Dynamic integrated system optimization and parameter estimation for discrete time optimal control of nonlinear systems

An algorithm for solving nonlinear discrete time optimal control problems with model-reality differences is presented. The technique uses Dynamic Integrated System Optimization and Parameter Estimation (DISOPE), which achieves the correct optimal solution in spite of deficiencies in the mathematical model employed in the optimization procedure. A version of the algorithm with a linear-quadratic model-based problem, implemented in the C+ + programming language, is developed and applied to illustrative simulation examples. An analysis of the optimality and convergence properties of the algorithm is also presented.

Optimal control of nonlinear systems represented by differential algebraic equations

An iterative procedure is described for solving nonlinear optimal control problems subject to differential algebraic equations. The procedure iterates on an integrated modified simplified model based problem with parameter updating in such a manner that the correct solution of the original nonlinear problem is achieved.

Mechatronic design of a high frequency probe for haptic interaction

Current force feedback, haptic interface devices are generally limited to the display of low frequency, high amplitude spatial data. A typical device consists of a low impedance framework of one or more degrees-of-freedom (dof), allowing a user to explore a pre-defined workspace via an end effector such as a handle, thimble, probe or stylus. The movement of the device is then constrained using high gain positional feedback, thus reducing the apparent dof of the device and conveying the illusion of hard contact to the user. Such devices are, however, limited to a narrow bandwidth of frequencies, typically below 30Hz, and are not well suited to the display of surface properties, such as object texture. This paper details a device to augment an existing force feedback haptic display with a vibrotactile display, thus providing a means of conveying low amplitude, high frequency spatial information of object surface properties. 1. Haptics and Haptic Interfaces Haptics is the study of human touch and interaction with the external environment via touch. Information from the human sense of touch can be classified in to two categories, cutaneous and kinesthetic. Cutaneous information is provided via the mechanoreceptive nerve endings in the glabrous skin of the human hand. It is primarily a means of relaying information regarding small-scale details in the form of skin stretch, compression and vibration.

Peptidomimetic design of unusual turns by incorporating flexible and rigid omega-amino acids simultaneously

The tripeptides Boc-Gly-Aib-m-ABA-OMe (I), Boc-beta Ala-Aib-m-ABA-OMe (II) and Boc-gamma Abu-Aib-rn-ABA-OMe (III) (Aib: alpha-aminoisobutyric acid, beta Ala: beta-alanine, gamma Abu: gamma-aminobutyric acid, m-ABA: meta-aminobenzoic acid) with homologated amino acids at the N-terminus, the rigid gamma-amino acid m-ABA at the C-terminus and the helicogenic Aib at the central position have been chosen to create unusual turns. Single crystal X-ray diffraction studies, solvent dependent NMR titrations and 2D NMR analysis reveal that peptides II and III adopt unusual turns of 11- and 12-membered rings stabilized by modified 4 -> 1 type intramolecular hydrogen bonds. Solution phase studies indicate that peptide I exists in the beta-turn conformation stabilized by 10-membered intramolecular hydrogen bonding.

Implementation of VR systems: a comparison between the early adoption of CAD and current uptake of VR

Use of new technologies, such as virtual reality (VR), is important to corporations, yet understanding of their successful implementation is insuf. ciently developed. In this paper a case study is used to analyse the introduction of VR use in a British housebuilding company. Although the implementation was not successful in the manner initially anticipated, the study provides insight into the process of change, the constraints that inhibit implementation and the relationship between new technology and work organization. Comparison is made with the early use of CAD and similarities and differences between empirical . ndings of the case study and the previous literature are discussed.

Inverting recurrent neural networks for internal model control of nonlinear systems

In this paper, we show how a set of recently derived theoretical results for recurrent neural networks can be applied to the production of an internal model control system for a nonlinear plant. The results include determination of the relative order of a recurrent neural network and invertibility of such a network. A closed loop controller is produced without the need to retrain the neural network plant model. Stability of the closed-loop controller is also demonstrated.

Internal model control of nonlinear systems through the inversion of recurrent neural networks

Recurrent neural networks can be used for both the identification and control of nonlinear systems. This paper takes a previously derived set of theoretical results about recurrent neural networks and applies them to the task of providing internal model control for a nonlinear plant. Using the theoretical results, we show how an inverse controller can be produced from a neural network model of the plant, without the need to train an additional network to perform the inverse control.

Identification of nonlinear systems with a dynamic recurrent neural network

Two approaches are presented to calculate the weights for a Dynamic Recurrent Neural Network (DRNN) in order to identify the input-output dynamics of a class of nonlinear systems. The number of states of the identified network is constrained to be the same as the number of states of the plant.

The control of dynamical systems by neural networks

In this paper the use of neural networks for the control of dynamical systems is considered. Both identification and feedback control aspects are discussed as well as the types of system for which neural networks can provide a useful technique. Multi-layer Perceptron and Radial Basis function neural network types are looked at, with an emphasis on the latter. It is shown how basis function centre selection is a critical part of the implementation process and that multivariate clustering algorithms can be an extremely useful tool for finding centres.

Connectivity measures for internet topologies on the level of autonomous systems

Classical measures of network connectivity are the number of disjoint paths between a pair of nodes and the size of a minimum cut. For standard graphs, these measures can be computed efficiently using network flow techniques. However, in the Internet on the level of autonomous systems (ASs), referred to as AS-level Internet, routing policies impose restrictions on the paths that traffic can take in the network. These restrictions can be captured by the valley-free path model, which assumes a special directed graph model in which edge types represent relationships between ASs. We consider the adaptation of the classical connectivity measures to the valley-free path model, where it is -hard to compute them. Our first main contribution consists of presenting algorithms for the computation of disjoint paths, and minimum cuts, in the valley-free path model. These algorithms are useful for ASs that want to evaluate different options for selecting upstream providers to improve the robustness of their connection to the Internet. Our second main contribution is an experimental evaluation of our algorithms on four types of directed graph models of the AS-level Internet produced by different inference algorithms. Most importantly, the evaluation shows that our algorithms are able to compute optimal solutions to instances of realistic size of the connectivity problems in the valley-free path model in reasonable time. Furthermore, our experimental results provide information about the characteristics of the directed graph models of the AS-level Internet produced by different inference algorithms. It turns out that (i) we can quantify the difference between the undirected AS-level topology and the directed graph models with respect to fundamental connectivity measures, and (ii) the different inference algorithms yield topologies that are similar with respect to connectivity and are different with respect to the types of paths that exist between pairs of ASs.

The design of probiotic studies to substantiate health claims

The EC Regulation No. 1924/2006 on Nutrition and Health claims made on foods has generated considerable debate and concern among scientists and industry. At the time of writing, the European Food Safety Authority (EFSA) has not approved any probiotic claims despite numerous human trials and meta-analyses showing evidence of beneficial effects. On 29th and 30th September 2010, ten independent, academic scientists with a documented record in probiotic research, met to discuss designs for future probiotic studies to demonstrate health benefits for gut and immune function. The expert panel recommended the following: (i) always formulate a precise and concrete hypothesis, and appropriate goals and parameters before starting a trial; (ii) ensure trials have sufficient sample size, such that they are adequately powered to reach statistically significant conclusions, either supporting or rejecting the a priori hypothesis, taking into account adjustment for multiple testing (this might necessitate more than one recruitment site); (iii) ensure trials are of appropriate duration; (iv) focus on a single, primary objective and only evaluate multiple parameters when they are hypothesis-driven. The panel agreed that there was an urgent need to better define which biomarkers are considered valuable for substantiation of a health claim. As a first step, the panel welcomed the publication on the day of the meeting of EFSA's draft guidance document on immune and gut health, although it came too late for study designs and dossiers to be adjusted accordingly. New validated biomarkers need to be identified in order to properly determine the range of physiological functions influenced by probiotics. In addition, validated biomarkers reflecting risk factors for disease, are required for article 14 claims (EC Regulation No. 1924/2006). Finally, the panel concluded that consensus among scientists is needed to decide appropriate clinical endpoints for trials.