Abuse of Law in International Arbitration

The article deals with the phenomenon of abuse of law in international arbitration that seems to be an extremely relevant subject for study due to the development of transnational economic relations. At the same time, various types of abuse in arbitration make us think about developing a certain classification of all cases of abuse of law. The purpose of this article is to comprehensively consider the types of abuse of law in international arbitration and the prospects for countering such abuses, as well as to develop a theoretical basis for such countering based on world experience. In this study, the delay in the process, challenging the competence of arbitration, abuse of information disclosure and exchange of documents, the transfer of the assets of debtor to affiliates or third parties, a fraudulent application for bankruptcy of the debtor, as well as lies to arbitrators and fake evidence were considered. At the same time, the article notes the problem of the lack of mandatory ethical standards in international arbitration and the insufficient powers of arbitrators in the process. The authors conclude that it is necessary to continue work on ethical codes of conduct. In addition, it is concluded that it is necessary to apply liability measures and “procedural sanctions”. In this regard, we are ready for regulatory changes and the implementation of the “ethical review”, that is necessary for positive changes in arbitration

Stabilization of Differential Repetitive Processes

Differential repetitive processes are a subclass of 2D systems that arise in modelingphysical processes with identical repetitions of the same task and in the analysis of othercontrol problems such as the design of iterative learning control laws. These models haveproved to be efficient within the framework of linear dynamics, where control laws designed inthis setting have been verified experimentally, but there are few results for nonlinear dynamics.This paper develops new results on the stability, stabilization and disturbance attenuation,using an H? norm measure, for nonlinear differential repetitive processes. These results arethen applied to design iterative learning control algorithms under model uncertainty and sensorfailures described by a homogeneous Markov chain with a finite set of states. The resultingdesign algorithms can be computed using linear matrix inequalities