Neuron-Adaptive PID Based Speed Control of SCSG Wind Turbine System

Abstract

In searching for methods to increase the power capacity of wind power generation system, superconducting synchronous generator (SCSG) has appeared to be an attractive candidate to develop large-scale wind turbine due to its high energy density and unprecedented advantages in weight and size. In this paper, a high-temperature superconducting technology based large-scale wind turbine is considered and its physical structure and characteristics are analyzed. A simple yet effective single neuron-adaptive PID control scheme with Delta learning mechanism is proposed for the speed control of SCSG based wind power system, in which the RBF neural network (NN) is employed to estimate the uncertain but continuous functions. Compared with the conventional PID control method, the simulation results of the proposed approach show a better performance in tracking the wind speed and maintaining a stable tip-speed ratio, therefore, achieving the maximum wind energy utilization.

A Review of the Motion Planning and Control Methods for Automated Vehicles

“…These challenges arise due to the constraints of the vehicle model, instability of the surrounding environment, and non-integrity constraints [58]. Zuo et al [59] developed a path-tracking control method using a single neuron-adaptive PID to address issues related to frequent control oscillations. They also included a reasonable dead band to ensure accurate frontwheel corner control.…”

Undisturbed Switching Control Method of Superheated Steam Temperature Systems

“…The learning strategy has a great influence on the adaptive ability and stability of the controller. The adjustment of the weight coefficient is implemented based on Supervised Hebb learning rules [3,[9][10][11]. Practice results show that the online learning correction of PSD parameters are mainly related to Δ ( ) and Δ 2 ( ).…”

“…The thermal power plant boiler is a complex object with nonlinear coupling, large lag, multivariable, and multi-interference. At present, superheated steam temperature control systems of most domestic thermal power plant boiler still use PID controllers, which has many shortcomings in control quality [1][2][3][4][5][6][7][8][9][10][11][12][13], such as the lack of timely adjustment and excessive overshoot. Nowadays, many scholars have proposed many advanced control algorithm strategies for boiler superheated steam temperature control systems.…”

“…An application of the boiler steam temperature control system has been modeled as the switching control plant, and a disturbance compensator observer from the sliding mode dynamics has been developed to enhance robustness [6]. Therefore, how to ensure the balance between control accuracy and real-time performance of superheated steam temperature systems in thermal power plants is crucial [9][10][11][12][13]. Inspired by the switching system, this paper introduces the switching rules into the controller design process of the superheated steam temperature system to achieve the undisturbed switching between multiple controllers.…”

Rotor dynamic balancing control method based on fuzzy auto-tuning single neuron PID

“…The activation function of the single neuron network is a linear function, and the output of the single neuron is linearly related to the local field [10]. In the control field, the single neuron control expression is…”