## 5 Discussion and Conclusions
This is because they can develop the adaptation in systems where it is not possible to have a mathematical model, organize the information for analysis and prediction of the response of the controller, as well as optimize the solution of a set of solutions imitating the patterns of biological behavior of the species. The main contribution of an ES simplifies the non-linearity of the variables of a system. An FLC is based on brain functions such as language, processes information and formulates solutions according to programmed rules defined by the experience of human beings. An ANN bases its operation on the self-learning of its connection weights, so they predict changes in their input variables and as a result, has a faster response. An ISA uses characteristic behavioral patterns of nature to optimize the search for the appropriate solution. The wind turbines of last generation, due to their high altitude, have faced intense gusts of wind that generate multiple oscillations, mechanical stress and risks for the system itself; these have, therefore, required a very precise driver for these operating conditions. The use of ES has contributed to give solutions to this problem, thanks to its adaptability to sudden changes since its control action does not depend on a mathematical model. Because of this analysis, we obtained the assertion that a wind turbine system works in a stable state, when the winds are constant and in a transient state in the presence of gusts or turbulence. An MPPT controller must be efficient in both cases. The recurrent technique by diverse authors is the combination of a conventional PID controller with an expert controller. A conventional PID controller can obtain a high precision in stable state, and an expert system, to not consider the perturbations of the environment, has a faster response in transient state. For this purpose, it is more common to use the PID command with FLC, the controllers can work in parallel by adding their control signals or by selecting the type of response desired according to the state of the system. It is also convenient to use an expert FLC, ANN or ISA system to adjust the control gains of a PID to work stably in different wind speed ranges. Another option is the use of hierarchical systems, where several controllers are connected in cascade, the output of one is the input of the next, in this way different types of controllers can be combined, so that the final control signal is optimized. All these techniques are used both for a simultaneous operation of the blades, as for an individual pitch control. The use of ANN in wind power systems has been very successful in predicting air velocity, which is very valuable in anticipating the control response. The most complete control proposals obtain the value of the angle of inclination using only values obtained directly from sensors. The ISAs are used to a greater extent for the learning of the weights in ANNs or for the efficient search of the optimal solution among a set of solutions. The combination of these systems is a factor of success in obtaining the maximum power of a wind turbine, since they have higher response time and efficiency. Review, methodology and Writing--Original Draft preparation, E.C.-N.; formal analysis and validation, R.V.C.-S.; discussion, data curation and Writing--Review and Editing, M.T.-P. and J.G.R.-M.; resources, supervision, project administration and funding acquisition, J.C.J.-C. This research received no external funding. This work was supported by Departamento de Investigacion y Posgrado of the Facultad de Ingenieria and Universidad Autonoma de Queretaro. Authors declare no conflict of interest.