This paper presents a novel adaptive control architecture that adapts fast and ensures uniformly bounded transient response for system's both signals, input output, simultaneously. new has low-pass filter in the feedback loop relies on small-gain theorem proof of asymptotic stability. The tools from this can be used to develop theoretically justified verification validation framework systems. Simulations illustrate theoretical findings.

The success of deep learning in visual recognition tasks has driven advancements multiple fields research. Particularly, increasing attention been drawn towards its application agriculture. Nevertheless, while pattern on farmlands carries enormous economic values, little progress made to merge computer vision and crop sciences due the lack suitable agricultural image datasets. Meanwhile, problems agriculture also pose new challenges vision. For example, semantic segmentation aerial farmland...

We consider adaptive output feedback control of uncertain nonlinear systems, in which both the dynamics and dimension regulated system may be unknown. However, relative degree is assumed to known. Given a smooth reference trajectory, problem design controller that forces measurement track it with bounded errors. The classical approach requires state observer. Finding good observer for an not obvious task. argue sufficient build tracking error. Ultimate boundedness error signals shown through...

This article presents the development of L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> adaptive-control theory and its application to safety critical flight control system (FCS) development. Several architectures benchmark examples are analyzed. The key feature is decoupling estimation control, which enables use arbitrarily fast rates without sacrificing robustness. Rohrs's example two-cart used as problems for illustration. NASA's...

In this paper, we develop a novel adaptive control architecture that ensures the input and output of an uncertain linear system track desired during transient phase, in addition to asymptotic tracking. These features are established by first performing equivalent reparametrization MRAC, main difference which from MRAC is definition error signal for laws. This new architecture, called companion model controller (CMAC), allows incorporation low-pass filter into feedback-loop enables enforce...

The paper presents a three-dimensional path-following control algorithm that expands the capabilities of conventional autopilots, which are normally designed to provide only guidance loops for waypoint navigation. Implementation this broadens range possible applications small unmanned aerial vehicles. solution proposed takes explicit advantage fact these vehicles equipped with autopilots stabilizing and providing angular-rate tracking capabilities. Therefore, overall closed-loop system...

Predicting crop yield response to management and environmental variables is a crucial step towards nutrient optimization. With the increase in amount of data generated by agricultural machinery, more sophisticated models are necessary get full advantage such data. In this work, we propose Convolutional Neural Network (CNN) capture relevant spatial structures different attributes combine them model seed rate management. Nine on-farm experiments on corn fields used construct suitable dataset...

In this study, we uncover the unexpected efficacy of residual-based large language models (LLMs) as part encoders for biomedical imaging tasks, a domain traditionally devoid or textual data. The approach diverges from established methodologies by utilizing frozen transformer block, extracted pre-trained LLMs, an innovative encoder layer direct processing visual tokens. This strategy represents significant departure standard multi-modal vision-language frameworks, which typically hinge on...

In this paper, we present a novel adaptive control architecture that ensures the input and output of an uncertain linear system track desired during transient phase, in addition to asymptotic tracking. Design guidelines are presented ensure specifications can be achieved for both system's signals. The tools from paper used develop theoretically justified verification validation framework systems. Simulation results illustrate theoretical findings

In this paper, a neuroadaptive control framework for continuous- and discrete-time nonlinear uncertain dynamical systems with input-to-state stable internal dynamics is developed. The proposed Lyapunov based unlike standard neural network (NN) controllers guaranteeing ultimate boundedness, the guarantees partial asymptotic stability of closed-loop system, that is, respect to part system states associated plant states. are constructed without requiring explicit knowledge other than assumption...

This paper presents an extension of the L 1 adaptive output-feedback controller to systems unknown relative degree in presence time-varying uncertainties without restricting rate their variation. As compared with earlier results this direction, a new piecewise continuous law is introduced, along low-pass-filtered control signal that allows for achieving arbitrarily close tracking input and output signals reference system, transfer function which not required be strictly positive real....

In this paper we present a new L(sub 1) adaptive control architecture that directly compensates for matched as well unmatched system uncertainty. To evaluate the controller, take advantage of flexible research environment with rapid prototyping and testing laws in Airborne Subscale Transport Aircraft Research at NASA Langley Center. We apply to subscale turbine powered Generic Model. The presented results are from full nonlinear simulation Model some preliminary pilot evaluations law.

This paper presents a novel adaptive control methodology for uncertain systems with time-varying unknown parameters and bounded disturbances. The controller ensures uniformly transient asymptotic tracking system's both signals, input output, simultaneously. performance bounds can be systematically improved by increasing the adaptation rate. Simulations of robotic arm friction verify theoretical findings.

This technical note presents the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i> <sub xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> adaptive control architecture for systems in presence of unknown high-frequency gain with known sign, time-varying parameters and disturbances. The controller leads to uniform performance bounds system's input output signals, which can be systematically improved by increasing adaptation rate. For constant...

Verification and Validation (V&V) of gain-scheduled flight control systems relies on analysis gain phase margins across the envelope. Because similar tools are not available for nonlinear systems, V&V such requires numerous Monte Carlo simulations, cost which grows with increasing complexity system. The recently developed L1 adaptive methodology addresses this issue by providing a systematic framework design laws. It extends classical notions to scheme, enables closedloop system guaranteed,...

This paper addresses the problem of steering a fleet unmanned aerial vehicles along desired three-dimensional paths while meeting stringent spatial and temporal constraints. A representative example is challenging mission scenario where are tasked to cooperatively execute collision-free maneuvers arrive at their final destinations same time. In proposed framework, assigned nominal speed profiles those, then requested cooperative path following, rather than open loop trajectory tracking...

This paper presents results of a flight test the L-1 adaptive control architecture designed to directly compensate for significant uncertain cross-coupling in nonlinear systems. The was conducted on subscale turbine powered Generic Transport Model that is an integral part Airborne Subscale Aircraft Research system at NASA Langley Center. presented are piloted tasks performed during test.

This paper addresses the problem of time-coordination a team cooperating multirotor unmanned aerial vehicles that exchange information over supporting time-varying network. A distributed control law is developed to ensure meet desired temporal assignments mission, while flying along predefined collision-free paths, even in presence faulty communication networks, temporary link losses, and switching topologies. In this paper, coordination task solved by reaching consensus on suitably defined...

Experimental results are presented that illustrate a recently developed method for adaptive output feedback control. The permits adaptation to both parametric uncertainty and unmodeled dynamics, incorporates novel approach under known actuator characteristics including dynamics saturation. Only knowledge of the relative degree controlled system within bandwidth control design is required. controller was tested by controlling pitch axis three degrees-of-freedom (DOF) helicopter model, using...