Online Sensor Bias Estimation & Calibration by Kalman Filtering with Adaptive Lyapunov Redesign Method

Faulty measurements bring faulty controls and the major part of those are the bias in sensor readings. In this paper, the theory of adaptive and online calibration of a sensor with another measurement model is demonstrated by using Lyapunov redesign approach in Kalman filtering framework. In the measurement update step of Kalman filter, the effect of measurement bias is considered as a parametric uncertainty term and it is proven that it can be regressed by a universal approximator and can be eliminated from measurement update step while preserving the asymptotic stability of the estimator. Then, the convergence criteria for online parameter adaptation are obtained. Finally, a case study for estimation-based roll control of a missile is conducted and the results of online calibration is discussed

Constrained discrete-time optimal control of uncertain systems with adaptive Lyapunov redesign

© 2021 Turkiye Klinikleri. All rights reserved.In this paper, the conventional estimation-based receding horizon control paradigm is enhanced by using functional approximation, the adaptive modifications on state estimation and convex projection notion from optimization theory. The mathematical formalism of parameter adaptation and uncertainty estimation procedure are based on the redesign of optimal state estimation in discrete-time. By using Lyapunov stability theory, it is shown that the online approximation of uncertainties acting on both physical system and state estimator can be obtained. Moreover, the convergence criteria for online parameter adaptation with fully matched and partially matched cases are presented and shown. In addition, it is shown that the uniform boundedness of tracking and adaptation errors can be maintained by projection-based parameter update laws in discrete-time with adequate sampling times. Finally, the proposed method is implemented to quadrotor case study and the gradual recovery of feasible sub-optimal solutions are presented despite actuation, modeling and measurement errors. By using the proposed method, the uncertainty estimates are successfully converged to their prescribed values and both state prediction and command tracking of model predictive controller are corrected within the convergence bounds

Otonom Quadrotor Sürüleri için Orantısal Navigasyon Tabanlı Merkezi Olmayan Toplu Hareket Algoritması

Bu bildiride orantısal navigasyon yaklaşımlarının yeni bir yöntem olarak otonom ve merkezi olmayan multikopter robotların kontrolüne nasıl uygulanabileceği anlatılmaktadır. Burada merkezi olmayan ile kastedilen her bir sürü bireyinin yakınındaki diğer bireylerden edindiği bilgi doğrultusunda bağımsız olarak hareket edebilmesidir. Çalışmada iki farklı iletişim prosedürü kullanılmış olup bunlar eşler arası etkileşim ve odaklanmış etkileşim olarak tanımlanmıştır. Eşler arası etkileşimde her birey en yakınındakine güdümlenirken odaklanmış etkileşimde ise yayını alan diğer bireylerin ortalama konumuna güdümlenmiştir. Buna ek olarak basit bir itme-çekme modeli kullanılarak da bireylerin çarpışma ve saçılma durumları önlenmiştir. Yaklaşım çeşitli sayıda üyelerden oluşan sürü grupları ve sinyal-gürültü oranları altında üyeleri bir araya toplayıp hizalayarak, toplu şekilde hareketi ve bir arada kalmayı başarılı bir şekilde sağlamıştır.In this paper we will describe the adaptation of the well-known proportional navigation methods as a novel way to control a decentralized and autonomous swarm of flying robots. By decentralized we mean that each individuals navigate themselves according to the information they receive from other robots in their vicinity. We have used two different communication procedures; the peer to peer method where individuals receive information only from the closest member and focused communication where the information from all the members in a specified radius in the vicinity of each individual is processed. In addition, by using a simple attraction-repulsion model the collision and scattering of members are prevented. The algorithm is tested against different swarm sizes and noise to signal ratios and performs successfully in both aggregation and flocking by gathering individuals together and aligning them towards the same destinatio

Global distribution of alveolar and cystic echinococcosis

Alveolar echinococcosis (AE) and cystic echinococcosis (CE) are severe helminthic zoonoses. Echinococcus multilocularis (causative agent of AE) is widely distributed in the northern hemisphere where it is typically maintained in a wild animal cycle including canids as definitive hosts and rodents as intermediate hosts. The species Echinococcus granulosus, Echinococcus ortleppi, Echinococcus canadensis and Echinococcus intermedius are the causative agents of CE with a worldwide distribution and a highly variable human disease burden in the different endemic areas depending upon human behavioural risk factors, the diversity and ecology of animal host assemblages and the genetic diversity within Echinococcus species which differ in their zoonotic potential and pathogenicity. Both AE and CE are regarded as neglected zoonoses, with a higher overall burden of disease for CE due to its global distribution and high regional prevalence, but a higher pathogenicity and case fatality rate for AE, especially in Asia. Over the past two decades, numerous studies have addressed the epidemiology and distribution of these Echinococcus species worldwide, resulting in better-defined boundaries of the endemic areas. This chapter presents the global distribution of Echinococcus species and human AE and CE in maps and summarizes the global data on host assemblages, transmission, prevalence in animal definitive hosts, incidence in people and molecular epidemiology