Input constraints handling in an MPC/feedback linearization scheme

The combination of model predictive control based on linear models (MPC) with feedback linearization (FL) has attracted interest for a number of years, giving rise to MPC+FL control schemes. An important advantage of such schemes is that feedback linearizable plants can be controlled with a linear predictive controller with a fixed model. Handling input constraints within such schemes is difficult since simple bound contraints on the input become state dependent because of the nonlinear transformation introduced by feedback linearization. This paper introduces a technique for handling input constraints within a real time MPC/FL scheme, where the plant model employed is a class of dynamic neural networks. The technique is based on a simple affine transformation of the feasible area. A simulated case study is presented to illustrate the use and benefits of the technique.

Mutant prevention concentrations of ciprofloxacin and enrofloxacin for Salmonella enterica

Objectives: To determine the mutant prevention concentrations (MPCs) of ciprofloxacin and enrofloxacin against four strains of Salmonella enterica serovar Enteritidis and four strains of S. Typhimurium including one fully susceptible, one multiply resistant (MAR), one GyrA mutant and one GyrA/MAR mutant. Further, to examine mutants arising after exposure to sub-MPC concentrations of the antibiotics for susceptibility to ciprofloxacin and enrofloxacin, and cyclohexane tolerance. Methods: MICs were determined using the agar dilution method of the BSAC. The MPC was recorded as the lowest concentration of antibiotic to inhibit growth from an inoculum of 10(10) cfu. Results: The MPCs and resulting MPC/MIC ratios of enrofloxacin were generally two- to four-fold higher than for ciprofloxacin. At 24 h for both antibiotics, MPCs were lowest for the fully susceptible strains (0.25-0.5 mg/L), similar for the MAR (1-4 mg/L) and GyrA (2-4 mg/L) mutants and highest for the GyrA/MAR mutants (1-8 mg/L). MPC/MIC ratios at 24 h were 2-16 for all strains except those for the MAR strains without mutation in gyrA where the ratios were 8-64. Conclusions: The ability to eradicate Salmonella in vivo depends on many factors such as antibiotic susceptibility of the strain, dose and route of administration. It is suggested that these MPC values will be useful when considering dosing strategies. In view of the high MPC/MIC ratio, MAR strains with wild-type gyrA, although susceptible to ciprofloxacin (MICs 0.06-0.13 mg/L), may give rise to treatment failures.

Evaluating the Bank of England density forecasts of inflation

We consider evaluating the UK Monetary Policy Committee's inflation density forecasts using probability integral transform goodness-of-fit tests. These tests evaluate the whole forecast density. We also consider whether the probabilities assigned to inflation being in certain ranges are well calibrated, where the ranges are chosen to be those of particular relevance to the MPC, given its remit of maintaining inflation rates in a band around per annum. Finally, we discuss the decision-based approach to forecast evaluation in relation to the MPC forecasts

The real-time optimisation of DNO owned storage devices on the LV network for peak reduction

Energy storage is a potential alternative to conventional network reinforcementof the low voltage (LV) distribution network to ensure the grid’s infrastructure remainswithin its operating constraints. This paper presents a study on the control of such storagedevices, owned by distribution network operators. A deterministic model predictive control (MPC) controller and a stochastic receding horizon controller (SRHC) are presented, wherethe objective is to achieve the greatest peak reduction in demand, for a given storagedevice specification, taking into account the high level of uncertainty in the prediction of LV demand. The algorithms presented in this paper are compared to a standard set-pointcontroller and bench marked against a control algorithm with a perfect forecast. A specificcase study, using storage on the LV network, is presented, and the results of each algorithmare compared. A comprehensive analysis is then carried out simulating a large number of LV networks of varying numbers of households. The results show that the performance of each algorithm is dependent on the number of aggregated households. However, on a typical aggregation, the novel SRHC algorithm presented in this paper is shown to outperform each of the comparable storage control techniques.