In this paper we deal with a class of uncertain time-varying nonlinear systems with a state delay. Under some assumptions, we construct some stabilizing continuous feedback, i.e. linear and nonlinear in the state, whi...In this paper we deal with a class of uncertain time-varying nonlinear systems with a state delay. Under some assumptions, we construct some stabilizing continuous feedback, i.e. linear and nonlinear in the state, which can guarantee global uniform exponential stability and global uniform practical convergence of the considered system. The quadratic Lyapunov function for the nominal stable system is used as a Lyapunov candidate function for the global system. The results developed in this note are applicable to a class of dynamical systems with uncertain time-delay. Our result is illustrated by a numerical example.展开更多
Since their publication in 2016 we have seen a rapid adoption of the FAIR principles in many scientific disciplines where the inherent value of research data and,therefore,the importance of good data management and da...Since their publication in 2016 we have seen a rapid adoption of the FAIR principles in many scientific disciplines where the inherent value of research data and,therefore,the importance of good data management and data stewardship,is recognized.This has led to many communities asking“What is FAIR?”and“How FAIR are we currently?”,questions which were addressed respectively by a publication revisiting the principles and the emergence of FAIR metrics.However,early adopters of the FAIR principles have already run into the next question:“How can we become(more)FAIR?”This question is more difficult to answer,as the principles do not prescribe any specific standard or implementation.Moreover,there does not yet exist a mature ecosystem of tools,platforms and standards to support human and machine agents to manage,produce,publish and consume FAIR data in a user-friendly and efficient(i.e.,“easy”)way.In this paper we will show,however,that there are already many emerging examples of FAIR tools under development.This paper puts forward the position that we are likely already in a creolization phase where FAIR tools and technologies are merging and combining,before converging in a subsequent phase to solutions that make FAIR feasible in daily practice.展开更多
文摘In this paper we deal with a class of uncertain time-varying nonlinear systems with a state delay. Under some assumptions, we construct some stabilizing continuous feedback, i.e. linear and nonlinear in the state, which can guarantee global uniform exponential stability and global uniform practical convergence of the considered system. The quadratic Lyapunov function for the nominal stable system is used as a Lyapunov candidate function for the global system. The results developed in this note are applicable to a class of dynamical systems with uncertain time-delay. Our result is illustrated by a numerical example.
基金Part of this work is funded by the NWA program(project VWData-400.17.605)by the Netherlands Organization for Scientific Research(NWO)+1 种基金by the European Joint Program Rare Diseases(grant agreement#825575)ELIXIR-EXCELERATE(H2020-INFRADEV-1-2015-12).
文摘Since their publication in 2016 we have seen a rapid adoption of the FAIR principles in many scientific disciplines where the inherent value of research data and,therefore,the importance of good data management and data stewardship,is recognized.This has led to many communities asking“What is FAIR?”and“How FAIR are we currently?”,questions which were addressed respectively by a publication revisiting the principles and the emergence of FAIR metrics.However,early adopters of the FAIR principles have already run into the next question:“How can we become(more)FAIR?”This question is more difficult to answer,as the principles do not prescribe any specific standard or implementation.Moreover,there does not yet exist a mature ecosystem of tools,platforms and standards to support human and machine agents to manage,produce,publish and consume FAIR data in a user-friendly and efficient(i.e.,“easy”)way.In this paper we will show,however,that there are already many emerging examples of FAIR tools under development.This paper puts forward the position that we are likely already in a creolization phase where FAIR tools and technologies are merging and combining,before converging in a subsequent phase to solutions that make FAIR feasible in daily practice.
