Download Fuzzy immune PID neural network control method based on boiler

Fuzzy immune PID neural network control
method based on boiler steam pressure
system
Third pacific-asia conference on circuits ,communications and
system, p.p. 1-5, July 2011
Outline
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Abstract
Introduction
Theory on fuzzy neural network (FNN)
Immune PID control
Fuzzy neural network immune PID control
Conclusions
References
ABSTRACT
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Steam pressure is a key point to keep the steam pressure constant in
various operation situations. Considering steam pressure with the time
delay and uncertainties, the sliding mode predictive control was used to
design the controller. The predictive control was used to deal with time
delay, the sliding mode control was used to deal with the uncertainties.
And the predictive control can reduce the chattering phenomenon of
sliding mode. This simulation results show that the proposed algorithm
can largely imporved the system response performance compared to the
single generalized predictive control
INTRODUCTION
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Boiler system is a complex industrial process, it has high nonlinearity,
large delay, strong coupling and load disturbance. Boiler steam pressure
power plant control system is a key link in the system, which directly
affect the turbine speed. In engineering, the current steam pressure
control system is mainly dominated by traditional PID control. In theory,
land-based power plant boiler, the use of intelligent control strategy has
been the boiler combustion system has been extensively studied [1-4].
Control of the ship boiler control system study is to PID [5], intelligent
control has lagged behind, only a few fuzzy or neural network PID
parameter calibration literature. However, due to the complexity of
fuzzy rules of precise formulation, making the control precision is often
not very satisfactory
THEORY ON FUZZY NEURAL NETWORK
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Neural network parallel computing, distributed storage, fault-tolerant
capability, with adaptive learning function and a series of advantages.
But generally speaking, the expression of neural network is not suitable
for rule-based knowledge, and therefore the neural network training,
because it is not already some experience to good use the knowledge,
often the initial weights can only be taken as zero, or the random
number , which increases the training time or network requirements into
a non-local extremum, which is insufficient neural network.
THEORY ON FUZZY NEURAL NETWORK
IMMUNE PID CONTROL
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Intelligent behavior of biological information
systems for science and engineering fields to provide
a reference for a variety of theoretical and technical
methods. Biological immune principle combined
with conventional PID control from the immune PID
control, can be mutually reinforcing in order to
further improve the control performance. PID control
is a reference biological immune system, immune
mechanism and design of a nonlinear control method.
FUZZY NEURAL NETWORK IMMUNE PID
CONTROL
CONCLUSIONS
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The system analyzes the dynamic characteristics of the boiler steam
pressure, based on the model through the mechanism of a ship boiler
steam pressure control system of intelligent control design, because we
are fully Use of the advantages of the fuzzy neural network, combined
with immune algorithm gives an adaptive, self-learning algorithm for
PID controller design, simulation shows that the control algorithm has
good control quality.
REFERENCES