Improving the Performance of Controllers for Wind Turbines on Semi-Submersible Offshore Platforms: Fuzzy Supervisor Control

The use of sea wind energy is restricted by the limited availability of suitable sites in shallow waters. To overcome this challenge, wind turbines located on offshore semi-submersible platforms appear as a valuable option, as they also allow the exploitation of other resources like wave energy or aquaculture. Nevertheless, the literature addressing this kind of design is scarce, and the interactions of the wind turbine and the platform movements increase the complexity of the control system with respect to the wind turbines with fixed foundations. Within this context, fuzzy control is a promising alternative to deal with these issues. However, while fuzzy controllers can be an alternative to substitute conventional PI control, the latter is a well-known, robust choice for operators. In this sense, fuzzy controllers can be designed to work in collaboration with PI controllers to ease their adoption. To this end, this paper addresses those gaps in the literature by presenting a methodology, its application to enhance controllers for large-scale wind turbines in semi-submersible offshore platforms and the results attained. The methodology is based on the implementation of an integrated simulation tool, together with the definition of three indexes that describe the performance of the control system in the overall platform behaviour regarding key aspects of its exploitation. Using it, an Anti-Wind-Up algorithm was designed to improve the behaviour of the conventional controller and is presented and evaluated along a fuzzy supervisor controller. In this kind of configuration, the fuzzy controller modifies the values of the PI controller. Finally, a comparison of the performance using the reference PI and the improved PI, in both cases together with a fuzzy supervisor controller modifying their values, is presented and discussed, contributing to extend the state of the art of controllers for large-scale wind turbines on offshore semi-submersible platforms.

Fuzzy adapting rate for a neural emulator of nonlinear systems: real application on a chemical process

This paper deals with a new fuzzy adapting rate for a neural emulator of nonlinear systems with unknown dynamics. This method is based on an online intelligent adaptation by using a fuzzy supervisor. The satisfactory obtained simulation results are compared with those registered in the case of the classical choice of adapting rate and show very good emulation performances. An experimental validation of the proposed fuzzy adapting rate on a chemical reactor is also proposed to confirm the good performances in terms of speed of convergence and precision of representation.

Chaos control of the power system via sliding mode based on fuzzy supervisor

Purpose The purpose of this paper is to address the problem of control in a typical chaotic power system. Chaotic oscillations cannot only extremely endanger the stabilization of the power system but they can also not be controlled by adding the traditional controllers. So, the sliding mode control based on a fuzzy supervisor can sufficiently ensure perfect tracking and controlling in the presence of uncertainties. Closed-loop stability is proved using the Lyapunov stability theory. The simulation results show the effectiveness of the proposed method in damping chaotic oscillations of the power system, eliminating control signal chattering and also show less control effort in comparison with the methods considered in previous literatures. Design/methodology/approach The sliding mode control based on a fuzzy supervisor can sufficiently ensure perfect tracking and controlling in the presence of uncertainties. Closed-loop stability is proved using the Lyapunov stability theory. Findings Closed-loop stability is proved using the Lyapunov stability theory. The simulation results show the effectiveness of the proposed method in damping chaotic oscillations of power system, eliminating control signal chattering and also less control effort in comparison with the methods considered in previous literatures. Originality/value Main contributions of the paper are as follows: the chaotic behavior of power systems with two uncertainty parameters and tracking reference signal for the control of generator angle and the controller signal are discussed; designing sliding mode control based on a fuzzy supervisor in order to practically implement for the first time; while the generator speed is constant, the proposed controller will enable the power system to go in any desired trajectory for generator angle at first time; stability of the closed-loop sliding mode control based on the fuzzy supervisor system is proved using the Lyapunov stability theory; simulation of the proposed controller shows that the chattering is low control signal.