Search results for "Robustne"
showing 10 items of 515 documents
Adaptive Backstepping Control of a 2-DOF Helicopter
2019
This paper proposes an adaptive nonlinear controller for a 2-Degree of Freedom (DOF) helicopter. The proposed controller is designed using backstepping control technique and is used to track the pitch and yaw position references independently. A MIMO nonlinear mathematical model is derived for the 2DOF helicopter based on Euler-Lagrange equations, where the system parameters and the control coefficients are uncertain. Unlike some existing control schemes for the helicopter control, the developed controller does not require the knowledge on the system uncertain parameters. Updating laws are used to estimate the unknown parameters. It is shown that not only the global stability is guaranteed …
Use of second-order sliding mode observer for low-accuracy sensing in hydraulic machines
2018
Low-accuracy sensing is very common for the large hydraulic machines and does not allow for directly measuring the relative velocity which can be, otherwise, required for the control and monitoring purposes. This paper provides a case study of designing the second-order sliding mode observer based on the super-twisting robust exact differentiator. The nominal part of the system dynamics is derived from the simple available system measurements and incorporated into the observer structure. Parasitic by-effects, arising from the sensor sampling, quantization, and non-modeled distortions due to mechanical sensor interface, are shown as the main causes of hampering the final (steady-state) conve…
Machine Learning Approaches for Activity Recognition and/or Activity Prediction in Locomotion Assistive Devices—A Systematic Review
2020
Locomotion assistive devices equipped with a microprocessor can potentially automatically adapt their behavior when the user is transitioning from one locomotion mode to another. Many developments in the field have come from machine learning driven controllers on locomotion assistive devices that recognize/predict the current locomotion mode or the upcoming one. This review synthesizes the machine learning algorithms designed to recognize or to predict a locomotion mode in order to automatically adapt the behavior of a locomotion assistive device. A systematic review was conducted on the Web of Science and MEDLINE databases (as well as in the retrieved papers) to identify articles published…
Using the Analytic Hierarchy Process (AHP) and fuzzy logic to evaluate the possibility of introducing single point incremental forming on industrial …
2018
Abstract Single point incremental forming (SPIF) is a promising forming process, yet not entirely accepted and implemented on industrial scale, due to several reasons, presented in the paper. The approach presented here develops an evaluation method for the degree of its industrial implementation. Several factors which will favor the industrial implementation of ASPIF are identified and their weights are hierarchized by means of AHP. To assess the robustness of the AHP, a sensitivity analysis was also presented. Furthermore, a fuzzy inference system was built, having as output the degree of industrial implementation of SPIF.
Optimizing MRI contrast with B1 pulses using optimal control theory
2016
The variety of achievable contrasts by MRI makes it a highly flexible and valuable diagnostic tool. Contrast results from relaxation time differences, which are intrinsic properties of each tissue. Using optimal control theory, one can control the obtained contrast by applying excitation pulses that bring the magnetization in a user-defined target state. Simulation results are presented to illustrate the feasibility and the flexibility of using optimal contrast pulses. The robustness to experimental variable parameters such as field inhomogeneities is also studied. Finally, an in-vitro contrast experiment is performed on a small-animal MRI showing a reasonable match with the simulation resu…
A robust two-feedback loops position control algorithm for compliant low-cost series elastic actuators
2019
Elastic joints are considered to outperform rigid joints in terms of peak dynamics, collision tolerance, robustness, and energy efficiency. Therefore, intrinsically elastic joints have become progressively prominent over the last years for a variety of robotic applications. In this article, a two-feedback loops position control algorithm is proposed for an elastic actuator to deal with the influence from external disturbances. The considered elastic actuator was recently designed by our research group for Serpens, a low-cost, open-source and highly-compliant multi-purpose modular snake robot. In particular, the inner controller loop is implemented as a model reference adaptive controller (M…
Homography based egomotion estimation with a common direction
2017
International audience; In this paper, we explore the different minimal solutions for egomotion estimation of a camera based on homography knowing the gravity vector between calibrated images. These solutions depend on the prior knowledge about the reference plane used by the homography. We then demonstrate that the number of matched points can vary from two to three and that a direct closed-form solution or a Gröbner basis based solution can be derived according to this plane. Many experimental results on synthetic and real sequences in indoor and outdoor environments show the efficiency and the robustness of our approach compared to standard methods.
Adaptive Control of Soft Robots Based on an Enhanced 3D Augmented Rigid Robot Matching
2021
Despite having proven successful in generating precise motions under dynamic conditions in highly deformable soft-bodied robots, model based techniques are also prone to robustness issues connected to the intrinsic uncertain nature of the dynamics of these systems. This letter aims at tackling this challenge, by extending the augmented rigid robot formulation to a stable representation of three dimensional motions of soft robots, under Piecewise Constant Curvature hypothesis. In turn, the equivalence between soft-bodied and rigid robots permits to derive effective adaptive controllers for soft-bodied robots, achieving perfect posture regulation under considerable errors in the knowledge of …
Event-triggered robust adaptive control for discrete time uncertain systems with unmodelled dynamics and disturbances
2019
In practice, modelling errors caused by high-order unmodelled dynamics and external disturbances are unavoidable. How to ensure the robustness of an adaptive controller with respect to such modelling errors is always a critical concern. In this study, the authors consider the design of event-triggered robust adaptive control for a class of discrete-time uncertain systems which involve such modelling errors and also are allowed to be non-minimum phase. Unlike some existing event-triggered control schemes, the developed controllers do not require that the measurement errors meet the corresponding input-to-state stable condition. Global stability of the closed-loop system which means that all …
Density Flow in Dynamical Networks via Mean-Field Games
2016
Current distributed routing control algorithms for dynamic networks model networks using the time evolution of density at network edges, while the routing control algorithm ensures edge density to converge to a Wardrop equilibrium, which was characterized by an equal traffic density on all used paths. We rearrange the density model to recast the problem within the framework of mean-field games. In doing that, we illustrate an extended state-space solution approach and we study the stochastic case where the density evolution is driven by a Brownian motion. Further, we investigate the case where the density evolution is perturbed by a bounded adversarial disturbance. For both the stochastic a…