In recent years, the rapid development in contemporary technology has brought nano quadcopters with high agility. This paper presents a new differential flatness-based singleinputfuzzylogiccontroller (SFLC) struct...
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In recent years, the rapid development in contemporary technology has brought nano quadcopters with high agility. This paper presents a new differential flatness-based singleinputfuzzylogiccontroller (SFLC) structure for aggressive maneuvering control alongside its real-world application on Crazyflie 2.1 nano quadcopter. We propose both Type-1 and Interval Type-2 SFLCs as the primary controllers in the flight control system, which are built on the concept of differential flatness. We investigate how the design parameters of SFLCs shape the characteristics of the fuzzy mapping through a geometric approach by analyzing the region and level of aggressiveness/smoothness. Based on the analysis, we present simple tuning guidelines and then design fuzzylogic-based flight control systems, which were implemented as onboard real-time controllers. Finally, we evaluate the performance of SFLCs in comparison with their crisp differential flatness-based nonlinear counterparts for four trajectories with distinct dynamics and shapes in the real world. The presented comparative experimental results clearly show the performance improvements when the proposed T1 and IT2 SFLCs are deployed for real-time aggressive maneuvering. (c) 2022 Elsevier B.V. All rights reserved
Rotational speed sensor is one of the most important components used in wind energy conversion system control strategies. The latter is very expensive and may be faulty due to the harsh environment working, causing by...
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Rotational speed sensor is one of the most important components used in wind energy conversion system control strategies. The latter is very expensive and may be faulty due to the harsh environment working, causing by that a low efficiency operation of the system. The use of a speed estimator or an observer may be a good alternative solution for the use either in sensorless control or detecting the sensor failure or degradation (FDI and FTC), provided that the observer is robust and ensures high rotational speed estimation accuracy. This paper presents a comprehensive study to solve the optimization problem of a model reference adaptive speed (MRAS) observer in a typical wind energy generation system based on permanent magnet synchronous generator using five adaptation mechanisms: The first one is the classical MRAS observer;it is based on proportional-integral (PI) controller. The second one uses a fuzzylogiccontroller (FLC) with two inputs. The third one uses the single-input fuzzy logic controller which represents the simplification of the conventional FLC. The fourth one uses the sliding mode controller, and the last one uses the super-twisting algorithm. A detailed comparison between the five adaptation mechanisms is carried out. The obtained results show a good estimation stability as well as a fast speed estimation at dynamic regime for the improved adaptation mechanisms compared with the conventional PI controller.
Despite its excellent performance as a controller for linear and non-linear systems, the fuzzylogiccontroller (FLC) has certain limitations. For instance, large-scale complex fuzzy systems like multi-input, single-o...
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Despite its excellent performance as a controller for linear and non-linear systems, the fuzzylogiccontroller (FLC) has certain limitations. For instance, large-scale complex fuzzy systems like multi-input, single-output, or multi-output systems create complex applications with large amounts of rules. This study presents a novel framework that reduces the number of rules for an FLC based on a single-input fuzzy logic controller. controller parameters are then optimized based on a genetic algorithm, and subsequently eliminating the trial and error approach involved in controller design. Reliability of the proposed method is verified with three complex and strong nonlinear systems, i.e. a twin-rotor multi-input multi-output system, an inverted pendulum and cart system, and permanent magnet linear synchronous motor systems. Simulation and experiment results demonstrate that the proposed framework performs well in terms of the number of rules in the rules base and robustness. Moreover, the fuzzy rule number of the proposed approach decreases only with the number of linguistic labels for the membership function.
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