Solving optimal control problems with state constraints using nonlinear programming and simulation tools

This paper illustrates how nonlinear programming and simulation tools, which are available in packages such as MATLAB and SIMULINK, can easily be used to solve optimal control problems with state- and/or input-dependent inequality constraints. The method presented is illustrated with a model of a single-link manipulator. The method is suitable to be taught to advanced undergraduate and Master's level students in control engineering.

A forward-constrained regression algorithm for sparse kernel density estimation

Using the classical Parzen window (PW) estimate as the target function, the sparse kernel density estimator is constructed in a forward-constrained regression (FCR) manner. The proposed algorithm selects significant kernels one at a time, while the leave-one-out (LOO) test score is minimized subject to a simple positivity constraint in each forward stage. The model parameter estimation in each forward stage is simply the solution of jackknife parameter estimator for a single parameter, subject to the same positivity constraint check. For each selected kernels, the associated kernel width is updated via the Gauss-Newton method with the model parameter estimate fixed. The proposed approach is simple to implement and the associated computational cost is very low. Numerical examples are employed to demonstrate the efficacy of the proposed approach.

A forward constrained selection algorithm for probabilistic neural network

A new probabilistic neural network (PNN) learning algorithm based on forward constrained selection (PNN-FCS) is proposed. An incremental learning scheme is adopted such that at each step, new neurons, one for each class, are selected from the training samples arid the weights of the neurons are estimated so as to minimize the overall misclassification error rate. In this manner, only the most significant training samples are used as the neurons. It is shown by simulation that the resultant networks of PNN-FCS have good classification performance compared to other types of classifiers, but much smaller model sizes than conventional PNN.

Long-lived halocarbon trends and budgets from atmospheric chemistry modelling constrained with measurements in polar firn

The budgets of seven halogenated gases (CFC-11, CFC-12, CFC-113, CFC-114, CFC-115, CCl4 and SF6) are studied by comparing measurements in polar firn air from two Arctic and three Antarctic sites, and simulation results of two numerical models: a 2-D atmospheric chemistry model and a 1-D firn diffusion model. The first one is used to calculate atmospheric concentrations from emission trends based on industrial inventories; the calculated concentration trends are used by the second one to produce depth concentration profiles in the firn. The 2-D atmospheric model is validated in the boundary layer by comparison with atmospheric station measurements, and vertically for CFC-12 by comparison with balloon and FTIR measurements. Firn air measurements provide constraints on historical atmospheric concentrations over the last century. Age distributions in the firn are discussed using a Green function approach. Finally, our results are used as input to a radiative model in order to evaluate the radiative forcing of our target gases. Multi-species and multi-site firn air studies allow to better constrain atmospheric trends. The low concentrations of all studied gases at the bottom of the firn, and their consistency with our model results confirm that their natural sources are small. Our results indicate that the emissions, sinks and trends of CFC-11, CFC-12, CFC-113, CFC-115 and SF6 are well constrained, whereas it is not the case for CFC-114 and CCl4. Significant emission-dependent changes in the lifetimes of halocarbons destroyed in the stratosphere were obtained. Those result from the time needed for their transport from the surface where they are emitted to the stratosphere where they are destroyed. Efforts should be made to update and reduce the large uncertainties on CFC lifetimes.

Flexible rules cum constrained discretion: a new consensus in monetary policy

This paper demonstrates that recent influential contributions to monetary policy imply an emerging consensus whereby neither rigid rules nor complete discretion are found optimal. Instead, middle-ground monetary regimes based on rules (operative under 'normal' circumstances) to anchor inflation expectations over the long run, but designed with enough flexibility to mitigate the short-run effect of shocks (with communicated discretion in 'exceptional' circumstances temporarily overriding these rules), are gaining support in theoretical models and policy formulation and implementation. The opposition of 'rules versus discretion' has, thus, reappeared as the synthesis of 'rules cum discretion', in essence as inflation-forecast targeting. But such synthesis is not without major theoretical problems, as we argue in this contribution. Furthermore, the very recent real-world events have made it obvious that the inflation targeting strategy of monetary policy, which rests upon the new consensus paradigm in modern macroeconomics is at best a 'fair weather' model. In the turbulent economic climate of highly unstable inflation, deep financial crisis and world-wide, abrupt economic slowdown nowadays this approach needs serious rethinking to say the least, if not abandoning it altogether

Climate change justice: getting motivated in the last chance saloon

A key reason for pessimism with respect to greenhouse gas emissions reduction relates to the ‘motivation problem’, whereby those who could make the biggest difference prima facie have the least incentive to act because they are most able to adapt: how can we motivate such people (and thereby everyone else) to accept, indeed to initiate, the changes to their lifestyles that are required for effective emissions reductions? This paper offers an account inspired by Rawls of the good of membership of ‘intergenerational cooperative union’ to achieve justice that provides a solution to the motivation problem.

The programming language standards scene, ten years on paper 19: Pop

This paper, one of a simultaneously published set, describes the establishment in 1990 of the UK standards project for the Pop programming language, and the progress of the project to the end of 1993.

POP-11 comes of age: the advancement of an AI programming language

In 1989, the computer programming language POP-11 is 21 years old. This book looks at the reasons behind its invention, and traces its rise from an experimental language to a major AI language, playing a major part in many innovating projects. There is a chapter on the inventor of the language, Robin Popplestone, and a discussion of the applications of POP-11 in a variety of areas. The efficiency of AI programming is covered, along with a comparison between POP-11 and other programming languages. The book concludes by reviewing the standardization of POP-11 into POP91.

Constrained surplus energy adaptive blind CDMA detection

The blind minimum output energy (MOE) adaptive detector for code division multiple access (CDMA) signals requires exact knowledge of the received spreading code of the desired user. This requirement can be relaxed by constraining the so-called surplus energy of the adaptive tap-weight vector, but the ideal constraint value is not easily obtained in practice. An algorithm is proposed to adaptively track this value and hence to approach the best possible performance for this class of CDMA detector.

Towards a modular robotics standard for AGV design and programming

Across the world there are many bodies currently involved in researching into the design of autonomous guided vehicles (AGVs). One of the greatest problems at present however, is that much of the research work is being conducted in isolated groups, with the resulting AGVs sensor/control/command systems being almost completely nontransferable to other AGV designs. This paper describes a new modular method for robot design which when applied to AGVs overcomes the above problems. The method is explained here with respect to all forms of robotics but the examples have been specifically chosen to reflect typical AGV systems.

Manual response preparation and saccade programming are linked to attention shifts: ERP evidence for covert attentional orienting and spatially specific modulations of visual processing

The premotor theory of attention claims that attentional shifts are triggered during response programming, regardless of which response modality is involved. To investigate this claim, event-related brain potentials (ERPs) were recorded while participants covertly prepared a left or right response, as indicated by a precue presented at the beginning of each trial. Cues signalled a left or right eye movement in the saccade task, and a left or right manual response in the manual task. The cued response had to be executed or withheld following the presentation of a Go/Nogo stimulus. Although there were systematic differences between ERPs triggered during covert manual and saccade preparation, lateralised ERP components sensitive to the direction of a cued response were very similar for both tasks, and also similar to the components previously found during cued shifts of endogenous spatial attention. This is consistent with the claim that the control of attention and of covert response preparation are closely linked. N1 components triggered by task-irrelevant visual probes presented during the covert response preparation interval were enhanced when these probes were presented close to cued response hand in the manual task, and at the saccade target location in the saccade task. This demonstrates that both manual and saccade preparation result in spatially specific modulations of visual processing, in line with the predictions of the premotor theory.