is introduced to build a nonlinear soft sensor model. This soft sensor is then applied to a real solidifying point estimation experiment, with comparison to other nonlinear models such as KPLS, SVM and typical RVM. The result reveals that aRVM shows better performance than KPLS, SVM and models a much sparser representation than SVM and typical RVM.
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