  Nonlinear state space modeling of a nuclear reactor has been done for the
purpose of controlling its global power in load following mode. The nonlinear
state space model has been linearized at different percentage of reactor powers
and a novel fractional order (FO) fuzzy proportional integral derivative (PID)
controller is designed using real coded Genetic Algorithm (GA) to control the
reactor power level at various operating conditions. The effectiveness of using
the fuzzy FOPID controller over conventional fuzzy PID controllers has been
shown with numerical simulations. The controllers tuned with the highest power
models are shown to work well at other operating conditions as well; over the
lowest power model based design and hence are robust with respect to the
changes in nuclear reactor operating power levels. This paper also analyzes the
degradation of nuclear reactor power signal due to network induced random
delays in shared communication network and due to sensor noise while being
fed-back to the Reactor Regulating System (RRS). The effect of long range
dependence (LRD) which is a practical consideration for the stochastic
processes like network induced delay and sensor noise has been tackled by
optimum tuning of FO fuzzy PID controllers using GA, while also taking the
operating point shift into consideration.
