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Abstrak :
Impossible Refuge brings the perspectives of refugees into rapidly emerging dialogues about contemporary situations of mass forced migration, asking: what does it mean to be displaced? Based on multi-sited ethnographic research conducted with refugees from Central Africa living in situations of protracted asylum in Uganda and resettlement in Australia, the book provides a unique comparative analysis of global humanitarian systems and the experiences of refugees whose lives are interwoven with them. The book problematises the solutions that are currently in place to resolve the displacement of refugees, considering that since displacement cannot be reduced to a politico-legal problem but is an experience that resonates at an existential level, it cannot be assumed that politico-legal solutions to displacement automatically resolve what is, fundamentally, an existential state of being. Impossible Refuge therefore offers a new theoretical foundation through which to think about the experiences of refugees, as well as the systems in place to manage and resolve their displacement. The book argues that the refuge provided to refugees through international humanitarian systems is conditional: requiring that they conform to lifestyles that benefit the hegemonic future horizons of the societies that host and receive them. Impossible Refuge calls for new ways of approaching displacement that go beyond the exceptionality of refugee experience, to consider instead how the contestation and control of possible futures makes displacement a general condition of our time.

Abstrak :
Model Predictive Control (MPC) merupakan salah satu metode pengendali prediktif yang populer digunakan pada dunia industri. Beberapa keuntungan yang ditawarkan oleh pengendali ini di antaranya adalah kemampuannya dalam menangani sistem multivariabel dengan cukup mudah dan juga kemampuannya untuk memberikan constraint atau batasan tertentu baik pada sinyal pengendali maupun pada keluaran sistem. Sistem tata udara presisi yang akan dikendalikan pada skripsi ini juga merupakan sistem multivariabel berorde tinggi yang mempunyai dua masukan dan dua keluaran. Model sistem yang dipakai berupa model linier diskrit yang didapat dari hasil identifikasi menggunakan metode N4SID. Hasil pengendalian menggunakan MPC akan dibandingkan dengan pengendalian sistem menggunakan metode pengendali penempatan kutub dari umpan balik keadaan.

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Model Predictive Control (MPC) is one of predictive controller methods and popular for being used in industry. Some advantages offered by this controller are its ability to easily handle multivariable systems and its feature to provide constraints both for control signals and output signals. Precision air conditioning (PAC) system which will be controlled here is also a high-order multivariable system with two inputs and two outputs. Its model that is used in the controller is a discrete linear model from identification using N4SID method. The results of using MPC for this PAC system will be compared with the ones using another method of controller which is state-feedback pole placement.