Stability enhancement by casing grooves: The importance of stall inception mechanism and solidity

This paper concerns the optimisation of casing grooves and the important influence of stall inception mechanism on groove performance. Installing casing grooves is a well known technique for improving the stable operating range of a compressor, but the wide-spread use of grooves is restricted by the loss of efficiency and flow capacity. In this paper, laboratory tests are used to examine the conditions under which casing treatment can be used to greatest effect. The use of a single casing groove was investigated in a recently published companion paper. The current work extends this to multiple-groove treatments and considers their performance in relation to stall inception mechanisms. Here it is shown that the stall margin gain from multiple grooves is less than the sum of the gains if the grooves were used individually. By contrast, the loss of efficiency is additive as the number of grooves increases. It is then shown that casing grooves give the greatest stall margin improvement when used in a compressor which exhibits spike-type stall inception, while modal activity before stall can dramatically reduce the effectiveness of the grooves. This finding highlights the importance of being able to predict the stall inception mechanism which might occur in a given compressor before and after grooves are added. Some published prediction techniques are therefore examined, but found wanting. Lastly, it is shown that casing grooves can, in some cases, be used to remove rotor blades and produce a more efficient, stable and light-weight rotor. © 2010 by ASME.

Verification of periodically controlled hybrid systems: Application to an autonomous vehicle

This article introduces Periodically Controlled Hybrid Automata (PCHA) for modular specification of embedded control systems. In a PCHA, control actions that change the control input to the plant occur roughly periodically, while other actions that update the state of the controller may occur in the interim. Such actions could model, for example, sensor updates and information received from higher-level planning modules that change the set point of the controller. Based on periodicity and subtangential conditions, a new sufficient condition for verifying invariant properties of PCHAs is presented. For PCHAs with polynomial continuous vector fields, it is possible to check these conditions automatically using, for example, quantifier elimination or sum of squares decomposition. We examine the feasibility of this automatic approach on a small example. The proposed technique is also used to manually verify safety and progress properties of a fairly complex planner-controller subsystem of an autonomous ground vehicle. Geometric properties of planner-generated paths are derived which guarantee that such paths can be safely followed by the controller. © 2012 ACM.

ℓasso MPC: Smart regulation of over-actuated systems

In this paper, a novel MPC strategy is proposed, and referred to as asso MPC. The new paradigm features an 1-regularised least squares loss function, in which the control error variance competes with the sum of input channels magnitude (or slew rate) over the whole horizon length. This cost choice is motivated by the successful development of LASSO theory in signal processing and machine learning. In the latter fields, sum-of-norms regularisation have shown a strong capability to provide robust and sparse solutions for system identification and feature selection. In this paper, a discrete-time dual-mode asso MPC is formulated, and its stability is proven by application of standard MPC arguments. The controller is then tested for the problem of ship course keeping and roll reduction with rudder and fins, in a directional stochastic sea. Simulations show the asso MPC to inherit positive features from its corresponding regressor: extreme reduction of decision variables' magnitude, namely, actuators' magnitude (or variations), with a finite energy error, being particularly promising for over-actuated systems. © 2012 AACC American Automatic Control Council).