Design of a minimum variance multiple input-multiple output neuro self-tuning proportional-integral-derivative controller for non-linear dynamic systems

In this study a minimum variance neuro self-tuning proportional-integral-derivative (PID) controller is designed for complex multiple input-multiple output (MIMO) dynamic systems. An approximation model is constructed, which consists of two functional blocks. The first block uses a linear submodel to approximate dominant system dynamics around a selected number of operating points. The second block is used as an error agent, implemented by a neural network, to accommodate the inaccuracy possibly introduced by the linear submodel approximation, various complexities/uncertainties, and complicated coupling effects frequently exhibited in non-linear MIMO dynamic systems. With the proposed model structure, controller design of an MIMO plant with n inputs and n outputs could be, for example, decomposed into n independent single input-single output (SISO) subsystem designs. The effectiveness of the controller design procedure is initially verified through simulations of industrial examples.

A neural network enhanced generalized minimum variance self-tuning proportional, integral and derivative control algorithm for complex dynamic systems

A neural network enhanced proportional, integral and derivative (PID) controller is presented that combines the attributes of neural network learning with a generalized minimum-variance self-tuning control (STC) strategy. The neuro PID controller is structured with plant model identification and PID parameter tuning. The plants to be controlled are approximated by an equivalent model composed of a simple linear submodel to approximate plant dynamics around operating points, plus an error agent to accommodate the errors induced by linear submodel inaccuracy due to non-linearities and other complexities. A generalized recursive least-squares algorithm is used to identify the linear submodel, and a layered neural network is used to detect the error agent in which the weights are updated on the basis of the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model, and therefore the error agent is naturally functioned within the control law. In this way the controller can deal not only with a wide range of linear dynamic plants but also with those complex plants characterized by severe non-linearity, uncertainties and non-minimum phase behaviours. Two simulation studies are provided to demonstrate the effectiveness of the controller design procedure.

Self-tuning proportional, integral and derivative controller based on genetic algorithm least squares

A self-tuning proportional, integral and derivative control scheme based on genetic algorithms (GAs) is proposed and applied to the control of a real industrial plant. This paper explores the improvement in the parameter estimator, which is an essential part of an adaptive controller, through the hybridization of recursive least-squares algorithms by making use of GAs and the possibility of the application of GAs to the control of industrial processes. Both the simulation results and the experiments on a real plant show that the proposed scheme can be applied effectively.

Regularization of Descriptor Systems by Derivative and Proportional State Feedback

For linear multivariable time-invariant continuous or discrete-time singular systems it is customary to use a proportional feedback control in order to achieve a desired closed loop behaviour. Derivative feedback is rarely considered. This paper examines how derivative feedback in descriptor systems can be used to alter the structure of the system pencil under various controllability conditions. It is shown that derivative and proportional feedback controls can be constructed such that the closed loop system has a given form and is also regular and has index at most 1. This property ensures the solvability of the resulting system of dynamic-algebraic equations. The construction procedures used to establish the theory are based only on orthogonal matrix decompositions and can therefore be implemented in a numerically stable way. The problem of pole placement with derivative feedback alone and in combination with proportional state feedback is also investigated. A computational algorithm for improving the “conditioning” of the regularized closed loop system is derived.

AID enzymatic activity is inversely proportional to the size of cytosine C5 orbital cloud

Activation induced deaminase (AID) deaminates cytosine to uracil, which is required for a functional humoral immune system. Previous work demonstrated, that AID also deaminates 5-methylcytosine (5 mC). Recently, a novel vertebrate modification (5-hydroxymethylcytosine - 5 hmC) has been implicated in functioning in epigenetic reprogramming, yet no molecular pathway explaining the removal of 5 hmC has been identified. AID has been suggested to deaminate 5 hmC, with the 5 hmU product being repaired by base excision repair pathways back to cytosine. Here we demonstrate that AID’s enzymatic activity is inversely proportional to the electron cloud size of C5-cytosine - H . F . methyl .. hydroxymethyl. This makes AID an unlikely candidate to be part of 5 hmC removal.

The origins and impact of proportional representation

This article in the peer-reviewed Oxford Bibliographies series, gives an introduction to the literatures on the varieties, origins, and effects of proportional electoral systems.

Support for the far right in the 2014 European Parliament Elections: a comparative perspective

The May 2014 European Parliament (EP) elections were characterised by the success of far-right Eurosceptic parties, including the French Front National, UKIP, the Danish People’s Party, the Hungarian Jobbik, the Austrian FPÖ, the True Finns and the Greek Golden Dawn. However, a closer look at the results across Europe indicates that the success of far-right parties in the EP elections is neither a linear nor a clear-cut phenomenon: (1) the far right actually declined in many European countries compared to the 2009 results; (2) some of the countries that have experienced the worst of the economic crisis, including Spain, Portugal and Ireland, did not experience a significant rise in far-right party support; and (3) ‘far right’ is too broad an umbrella term, covering parties that are too different from each other to be grouped in one single party family.

Radical left-wing Euroscepticism in the 2014 elections: a cross-European comparison

This article examines the varied performance of radical left-wing Eurosceptic parties during the 2014 EP elections. While the performance of the radical right during this 'earthquake' election has been widely discussed, little attention has been paid to the radical left. The article examines the result comparatively, and identifies that: (1) across Europe, radical left-wing euroscepticism is limited to few countries, including Greece, Cyprus, France and Portugal; (2) the countries that have experienced the worst of the economic crisis did not experience a significant rise in far right-wing party support but did experience the rise of left-wing euroscepticism; (3) from this sample only Greece experienced the rise of both the radical right and radical left.

The rise of the far right in debtor and creditor European countries: the case of European Parliament elections

While the 2014 European Parliament elections were marked by the rise of far right-wing parties, the different patterns of support that we observe across Europe and across time are not directly related to the economic crisis. Indeed, economic hardship seems neither sufficient nor necessary for the rise of such parties to occur. Using the cross-national results for the 2004, 2009 and 2014 EP elections in order to capture time and country variations, we posit the economy affects the rise of far right-wing parties in more complex ways. Specifically, we compare the experience of high debt countries (the ‘debtors’) and the others (the ‘creditors’) and explore the relationship between far right-wing party success on the one hand, and unemployment, inequality, immigration, globalization and the welfare state on the other hand. Our discussion suggests there might be a trade off between budgetary stability and far right-wing party support, but the choice between Charybdis and Scylla may be avoided if policy makers carefully choose which policies should bear the brunt of the fiscal adjustment.

Risks, costs and labour markets: explaining cross-national patterns of far right party success in European Parliament elections

What is the impact of the economy on cross national variation in far right-wing party support? This paper tests several hypotheses from existing literature on the results of the last three EP elections in all EU member states. We conceptualise the economy affects support because unemployment heightens the risks and costs that the population faces, but this is crucially mediated by labour market institutions. Findings from multiple regression analyses indicate that unemployment, real GDP growth, debt and deficits have no statistically significant effect on far right-wing party support at the national level. By contrast, labour markets influence costs and risks: where unemployment benefits and dismissal regulations are high, unemployment has no effect, but where either one of them is low, unemployment leads to higher far right-wing party support. This explains why unemployment has not led to far right-wing party support in some European countries that experienced the 2008 Eurozone crisis.

Forecasting elections

In this paper we assess opinion polls, prediction markets, expert opinion and statistical modelling over a large number of US elections in order to determine which perform better in terms of forecasting outcomes. In line with existing literature, we bias-correct opinion polls. We consider accuracy, bias and precision over different time horizons before an election, and we conclude that prediction markets appear to provide the most precise forecasts and are similar in terms of bias to opinion polls. We find that our statistical model struggles to provide competitive forecasts, while expert opinion appears to be of value. Finally we note that the forecast horizon matters; whereas prediction market forecasts tend to improve the nearer an election is, opinion polls appear to perform worse, while expert opinion performs consistently throughout. We thus contribute to the growing literature comparing election forecasts of polls and prediction markets.