Current Issue : July-September Volume : 2026 Issue Number : 3 Articles : 5 Articles
The paper focuses on the practical benefits of using artificial neural networks (ANNs) in the control of unmanned aircraft vehicles (UAVs) and for the purposes of identification and surveillance. The presented methodology for modeling flight dynamics uses ANNs. Modeling of the object dynamics was based on experimental results obtained during flight tests. The aerodynamic g-loads were derived as a function of the flow parameters. The aim of ANN is to select weights of the neural network in such a way that it simultaneously generates all the necessary parameters to implement into the model with a high fidelity....
Maintaining high-precision line-of-sight pointing in airborne electro-optical gimbals remains a significant challenge due to the simultaneous presence of heterogeneous disturbances and strict mechanical structural constraints within complex dynamic conditions. Traditional anti-disturbance methods often struggle to provide fine-grained compensation for multi-source uncertainties where low-frequency lumped disturbances (e.g., friction and unbalanced torques) and high-frequency harmonic vibrations (e.g., engine-induced vibrations and aerodynamic gusts) are intricately coupled. To address these challenges, this paper proposes a refined disturbance separation-based composite control scheme. First, a deep-coupled aircraft–gimbal dynamics model is constructed to reveal the spectral separation characteristics of multi-source disturbances under the “moving base” effect. Second, a Refined Disturbance Observer architecture is developed by coupling an Extended State Observer with a Harmonic Disturbance Observer, enabling the decoupled separation and precise estimation of heterogeneous disturbances based on their spectral characteristics. Furthermore, a finite-time composite controller incorporating a Barrier Lyapunov Function is designed to guarantee that the system output strictly adheres to inherent mechanical structural boundaries. Numerical simulations confirm high-precision tracking and strict constraint satisfaction of the scheme....
This study carries out the research on event-triggered output feedback control tailored for discrete-time switched linear systems. A dynamic event-triggered mechanism (DETM) is utilized to mitigate the triggering frequency. To ensure stability and control performance, it is assumed that an event is triggered whenever the system undergoes a switch. First, the closed-loop stability of the underlying switched system with DETM is analyzed via the switched Lyapunov function method, followed by the establishment of a stability criterion for the system under arbitrary switching. Based on this criterion, a dynamic event-triggered output feedback control strategy is devised. The viability and application potential of our proposed control strategy is validated through simulation trials using a morphing aircraft model. Furthermore, when we pit dynamic event-triggered control (DETC) against its static (SETC) version, the proposed DETM reduces the trigger events and prolongs the inter-event intervals versus the SETM, while retaining nearly identical control accuracy and energy consumption, thus providing an efficient solution for resource-constrained networked control systems....
In this article, the motion control of ferromagnetic particles through varying a non-invasive magnetic field is addressed. Within an experimental test bench, three experiments are proposed to verify motion control, which consist of control of the distance between electromagnets, retention of particles over the flow, and manipulation of the direction of particle flow at a “Y”-type bifurcation emulating an “OR” gate. At each experimental stage, instrumented test benches were integrated with current, distance, and flow sensors, enabling measurement and feedback of the system’s physical variables. These benches were configured using pulse-width-modulation (PWM) and Proportional–Integral–Derivative (PID) controllers to regulate the current supplied to the electromagnets and, thereby, control the intensity of the induced electromagnetic field according to the requirements of each experiment. Different study cases were defined to analyze the operational limits of the system by varying the current influencing the electromagnetic field and the configuration of the electromagnets. The results describe the response of the magnetic field, the induced force, and the behavior of the suspended particles under each condition, providing elements to characterize the performance of the electromagnetic system in operational scenarios and contributing to the understanding of the phenomena associated with the non-invasive manipulation of ferromagnetic particles by means of controlled magnetic fields....
In order to address the challenges of frequency fluctuations and uneven voltage distributions in islanded microgrids, this paper proposes a distributed model predictive control (DMPC) strategy for secondary frequency and voltage regulation, and it adopts the virtual oscillator control (VOC) grid-forming method for the primary control. Firstly, the prediction model is constructed by integrating VOC dynamic equations with virtual inertia terms. Secondly, a cost function incorporating consensus constraints and tracking error terms is designed within the MPC framework, thereby achieving an optimal balance between dynamic consensus speed and steady-state tracking precision. Thirdly, the quadratic programming formulation strategy is used to solve the cost function optimization problem and update the DMPC outputs. Finally, simulation results verify that the proposed strategy ensures rapid frequency restoration and voltage regulation under sudden load variations and communication topology changes, while maintaining a smooth control process....
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