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    The development of an artificial organic networks toolkit for LabVIEW
    (2015)
    Ponce, Pedro
    ;
    Molina, Arturo
    ;
    Ponce, Hiram  
    Two of the most challenging problems that scientists and researchers face when they want to experiment with new cutting-edge algorithms are the time-consuming for encoding and the difficulties for linking them with other technologies and devices. In that sense, this article introduces the artificial organic networks toolkit for LabVIEW™ (AON-TL) from the implementation point of view. The toolkit is based on the framework provided by the artificial organic networks technique, giving it the potential to add new algorithms in the future based on this technique. Moreover, the toolkit inherits both the rapid prototyping and the easy-to-use characteristics of the LabVIEW™ software (e.g., graphical programming, transparent usage of other softwares and devices, built-in programming event-driven for user interfaces), to make it simple for the end-user. In fact, the article describes the global architecture of the toolkit, with particular emphasis in the software implementation of the so-called artificial hydrocarbon networks algorithm. Lastly, the article includes two case studies for engineering purposes (i.e., sensor characterization) and chemistry applications (i.e., blood–brain barrier partitioning data model) to show the usage of the toolkit and the potential scalability of the artificial organic networks technique. © 2015 Wiley Periodicals, Inc.
    Scopus© Citations 22  19  1
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    A novel robust liquid level controller for coupled-tanks systems using artificial hydrocarbon networks
    (2015)
    Ponce, Hiram  
    ;
    Ponce, Pedro
    ;
    Bastida, Héctor
    ;
    Molina, Arturo
    This paper proposes a robust liquid-level controller for coupled-tanks systems when dealing with variable discharge rates at the secondary tank, based on a hybrid fuzzy inference system that uses artificial hydrocarbon networks at the defuzzification step, so-called fuzzy-molecular control. The design methodology of the proposed controller is presented and discussed. In addition, a case study was run over the CE105 TecQuipment coupled-tanks system in order to implement and validate the fuzzy-molecular controller proposed in that work. A comparative evaluation with the proposed controller, a conventional PID controller specifically designed for this system and a QFT robust controller, was done. Also, a performance evaluation in terms of robustness, reference-tracking in a fixed operating point and reference-tracking in a variable operating point on-the-fly was run and analyzed. Results conclude that the proposed fuzzy-molecular controller deals with uncertainty and noise, can handle dynamics in operating point, a model of the plant is not required, and it is easy and simple to implement in comparison with other controllers in literature. To this end, the proposed fuzzy-molecular liquid-level controller inherits characteristics from fuzzy controllers and artificial hydrocarbon networks in order to implement an advanced robust and intelligent control system.
    Scopus© Citations 24  8  2
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    Doubly fed induction generator (DFIG) wind turbine controlled by artificial organic networks
    (2017)
    Ponce, Pedro
    ;
    Ponce, Hiram  
    ;
    Molina, Arturo
    The main goal of this paper is to show the control capabilities of artificial organic networks when they are applied to variable speed wind generators. Since doubly fed induction generator (DFIG) is one of the most important variable wind generators, it requires to include advanced controllers which allow to improve its performance during operation. On the other hand, the artificial organic controllers (AOC) are intelligent controllers based on ensembles of fuzzy inference systems and artificial hydrocarbon networks. To understand AOC, this paper introduces the fundamentals of artificial hydrocarbon networks, describes the fuzzy-molecular inference ensemble, and discusses artificial organic controllers when they are deployed in variable speed wind generators. Additionally, DFIG wind turbine model is completely derived in order to test the AOC. A conventional proportional–integral–derivative (PID) controller is compared with the proposed PID-based AOC (PID-AOC) for wind generators under linear and nonlinear wind profiles. Five parameters were used for evaluation: pitch angle, stator power, rotor power, generator’s speed and power coefficient. Results showed the superior control performance in wind generators when artificial organic networks are implemented. Particularly, the PID-AOC response obtained higher values of rotor and stator powers, small pitch angle response meaning less energy consumption, high power coefficient values, and smooth starting phase minimizing risks of damage in the DFIG. The proposed PID-AOC can be applied in DFIG to minimize the undesired fluctuation on the electric grid, to reduce the mechanical stress in the blades preventing mechanical damages and to perform good sensitivity when noise in the wind is included. © 2017 Springer-Verlag Berlin Heidelberg
    Scopus© Citations 30  9  1
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    A Robust Control Scheme for Renewable-Based Distributed Generators Using Artificial Hydrocarbon Networks
    (2019)
    Rosales, Antonio
    ;
    Ponce, Pedro
    ;
    Ponce, Hiram  
    ;
    Molina, Arturo
    Distributed generators (DGs) based on renewable energy systems such as wind turbines, solar panels, and storage systems, are key in transforming the current electric grid into a green and sustainable network. These DGs are called inverter-interfaced systems because they are integrated into the grid through power converters. However, inverter-interfaced systems lack inertia, deteriorating the stability of the grid as frequency and voltage oscillations emerge. Additionally, when DGs are connected to the grid, its robustness against unbalanced conditions must to be ensured. This paper presents a robust control scheme for power regulation in DGs, which includes inertia and operates under unbalanced conditions. The proposed scheme integrates a robust control algorithm to ensured power regulation, despite unbalanced voltages. The control algorithm is an artificial hydrocarbon network controller, which is a chemically-inspired technique, based on carbon networks, that provides stability, robustness, and accuracy. The robustness and stability of the proposed control scheme are tested using Lyapunov techniques. Simulation, considering one- and three-phase voltage sags, is executed to validate the performance of the control scheme.
    Scopus© Citations 2  12  1
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    Designing a Robust Controller Using SMC and Fuzzy Artificial Organic Networks for Brushed DC Motors
    (2020)
    Ponce, Pedro
    ;
    Rosales, J. Antonio
    ;
    Molina, Arturo
    ;
    Ponce, Hiram  
    ;
    MacCleery, Brian
    Electric direct-current (DC) drives based on DC motor are extremely important in the manufacturing process, so it must be crucial to increase their performance when they are working on load disturbances or the DC motor's parameters change. Usually, several load torque suddenly appears when electric drives are operating in a speed closed-loop, so robust controllers are required to keep the speed high-performance. One of the most well-known robust strategies is the sliding mode controller (SMC), which works under discontinue operation. This controller can handle disturbances and variations in the plant's parameters, so the controller has robust performance. Nevertheless, it has some disadvantages (chattering). Therefore, this paper proposed a fuzzy logic controller (FLC) that includes an artificial organic network for adjusting the command signal of the SMC. The proposed controller gives a smooth signal that decrements the chattering in the SMC. The stability condition that is based on Lyapunov of the DC motor is driven is evaluated; besides, the stability margins are calculated. The proposed controller is designed using co-simulation and a real testbed since co-simulation is an extremely useful tool in academia and industry allows to move from co-simulation to real implementation in short period of time. Moreover, there are several universities and industries that adopt co-simulation as the main step to design prototypes. Thus, engineering students and designers are able to achieve excellent results when they design rapid and functional prototypes. For instance, co-simulation based on Multisim leads to design directly printed circuit boards so engineering students or designers could swiftly get an experimental DC drive. The experimental results using this platform show excellent DC-drive performance when the load torque disturbances are suddenly applied to the system. As a result, the proposed controller based on fuzzy artificial organic and SMC allows for adjusting the command signal that improves the dynamic response in DC drives. The experimental response using the sliding-mode controller with fuzzy artificial organic networks is compared against an auto-tuning, Proportional-Integral-Derivative (PID), which is a conventional controller. The PID controller is the most implemented controller in several industries, so this proposal can contribute to improving manufacturing applications, such as micro-computer numerical control (CNC) machines. Moreover, the proposed robust controller achieves a superior-speed response under the whole tested scenarios. Finally, the presented design methodology based on co-simulation could be used by universities and industry for validating and implementing advanced control systems in DC drives. © 2020 by the author.
    Scopus© Citations 8  8  2