arXiv subjects

Ahmed A. Elgohary

Publications and source records attributed to Ahmed A. Elgohary.

8 recordsLinked to original sources

arXiv2026

First Experimental Demonstration of Natural Hovering Extremum Seeking: A New Paradigm in Flapping Flight Physics

In this article, we report the first attempt of experimental validation of the recently emerged new paradigm in hovering and flapping flight physics called "Natural Hovering Extremum Seeking (NH-ES)" [doi.org/10.1103/4dm4-kc4g], which theorized that stable hovering flight physics observed in nature by flapping insects and hummingbirds can be characterized and emulated via a model-free, real-time, computationally-basic, sensory-based feedback mechanism that only needs the built-in natural oscillations of the flapping wing motion as both the control and the propulsion input. We run experiments of moth-like, light bulb source-seeking, on a flapping-wing body in a total model-free setting that is agnostic to morphological parameters and body/aerodynamic models. That is, the flapping performer (e.g., insects or hummingbirds) do not perceive internal or external governing physical equations, system states, models or parameters. Moreover, in addition to experimentally demonstrating the NH-ES paradigm in vertical motion as predicted by simulations in our earlier foundational work, we provide experiments that suggest the expansion of the NH-ES theory to longitudinal mode by yielding altitude and pitch stabilization in hovering flight. In the presented experiments, the flapper seeks, then hovers, around the light bulb source like a moth, needing only feedback of sensory measurements of light intensity taken by a simple sensor mounted on the head of the flapper body. Our experiment confirms that NH-ES needs only instantaneous, local measurement of the physical signal (e.g., light) as a feedback to perform source-seeking and does not need measurements, estimations or reference information of states, angles, altitude, or coordinates of the flapper system or source, nor does it need any global information such as access to GPS. Our results were also achieved under delay and noise effects.

cs.RO↗

arXiv2026

Model-Free Optimization and Control of Rigid Body Dynamics: An Extremum Seeking for Vibrational Stabilization Approach

In this paper, we introduce a model-free, real-time, dynamic optimization and control method for a class of rigid body dynamics. Our method is based on a recent extremum seeking control for vibrational stabilization (ESC-VS) approach that is applicable to a class of second-order mechanical systems. The new ESC-VS method is able to stabilize a rigid body dynamic system about the optimal state of an objective function that can be unknown expression-wise, but assessable through measurements; the ESC-VS is operable by using only one perturbation/vibrational signal. We demonstrate the effectiveness and the applicability of our ESC-VS approach via three rigid-body systems: (1) satellite attitude dynamics, (2) quadcopter attitude dynamics, and (3) acceleration-controlled unicycle dynamics. The results, including simulations with and without measurement delays/noise, illustrate the ability of our ESC-VS to operate successfully as a new methodology of optimization and control for rigid body dynamics.

math.OC↗

arXiv2026

Model-free source seeking of exponentially convergent unicycle: theoretical and robotic experimental results

This paper introduces a novel model-free, real-time unicycle-based source seeking design. This design autonomously steers the unicycle dynamic system towards the extremum point of an objective function or physical/scalar signal that is unknown expression-wise, but accessible via measurements. A key contribution of this paper is that the introduced design converges exponentially to the extremum point of objective functions (or scalar signals) that behave locally like a higher-degree power function (e.g., fourth-degree polynomial function) as opposed to locally quadratic objective functions, the usual case in literature. We provide theoretical results and design characterization, supported by a variety of simulation results that demonstrate the robustness of the proposed design, including cases with different initial conditions and measurement delays/noise. Also, for the first time in the literature, we provide experimental robotic results that demonstrate the effectiveness of the proposed design and its exponential convergence ability. These experimental results confirm that the proposed exponentially convergent extremum seeking design can be practically realized on a physical robotic platform under real-world sensing and actuation constraints.

math.OC↗

arXiv2025

Hovering Flight in Flapping Insects and Hummingbirds: A Natural Real-Time and Stable Extremum Seeking Feedback System

In this paper, we take an initial and novel step toward characterizing the physics of the hovering phenomenon in flapping insects and hummingbirds as a new class of extremum seeking (ES) feedback systems. By characterizing hovering flight in insects and hummingbirds as a natural hovering ES system, we achieve: (1) very simple, (2) stable, (3) model-free, and (4) real-time hovering. More importantly, our hovering ES characterization only needs the natural oscillations of the wing as the ES input. That is, unlike other control techniques in the literature, the natural hovering ES system only needs the natural flapping action built in the system, and feedback of local sensations (measurements) related to the altitude where the insect seeks to stabilize itself. Said ES characterization, can become an important initial step in starting a new line of research that may succeed in resolving the long-standing gap between model-based control theory and the biologically observed mechanisms that stabilize hovering flight. We provide simulation trials, including comparisons with some approaches from literature, to demonstrate the effectiveness and robustness of our results. We used literature data for hawkmoth, cranefly, bumblebee, dragonfly, hoverfly, and a hummingbird.

math.OC↗

arXiv2025

Model-Free and Real-Time Unicycle-Based Source Seeking with Differential Wheeled Robotic Experiments

Many autonomous robots aimed at source-seeking are studied, and their controls designed, using unicycle modeling and formulation. This is true not only for model-based controllers, but also for model-free, real-time control methods such as extremum seeking control (ESC). In this paper, we propose a unicycle-based ESC design applicable to differential wheeled robots that: (1) is very simple design, based on one simple control-affine law, and without state integrators; (2) attenuates oscillations known to persist in ESC designs (i.e., fully stop at the source); and (3) operates in a model-free, real-time setting, tolerating environmental/sensor noise. We provide simulation and real-world robotic experimental results for fixed and moving light source seeking by a differential wheeled robot using our proposed design. Results indicate clear advantages of our proposed design when compared to the literature, including attenuation of undesired oscillations, improved convergence speed, and better handling of noise.

cs.RO↗

arXiv2025

Investigating the Performance of EKF, UKF, and PF for Quadrotor Position Estimation in Hurricane Wind Disturbances

Natural disasters, such as hurricanes and typhoons, pose significant challenges to public safety and infrastructure. While government agencies rely on multi million dollar UAV systems for storm data collection and disaster response, smaller drones lack the ability to autonomously adapt to rapidly changing environmental conditions, such as turbulent winds. This project investigates the implementation of advanced state estimation filters, Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), and Particle Filter (PF), to enhance the control and adaptability of quadrotor drones in uncertain wind profiles modeled by Von Karman turbulence. While the EKF relies on linearization techniques using the Taylor series expansion, which can struggle under high nonlinearity, the UKF leverages sigma points for better performance in nonlinear systems without requiring Jacobian computations. The PF, on the other hand, addresses non-Gaussian noise and severe nonlinearities by employing a large number of particles, albeit at a high computational cost. To enhance accuracy and minimize estimation errors, a genetic algorithm (GA) was employed to optimally tune the process and measurement noise covariances (Q and R matrices) as well as UKF specific parameters alpha, beta, and kappa. This study highlights the tradeoff between accuracy, computational efficiency, and smoothing capabilities across these filters. Despite its robustness, the PF suffered from computational inefficiencies due to the high state dimensionality, while the EKF demonstrated faster computation but lower adaptability in nonlinear conditions. The UKF emerged as a balanced approach, achieving superior performance in capturing dynamic wind disturbances.

math.DS↗

arXiv2025

Extremum Seeking for Controlled Vibrational Stabilization of Second Order Mechanical Systems

This paper presents a novel extremum seeking control (ESC) approach for the vibrational stabilization of a class of mechanical systems (e.g., systems characterized by equations of motion resulting from Newton second law or Euler-Lagrange mechanics). Inspired by flapping insects mechanics, the proposed ESC approach is operable by only one perturbation signal and can admit generalized forces that are quadratic in velocities. We test our ESC, and compare it against approaches from literature, on some classical mechanical systems (e.g., mass-spring and an inverted pendulum systems). We also provide a novel, first-of-its-kind, application of the introduced ESC by achieving a 1D model-free source-seeking of a flapping system.

math.OC↗

arXiv2024

Model-Free Source Seeking by a Novel Single-Integrator with Attenuating Oscillations and Better Convergence Rate: Robotic Experiments

In this paper we validate, including experimentally, the effectiveness of a recent theoretical developments made by our group on control-affine Extremum Seeking Control (ESC) systems. In particular, our validation is concerned with the problem of source seeking by a mobile robot to the unknown source of a scalar signal (e.g., light). Our recent theoretical results made it possible to estimate the gradient of the unknown objective function (i.e., the scalar signal) incorporated in the ESC and use such information to apply an adaptation law which attenuates the oscillations of the ESC system while converging to the extremum (i.e., source). Based on our previous results, we propose here an amended design of the simple single-integrator control-affine structure known in ESC literature and show that it can functions effectively to achieve a model-free, real-time source seeking of light with attenuated oscillations using only local measurements of the light intensity. Results imply that the proposed design has significant potential as it also demonstrated much better convergence rate. We hope this paper encourages expansion of the proposed design in other fields, problems and experiments.

cs.RO↗