Design and Optimization of a Neuro-Fuzzy System for the Control of an Electromechanical Plant

One characteristic of neuro-fuzzy systems is the possibility of incorporating preliminary information in their structure as well as being able to establish an initial configuration to carry out the training. In this regard, the strategy to establish the configuration of the fuzzy system is a relevant aspect. This document displays the design and implementation of a neuro-fuzzy controller based on Boolean relations to regulate the angular position in an electromechanical plant, composed by a motor coupled to inertia with friction (a widely studied plant that serves to show the control system design process). The structure of fuzzy systems based on Boolean relations considers the operation of sensors and actuators present in the control system. In this way, the initial configuration of fuzzy controller can be determined. In order to perform the optimization of the neuro-fuzzy controller, the continuous plant model is converted to discrete time to be included in the closed-loop controller training equations. For the design process, first the optimization of a Proportional Integral (PI) linear controller is carried out. Thus, linear controller parameters are employed to establish the structure and initial configuration of the neuro-fuzzy controller. The optimization process also includes weighting factors for error and control action in such a way that allows having different system responses. Considering the structure of the control system, the optimization algorithm (training algorithm) employed is dynamic back propagation. The results via simulations show that optimization is achieved in the linear and neuro-fuzzy controllers using different weighting values for the error signal and control action. It is also observed that the proposed control strategy allows disturbance rejection.

Improved sliding mode power control of doubly-fed-induction generator under wind speed variation

<p><span lang="EN-US">Due to drawbacks of classical linear controller like proportional-integral (PI), many studies have been used non-linear controller specially when it comes to robustness, but this is less efficient in sliding mode controller (SM) due to the sign function, this function is known as a problem chattering phenomenon, this main disadvantage it can be compensated by Lyapunov backstepping condition, This paper presents nonlinear power control strategy of the doubly-fed-induction generator (DFIG) for wind application system (WAS) using sliding mode combining with backstepping controller (SM-BS) to control produced statoric powers to mitigate unnecessary chattering effects inherent in traditional SMC, to check the effectiveness of the controller, we compare performance of sliding mode controller and sliding mode controller combining with backstepping (SM-BS) in terms of required reference tracking, robustness under parametric variations of the generator, sensitivity to perturbations and reaction to speed variations under investigating further of the chattering phenomenon.</span></p>

Gain-Scheduled Position Control of a Pneumatic Muscle Actuator

Pneumatic artificial muscles (PAMs) are high power-to-weight ratio actuators with considerable potential in biomimetic robotics and orthotics due to their similarities with human skeletal muscle. However, precise position control is difficult to achieve due to the highly nonlinear nature of the actuators and the pneumatic systems driving them. A wide range of nonlinear controllers have been proposed to-date, but none have been shown to be entirely satisfactory, and are often optimised for only one region of the PAM’s travel. In this paper, a gain-scheduled position controller is designed that aims to achieve equal tracking performance across the entire travel of the PAM. Selected scheduling variables include actuator displacement and error direction, with controller gains defined by ‘normalisation curves’ determined by data from open-loop characterisation tests. The experimental system consists of a Festo PAM, a pair of on-off valves driven by pulse-width modulated signals, and sensors for PAM displacement and pressure. Controller performance is tested using several dynamic position tracking tests, and the results are compared to an equivalent linear controller. The gain-scheduled approach successfully counteracts the differing inflation / deflation dynamics of the system, showing improved tracking performance over the linear controller with considerably less variability due to operating region.

Synthesis of non-linear controller to energy efficiency for damped-elastic-jointed inverted pendulum

In the paper we propose a synthetic way of the nonlinear controller for the damped-elastic-jointed inverted pendulum. The controller is designed based on the synergistic approach, the global variables are built on the asymptotically stable manifolds and the fast acting objective function is energy efficient. The effectiveness of the export method is proven through simulation results and compared with other methods.

Implementation of non-linear controller on photovoltaic maximum power point tracker for energy storage equipment charger

The portable energy storage system is an infrastructure for providing electrical energy needed to support the recovery process after a natural disaster. This system is a battery arrangement that can be recharged using locally available primary energy sources such as photovoltaic. The main problem in using photovoltaic as the power source for this equipment is to increase the efficiency of power extraction (energy harvesting) during the recharging process. Traditionally, to obtain maximum extraction conditions, conventional linear maximum power point tracker (MPPT) mechanisms such as PID-based MPPT and the like are used. However, if the PV and the storage system works at various locations with environmental conditions behave unusually, the conventional MPPT cannot work accurately and optimally. In this paper, the Fuzzy method for constructing a nonlinear controller-based MPPT was studied. The step size of the tracking process in the conventional MPPT P&O method is modified by involving the fuzzy algorithm. This algorithm then is applied to a DC-DC converter to test the performance criteria such as the response and efficiency of the resulting power extraction. The testing and computer simulations show that the conventional MPPT mechanism can provide prospective results through modification and application of a non-linear controller.