The non-contact automatic on-line classification of explosives is a multi-aspect task. It involves choosing the method of information gathering, planning and conduction of experiments, choosing a classifier, formation...
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ISBN:
(纸本)9789549641523
The non-contact automatic on-line classification of explosives is a multi-aspect task. It involves choosing the method of information gathering, planning and conduction of experiments, choosing a classifier, formation of training and control samples, synthesis and reduction of recognition attributes, etc. This paper presents the results of conducted experiments for non-contact ultrasonic information gathering, formation of attribute spaces by means of wavelet transformations and an automatic classification of explosives.
The FRISC (abbreviated from FER RISC) is a reduced instruction set architecture designed to assist in elementary computer architecture teaching at the Faculty of Electrical Engineering and Computing. We propose a new ...
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A remote control system that can control a mobile robot in real time via the internet is proposed. To compensate for the network delay and counteract its impact on the teleoperation system, a predictive control scheme...
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A remote control system that can control a mobile robot in real time via the internet is proposed. To compensate for the network delay and counteract its impact on the teleoperation system, a predictive control scheme based on the modified Smith predictor proposed is selected. To ensure the stability and transparency of the system, a dynamic model manager is designed based on the information exchange between the sensors at the mas-ter and slave sides. To precisely predict the time delay, a new timer synchronization algorithm is proposed. To decrease delay- jitter, a new data buffer scheme is per-formed. Force feedback and a virtual predictive display are introduced to enhance the real-time efficiency of tele-operation. The usefulness and effectiveness of the pro-posed method and system are proven by teleoperation experiments via the internet over a long distance.
The performance exploration (T. Baumann et al., 2007) is becoming more important in embedded system design like networked system on chip (NoC) design. Due to the rising complexity it is necessary to accomplished the p...
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The performance exploration (T. Baumann et al., 2007) is becoming more important in embedded system design like networked system on chip (NoC) design. Due to the rising complexity it is necessary to accomplished the performance analysis (T. Baumann et al., 2007) already in the early design stages. The model based mission level design supports exactly this approach (MLDesigner). An overall executable model can be achieved consisting of function, architecture/performance and mission models. Missions describe the environment and concrete use cases which makes an early execution and thus a validation of the system (V. Zerbe et al.) possible. In the paper the focus is directed toward the standardized architecture components and the performance exploration. Furthermore the concept is illustrated on an example of an ethernet based system.
The paper presents a mathematical model for a series architecture hybrid solar vehicle, based on previous versions. A quasi piecewise linear parameter varying (qPWLPV) model was built, both in continuous and in discre...
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The paper presents a mathematical model for a series architecture hybrid solar vehicle, based on previous versions. A quasi piecewise linear parameter varying (qPWLPV) model was built, both in continuous and in discrete time. The advantage of the new modeling approach lies in a better handling of nonlinearities and answering model related analytical questions. controllability and stability of the switching system was studied. The model was tested throughout open loop simulations, it can further be used for developing control strategies for energy optimization.
This paper addresses the switching LPV techniques aiming to improve the control performance of a class of nonlinear systems that can be approximated by a family of linear parameter varying (LPV) models for the entire ...
This paper addresses the switching LPV techniques aiming to improve the control performance of a class of nonlinear systems that can be approximated by a family of linear parameter varying (LPV) models for the entire operation envelope. The proposed method provides a systematical strategy for the controller synthesis for such class system which can guarantee the global stability of the closed loop. The proposed method is further applied to the air path system of diesel engines which is critical for reducing the emissions. Due to its strong nonlinearity the working envelope of the air path system is divided into four subregions and in each subregion an LPV model is built. Accordingly, a gain scheduled LPV controller is synthesized for each nominal LPV model, the system is then regulated by hysteresis switching logic among a family of LPV controllers. The effectiveness of the proposed method is illustrated by simulations.
This paper addresses the issue on gain scheduled quasi linear parameter varying (LPV) control strategy for the air path system of diesel engines, which plays a critical role for the emission reduction of diesel engine...
This paper addresses the issue on gain scheduled quasi linear parameter varying (LPV) control strategy for the air path system of diesel engines, which plays a critical role for the emission reduction of diesel engines. Due to the strong nonlinearities of the underlying system, traditional linear control algorithm can not achieve a satisfactory control performance. In this paper, the considered nonlinear plant is approximated as an Hammerstein quasi-LPV system in the first place. An advanced quasi-LPV gain scheduled control strategy is applied to the underlying system. The effectiveness of the new control algorithm is illustrated by the simulations.
This paper presents a scheme for designing a robust decentralized PI controller for an industrial utility boiler system. First, a new method for designing robust decentralized PI controllers for uncertain LTI MIMO sys...
This paper presents a scheme for designing a robust decentralized PI controller for an industrial utility boiler system. First, a new method for designing robust decentralized PI controllers for uncertain LTI MIMO systems is presented. Sufficient conditions for closed-loop stability and diagonal dominance of a multivariable system are given. For each isolated subsystem a first order approximation is obtained. Then, achieving robust stability and closedloop diagonal dominance is formulated as local robust performance problems. It is shown by selecting time constants of the closed-loop isolated subsystems appropriately, these local robust performance problems are solved and the interactions between closed-loop stabilized subsystems are attenuated. The internal model control (IMC) method is used to design local PI controllers. The suggested design strategy is applicable to unstable systems as well. Thereafter, the nonlinear model of an industrial utility boiler is linearized about its operating points and the nonlinearity is modeled as uncertainty for a nominal LTI MIMO system. Using the new proposed method, a decentralized PI controller for the uncertain LTI nominal model is designed. The designed controller is applied to the real system. The simulation results show the effectiveness of the proposed methodology.
Brain emotional learning based intelligent controller (BELBIC) is based on computational model of limbic system in the mammalian brain. In recent years, this model was applied in many linear and nonlinear control appl...
Brain emotional learning based intelligent controller (BELBIC) is based on computational model of limbic system in the mammalian brain. In recent years, this model was applied in many linear and nonlinear control applications. Previous studies show that this controller has fast response, simple implementation and robustness with respect to disturbances. It is also possible to define emotional signal based on control application objectives. But in the previous studies, internal instability of this controller was not considered and control task were done in limited time period. In this article mathematical description of BELBIC is investigated and improved to avoid internal instability. Simulation and implementation of improved model was done on level plant. The obtained results showed that instability of model has been solved in the new model without loss of performance by using Integral Anti Windup (IAW).
Developing a practical fault diagnosis system for a power plant thermal system is important in ensuring safe and reliable operation of the whole power generation unit. It is a difficult task due to the complex structu...
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Developing a practical fault diagnosis system for a power plant thermal system is important in ensuring safe and reliable operation of the whole power generation unit. It is a difficult task due to the complex structure of the thermal system and the variable operating points of the system. Although artificial neural networks are very efficient in thermal system fault diagnosis, their applications for fault diagnosis usually consider only a single operating point (usually at the full rated load). Thus a fuzzy neural network approach for thermal system fault diagnosis under different operating points is investigated in this paper. An extended fuzzy fault symptom calculation method suitable for different load is discussed. The feedwater heater system of a 300 MW coal-fired power generation unit is taken as a fault diagnosis example. Several diagnosis tests for different faults under different operating points are carried out on a full-scope simulator of the power unit. The results under different operating points demonstrate the fault diagnosis ability of the fuzzy neural network method.
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