ZnO has many potential applications, such as, solar cells, photocatalysts, chemical sensors and biosensors. However, to extend its visible light response is still a great challenge. In this paper, ZnO nanosheets were ...
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Quality-relevant monitoring for multiphase batch processes is necessary. Between-phase transitions carry significant quality information and need particular attentions. In this paper, a Just-in-time-learning (JITL) ba...
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ISBN:
(纸本)9781479932757
Quality-relevant monitoring for multiphase batch processes is necessary. Between-phase transitions carry significant quality information and need particular attentions. In this paper, a Just-in-time-learning (JITL) based method is introduced to identify transitions and update modeling dataset of transitions. Due to the non-Gaussian distribution of the samples in the local model, a PLS-SVDD based method is proposed for modeling and monitoring. Fed-batch penicillin fermentation process is tested for performance evaluation of the proposed method.
We study the performance of GaN-based p i n ultraviolet （UV） photodetectors （PDs） with a 60 nm thin ptype contact layer grown on patterned sapphire substrate （PSS）. The PDs on PSS exhibit a low dark current of -...
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We study the performance of GaN-based p i n ultraviolet （UV） photodetectors （PDs） with a 60 nm thin ptype contact layer grown on patterned sapphire substrate （PSS）. The PDs on PSS exhibit a low dark current of -2 pA under a bias of -5 V, a large UV/visible rejection ratio of-7× 10^3, and a high-quantum efficiency of -40% at 365 nm under zero bias. The average quantum efficiency of the PDs still remains above 20% in the deep-UV region from 280 to 360 nm. In addition, the noise characteristics of the PDs are also discussed, and the corresponding specific detectivities limited by the thermal noise and the low-frequency 1/f noise are calculated.
Parameter selection is an essential work which influences the performance of a particle swarm optimization algorithm(PSO). In evolutionary equations of a PSO algorithm, two uniform random numbers are employed to perfo...
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Parameter selection is an essential work which influences the performance of a particle swarm optimization algorithm(PSO). In evolutionary equations of a PSO algorithm, two uniform random numbers are employed to perform the global exploration search and local exploitation, and then the particles can only fly in a limited search space. In this paper, a novel strategy is proposed by introducing Gaussian distribution operators into PSO and new evolutionary equations are given, which can expand the activity range of particles and increase the probability of finding global solutions of problems. Simulation results show the proposed method is effective and efficient compared with other variants of PSO.
This study suggests a moving horizon H8 control scheme for variable speed wind turbines above the rated wind speed to maintain the output power at the rated value for variable operating points. A constrainedH8 control...
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To improve the connected-grid wind power quality as well as profit,the pumped storage station is used to configure the wind farmThe economical benefit and deviation models are built as objective functions,the united o...
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To improve the connected-grid wind power quality as well as profit,the pumped storage station is used to configure the wind farmThe economical benefit and deviation models are built as objective functions,the united operation is based on fuzzy multi-objective evolutionary algorithm(FMOEA)In order to outstand method advantages,the results are compared with the consequences from each objective function that are optimized respectivelyThe analysis shows that a wind farm with a pumped storage station is as a combined system and uses FMOEA,not only improving profit,but also paying attention to reduce deviation so that can achieve the total net profit increase
This paper proposed an adaptive neural network controller to maintain the chilled water temperature in heating, ventilation and air conditioning(HVAC) systems. The heat transfer behavior between chilled water and refr...
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This paper proposed an adaptive neural network controller to maintain the chilled water temperature in heating, ventilation and air conditioning(HVAC) systems. The heat transfer behavior between chilled water and refrigerant is highly nonlinear. It is significant to design a controller that can handle the nonlinearity of the process. Firstly, by analyzing the heat transfer process from mechanism perspective, factors which influence the process have been obtained. Then the frequency of the compressor is manipulated to control the chilled water temperature in the outlet of the evaporator and uncontrolled variables are taken into the neural network controller. With a novel adaptive law for the neural network controller, both the nonlinear phenomenon and disturbance of uncontrolled variables can be handled. To further illustrate the performance of the NN controller, experiment was conducted on a pilot HVAC system. Then the result was compared with that of conventional PID controller. Real time experiment result showed the effectiveness of the adaptive neural network controller.
This paper investigates the modeling and H ∞ composite control of the coupled hysteretic dynamics in a piezoelectric micro-displacement system (PMS). First, the coupled multi-field hysteretic dynamics with physical ...
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This paper investigates the modeling and H ∞ composite control of the coupled hysteretic dynamics in a piezoelectric micro-displacement system (PMS). First, the coupled multi-field hysteretic dynamics with physical meanings is presented for PMS. Next, the composite control analysis of the hysteretic dynamics is proposed. Then, a H ∞ synthesis controller is designed by using the simplified hysteretic dynamics. To enhance the H ∞ performance, the inversion-based feedforward compensation is augmented. The proposed H ∞ feedback control and the inversion-based feedforward can be designed separately. Finally, the experimental studies are provided to demonstrate the proposed H ∞ composite control approach.
This paper focuses on the problem of cluster synchronization of a class of complex dynamical *** on impulsive control theory and a comparison theorem, generic criteria for cluster synchronization are derived. It is sh...
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This paper focuses on the problem of cluster synchronization of a class of complex dynamical *** on impulsive control theory and a comparison theorem, generic criteria for cluster synchronization are derived. It is shown that these criteria provide a novel and effective control approach to synchronize a general dynamical network to a cluster synchronization manifold by exposing the relationship between cluster synchronization, the impulsive intervals,and the graph topology.
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