New ways of being public: the experience of foundation degrees

This article explores the recent development of new spheres of public engagement within UK higher education through an analysis of the foundation degree qualification. These, according to the Higher Education Funding Council for England (HEFCE), were designed to equip students with the combination of technical skills, academic knowledge, and transferable skills increasingly being demanded by employers, and they have been identified as being at the forefront of educational agendas aimed at increasing employer engagement in the higher education (HE) sector. As such, they might be regarded as an expression of the 'increasing privatisation' of HE. However, this article argues that, on the contrary, they have enabled the development of new areas of public engagement relating to the design and delivery of courses as well as providing new opportunities for the pursuit of public policy goals such as widening participation. Such outcomes, it is argued, are the result of a number of factors that explain the 'publicness' of the qualification and that should be sustained to ensure the implementation of the 2006 Leitch Report in a manner that further develops public engagement

Computational complexity of μ calculation

The structured singular value μ measures the robustness of uncertain systems. Numerous researchers over the last decade have worked on developing efficient methods for computing μ. This paper considers the complexity of calculating μ with general mixed real/complex uncertainty in the framework of combinatorial complexity theory. In particular, it is proved that the μ recognition problem with either pure real or mixed real/complex uncertainty is NP-hard. This strongly suggests that it is futile to pursue exact methods for calculating μ of general systems with pure real or mixed uncertainty for other than small problems

Plenary Panel Discussion: Challenges and opportunities for the future of control

This panel reflects the scope and diversity of the unprecedented challenges and opportunities for the systems and controls community that has been created by several research themes from the basic sciences to advanced technologies. Connecting physical processes at multiple time and space scales in quantum, statistical, fluid, and solid mechanics, remains not only a central scientific challenge but also one with increasing technological implications. This is particular so in highly organized and nonequilibrium systems as in biology and nanotechnology, where interconnection, feedback, and dynamics are playing an increasingly central role

Controller Order Reduction with Guaranteed Stability and Performance

In this paper we consider the problem of controller order reduction for control design for robust performance. In practical control design it may be important to have low order controllers. For example, one may want to gain schedule a series of LTI (linear, time invariant) controllers, or give simple physical interpretations to the control dynamics. When solving practical design problems using, say, H∞ software it is common to produce controllers of high order - equal to the sum of the order of the plant plus each of the weighting functions. However, there may be lower order controllers which stabilize the plant and provide satisfactory H∞ closed loop performance. The objectives of a method for controller order reduction within the H∞ framework, then, should be to find low order controllers which stabilize a given plant and provides satisfactory H∞ performance. Ideally, the method should apply to a large class of problems, be easy to implement and be guaranteed to work

Practical computation of the mixed μ problem

Upper and lower bounds for the mixed μ problem have recently been developed, and this paper examines the computational aspects of these bounds. In particular a practical algorithm is developed to compute the bounds. This has been implemented as a Matlab function (m-file), and will be available shortly in a test version in conjunction with the μ-Tools toolbox. The algorithm performance is very encouraging, both in terms of accuracy of the resulting bounds, and growth rate in required computation with problem size. In particular it appears that one can handle medium size problems (less than 100 perturbations) with reasonable computational requirements