This paper proposes a newly adaptive single-neuron proportional integral derivative (SNPID) controller that uses fuzzy logic as an
adaptive system. The main problem of the classical controller is lacking the required robustness against disturbers, measurement
noise in industrial applications. The new formula of the proposed controller helps in fixing this problem based on the fuzzy
logic technique. In addition, the genetic algorithm (GA) is used to optimize parameters of the SNPID controller. Because of the
high demands on the availability and efficiency of electrical power production, the design of robust load-frequency controller is
becoming increasingly important due to its potential in increasing the reliability, maintainability and safety of power systems. So,
the proposed controller has been applied for load-frequency control (LFC) of a single-area power system. The effectiveness of the
proposed SNPID controller has been compared with the conventional controllers. The simulation results show that the proposed
controller approach provides better damping of oscillations with a smaller settling time. This confirms its superiority against its
counterparts. In addition, the results show the robustness of the proposed controller against the parametric variation of the system.
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