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Study On A VAV Terminal Controller Based On Embedded Technology In Central Air-conditioner

Posted on:2009-03-28Degree:MasterType:Thesis
Country:ChinaCandidate:P GuoFull Text:PDF
GTID:2178360245952455Subject:Control theory and control engineering
Abstract/Summary:PDF Full Text Request
The research of embedded system and the application of embedded technology are the newest research fields of computer application technology. The ARM microprocessor microprocessor is a good example of new generation embedded microprocessor. They are powerful, cabiner and power saving. The embedded system designed based on the new generation microprocessor can be implemented in much more fields than before. They are influencing every area of the world. Terminals of VAV is key equipment, it can accommodate supplying air quantity, compensate variational burthen of room to maintain temperature. In this document, we will introduce how to apply embedded technology in terminal control area. Besides this, we will also introduce how to design a new VAV terminal control system in central air-conditioner.Adopting S3C44BOX core of ARM7 of Samsung in the hardware design, the operatings peed and the capability of data processing of the controller are improved. The controller's kernel module, interface module and drivers depend on the functions is developed; used widely, open source real-time uClinux operation system, and multi-tasks capability is improved. especially the setup of crossing compilation environment and the transplantation of uClinux. Establishes the mathematical model of room. Simultaneity, contraposing the pressure independent terminals and room offer controller. The PID controlling strategy based on BP neural network is put forward. The simulation experiment shows that this the PID controlling strategy based on BP neural network has more excellent robust and better dynamic characteristics than traditional cascade PID control.
Keywords/Search Tags:VAV terminal controller, ARM7 micro processor S3C44BOX, Real-time uClinux, PID controlling strategy based on BPneural network
PDF Full Text Request
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