کد مقاله g186
عنوان مقاله:
Development of Self-Tuning Intelligent PID Controller Based on BPNN for Indoor Air Quality Control
سال ارائه: 2013 نوع مقاله: ژورنال گزارش فارسی: دارد
کلید واژه : کنترل کننده PID با شبکه عصبی ، سیستم حلقه بسته با کنترل کننده ی PID تطبیقی
Back-propagation, neural network, PID control, IAQ control, stability analysis
Abstract—For those who spend most of their time working
indoors, the indoor air quality (IAQ) could affect their
working efficiency and health. This paper presents an
intelligent proportional-integral-derivative (PID) controller
for IAQ control. Different from the traditional PID controller,
this novel controller combined with Back-Propagation Neural
Networks (BPNN) technology will regulate the PID
parameters k
p
, k
i
, kd automatically. In the present study, the
algorithm of the BPNN-based PID controller is first discussed
in details, and the control performance is then tested by
simulation using MATLAB. The difficulty in IAQ control is
the existence of control disturbance, time delay and
measurement errors. The results show that the combined
control algorithm has better performance on the systemic
stability, disturbance resistance, fast response rate and small
overshoot compared with traditional PID controller.
Keywords—Back-propagation, neural network, PID
control, IAQ control, stability analysis.
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