1,720,966 research outputs found
Distributed adaptive consensus for multi-agent systems subject to uncertainties
No full textResearch on cooperative control of multi-agent systems has drawn increased attention from control engineers in recent decades. Inspired by natural phenomena, this research has been developed to become more practical and reliable in implementation. Consensus is one of the most active and very crucial research topics in cooperative control of multi-agent systems. One of the unavoidable problems in developing consensus control for multi-agent systems is the presence of uncertainties in the dynamic models. Adaptive control is a research line applied to solve consensus problems for multi-agent systems subject to uncertainties. In this thesis, we establish a distributed adaptive consensus framework for multi-agent systems with uncertain dynamics. There are two main problems in designing distributed adaptive consensus control for general multi-agent systems. First, the adaptive law cannot always be implemented in a distributed fashion because it depends on the gradient of a (centrally constructed) Lyapunov function. Consequently, distributed adaptive consensus can only be applied for limited cases. In this thesis, we establish a distributed adaptive consensus framework to overcome this problem by proposing a novel distributed adaptive scheme that does not rely on the gradient of a Lyapunov function. An application of our framework is presented to solve the consensus problem in second-order multi-agent systems under a directed topology. The second problem is the presence of nonlinearly parameterized dynamics in multi-agent systems. It is always difficult to handle nonlinearly parameterized uncertainties in adaptive control. Some results have been obtained for special cases. In addition, none of the existing results are applicable to networked systems with nonlinearly parameterized dynamics. In this thesis, we develop a distributed adaptive framework for multi-agent systems subject to nonlinearly parameterized uncertainties. The linear parameterization assumption is removed by proposing a novel distributed adaptive update law. Therefore, our scheme is more applicable to general nonlinear multi-agent systems. A specific implementation of our framework is presented for nonlinear second-order multi-agent systems. To illustrate our approaches, we present some numerical examples and simulations with various settings
Adaptive Control of Unmanned Aerial Vehicles with Varying Payload and Full Parametric Uncertainties
No full textThis article investigates an adaptive tracking control problem for a six degrees of freedom (6-DOF) nonlinear quadrotor unmanned aerial vehicle (UAV) with a variable payload mass. The changing payload introduces time-varying parametric uncertainties into the dynamical model, rendering a static control strategy no longer effective. To handle this issue, two adaptive schemes are developed to maintain the uncertainties in the translational and rotational dynamics. Initially, a virtual proportional derivative (PD) is designed to stabilize the horizontal position; however, due to an unknown and time-varying mass, an adaptive controller is proposed to generate the total thrust of the UAV. Furthermore, an adaptive controller is designed for the rotational dynamics, to handle parametric uncertainties, such as inertia and external disturbance parameters. In both schemes, a standard adaptive scheme using the certainty equivalence principle is extended and designed. A stability analysis was conducted with rigorous analytical proofs to show the performance of our proposed controllers, and simulations were implemented to assess the performance against other existing methods. Tracking fitness and total control efforts were calculated and compared with closed-loop adaptive tracking control (CLATC) and adaptive sliding mode control (ASMC). The results indicated that the proposed design better maintained UAV stability
Evolution of Vortex Structures Generated by a Rigid Flapping Wing with a Winglet in Quiescent Water
Full text linkThis study aims to the utilization of vortex structures generated through wing flapping for achieving sustainable flight, and the motivation is elicited by the phenomenon observed in natural flyers. The vortex structures in the flow field generated by a flapping rigid wing are captured using vorticity and the LAMDA2 criterion. The study investigates a comparative analysis between a wing both with and without a winglet. Moreover, the influence of flapping frequency is examined as well. For the experiments, particle image velocimetry (PIV) measurements are employed for the flow field around mechanical flapping motion in a quiescent water condition. The flapping mechanism has one-degree freedom, showing a 1:3 ratio in motion, and tested wings at 1.5 and 2.0 Hz. A “modified” vortex filamentation and fragmentation phenomenon is proposed as a significant finding in the present study, based on a comprehensive analysis of the flow field around the wing with a winglet
Neural network based corrosion modeling of Stainless Steel 316L elbow using electric field mapping data
No full textAbstract Stainless steel (SS) is widely employed in industrial applications that demand superior corrosion resistance. Modeling its corrosion behavior in common structural and various operational scenarios is beneficial to provide wall-thickness (WT) information, thus leading to a predictive asset integrity regime. In this spirit, an approach to model the corrosion behavior of SS 316L using artificial neural networks (ANNs) is developed, whereby saline water at different concentrations is flown through an elbow structure at different flow rates and salt concentrations. Voltage, current, and temperature data are recorded hourly using electric field mapping (EFM) pins installed on the elbow surface, which serve as training data for the ANNs. The performance of corrosion modeling is verified by comparing the predicted WT with actual measurements obtained from experimental tests. The results show the exceptional performance of the proposed single ANN model to predict WT. The error is calculated by comparing the estimated WT and actual measurement recorded, where the maximum error for each setting is range from 0.5363 to 0.7535 % . RMSE and MAE values of each pin in every setting are also computed such that the maximum values of RMSE and MAE are 0.0271 and 0.0266, respectively. Moreover, a concise account of the observed scale formation is also reported. This comprehensive study contributes to a better understanding of SS 316L corrosion and offers valuable insights for developing efficient strategies to prevent corrosion in industrial environments. By accurately predicting WT loss using ANNs, this approach enables proactive maintenance planning, minimizing the risk of structural failures and ensuring the extended sustainability of industrial assets
An Adaptive Scheme to Estimate Unknown Parameters of an Unmanned Aerial Vehicle
Full text linkThis paper deals with tracking control problem for six degrees of freedom (6-DOF) nonlinear quadrotor unmanned aerial vehicle (UAV). A virtual control design using PD controller is proposed for tracking control position. The rotational dynamics of UAV is considered to have several unknown parameters such as propeller inertia, rotational drag coefficient and an external disturbance parameter. To handle this issue, an adaptive scheme using the certainty equivalence principle is developed. The basic idea behind this scheme is to cancel the nonlinear term by applying a similar nonlinear structure in the feedback control design. The unknown parameters are replaced by estimated parameters generated by adaptation law. The rigorous theoretical design and simulation results are presented to demonstrate the effectiveness of the controller
Robust Adaptive Fault-Tolerant Control of Quadrotor Unmanned Aerial Vehicles
No full textThe paper introduces a robust adaptive fault-tolerant control system for the six-degree-of-freedom (six-DOF) dynamics of quadrotor unmanned aerial vehicles (UAVs), incorporating disturbances and abrupt actuator faults to represent real-world conditions. The proposed control scheme employs robust control terms to manage unknown disturbances. However, robust control performance may degrade due to sudden fault impacts. To handle this issue, we introduce adaptive laws to ensure continuous adaptation. The control architecture ensures the tracking system’s stability by combining robust control using sliding-mode control (SMC) with adaptive control developed using the certainty equivalence principle. The sliding-surface error limits the adaptive laws, in which the convergence of estimated parameters to the actual unknown variables is not required as they fully rely on the convergence of the tracking error. We provide rigorous mathematics to validate the proposed control design. Furthermore, we conduct numerical simulations for a quadrotor UAV to showcase the effectiveness of the proposed scheme. The results demonstrate the efficacy of the proposed design in handling external disturbances and abrupt actuator faults
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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