I Going Away. I Going Home. : Austin Clarke\u27s Leaving this Island Place

Austin Clarke’s “Leaving This Island Place” is one of scores of Caribbean autobiographical works that focus on a bright, young, lower-class islander leaving his/her small island place and setting out on “Eldorado voyages.” The narrative of that journey away from home to Europe or Canada or the United States and the later efforts to return may be said to be the Caribbean story, as suggested in the subtitle of Wilfred Cartey’s study of Caribbean literature, Whispers from the Caribbean: I Going Away, I Going Home, which argues that while in Caribbean literature there is much movement away, there is also a body of literature in which “the notion of ‘away’ and images of movement out are replaced by images of return” (xvi). Traditionally, however, the first autobiographical works, such as George Lamming’s In the Castle of My Skin, V. S. Naipaul’s A House for Mr. Biswas, Merle Hodge’s Crick Crack, Monkey, Jamaica Kincaid’s Annie John, Michelle Cliff’s No Telephone to Heaven, Edwidge Danticat’s Breath, Eyes, Memory, and Elizabeth Nunez’s Beyond the Limbo Silence, have focused on the childhood in the Caribbean and the journey away—or at least the preparation for that journey. Such is the case with Clarke’s “Leaving This Island Place.

Efficient numerical methods for nonlinear mpc and moving horizon estimation

exploitation This overview paper reviews numerical methods for solution of optimal control problems in real-time, as they arise in nonlinear model predictive control (NMPC) as well as in moving horizon estimation (MHE). In the first part, we review numerical optimal control solution methods, focussing exclusively on a discrete time setting. We discuss several algorithmic ”building blocks ” that can be combined to a multitude of algorithms. We start by discussing the sequential and simultaneous approaches, the first leading to smaller, the second to more structured optimization problems. The two big families of Newton type optimization methods, Sequential Quadratic Programming (SQP) and Interior Point (IP) methods, are presented, and we discuss how to exploit the optimal control structure in the solution of the linear-quadratic subproblems, where the two major alternatives are “condensing ” and band structure exploiting approaches. The second part of the paper discusses how the algorithms can be adapted to the real-time challenge of NMPC and MHE. We recall an important sensitivity result from parametric optimization, and show that a tangential solution predictor for online data can easily be generated in Newton type algorithms. We point out one important difference between SQP and IP methods: while both methods are able to generate the tangential predictor for fixed active sets, the SQP predictor even works across active set changes. We then classify many proposed real-time optimization approaches from the literature into the developed categories