Performance evaluation of multiplexed model predictive control for a large airliner in nominal and contingency scenarios

Model predictive control allows systematic handling of physical and operational constraints through the use of constrained optimisation. It has also been shown to successfully exploit plant redundancy to maintain a level of control in scenarios when faults are present. Unfortunately, the computational complexity of each individual iteration of the algorithm to solve the optimisation problem scales cubically with the number of plant inputs, so the computational demands are high for large MIMO plants. Multiplexed MPC only calculates changes in a subset of the plant inputs at each sampling instant, thus reducing the complexity of the optimisation. This paper demonstrates the application of multiplexed model predictive control to a large transport airliner in a nominal and a contingency scenario. The performance is compared to that obtained with a conventional synchronous model predictive controller, designed using an equivalent cost function. © 2012 AACC American Automatic Control Council).

Durability indicators of SCC towards performance-based specifications for the durability of SCC

The fundamental principle behind the development of SCC has been the nanoscale tailoring of cementitious matrices. Although self-compacting concrete (SCC) is currently used in many countries, there is a fundamental lack of the intrinsic durability of the material itself. The scope of the current paper is to present the outcomes of a research study on some principal indicators (porosity and capillary absorption) that define the durability of SCC, and how these are compared with the corresponding parameters of conventional concrete. Furthermore, this paper investigates the addition of industrial by-products, such as fly-ash or lime powder, to SCC mixtures and their effect on the durability indicators.