Adaptive deadbeat control of stochastic systems

This paper considers the use of a discrete-time deadbeat control action on systems affected by noise. Variations on the standard controller form are discussed and comparisons are made with controllers in which noise rejection is a higher priority objective. Both load and random disturbances are considered in the system description, although the aim of the deadbeat design remains as a tailoring of reference input variations. Finally, the use of such a deadbeat action within a self-tuning control framework is shown to satisfy, under certain conditions, the self-tuning property, generally though only when an extended form of least-squares estimation is incorporated.

Auto-weighted minimum-variance self-tuning controller

A self-tuning controller which automatically assigns weightings to control and set-point following is introduced. This discrete-time single-input single-output controller is based on a generalized minimum-variance control strategy. The automatic on-line selection of weightings is very convenient, especially when the system parameters are unknown or slowly varying with respect to time, which is generally considered to be the type of systems for which self-tuning control is useful. This feature also enables the controller to overcome difficulties with non-minimum phase systems.

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.

Neural networks for linear control: an analysis

This paper considers the use of radial basis function and multi-layer perceptron networks for linear or linearizable, adaptive feedback control schemes in a discrete-time environment. A close look is taken at the model structure selected and the extent of the resulting parameterization. A comparison is made with standard, nonneural network algorithms, e.g. self-tuning control.

A critique of neural networks for discrete-time linear control

This paper discusses the use of multi-layer perceptron networks for linear or linearizable, adaptive feedback.control schemes in a discrete-time environment. A close look is taken at the model structure selected and the extent of the resulting parametrization. A comparison is made with standard, non-perceptron algorithms, e.g. self-tuning control, and it is shown how gross over-parametrization can occur in the neural network case. Because of the resultant heavy computational burden and poor controller convergence, a strong case is made against the use of neural networks for discrete-time linear control.

Hydrogelation of self-assembling RGD-based peptides

The self-assembly of tripeptides based on the RGD cell adhesion motif is investigated. Two tripeptides containing the Fmoc [N-(fluorenyl)-9-methoxycarbonyl] aromatic unit were synthesized, Fmoc-RGD and a control peptide containing a scrambled sequence, Fmoc-GRD. The Fmoc is used to control selfassembly via aromatic stacking interactions. The self-assembly and hydrogelation properties of the two Fmoc-tripeptides are compared. Both form well defined amyloid fibrils (as shown by cryo-TEM and SAXS) with b-sheet features in their circular dichroism and FTIR spectra. Both peptides form selfsupporting hydrogels, the dynamic shear modulus of which was measured. Preliminary cell culture experiments reveal that Fmoc-RGD can be used as a support for bovine fibroblasts, but not Fmoc- GRD, consistent with the incorporation of the cell adhesion motif in the former peptide.

Adaptive control: an insight

In this article, an overview is given of some of the more common approaches taken in applying adaptive control. Gain scheduling, model reference control and self-tuning control are all discussed and in each case suggestions are given for further reading.

Self-centred memories: the reminiscence bump and the self

The self-memory relationship is thought to be bidirectional, in such a way that memories provide context for the self, and equally, the self exercises control over retrieval (Conway, 2005). Autobiographical memories are not distributed equally across the life span; instead, memories peak between ages 10 and 30. This reminiscence bump has been suggested to support the emergence of a stable and enduring self. In the present study, the relationship between memory accessibility and self was explored with a novel methodology that used generation of self images in the form of I am statements. Memories generated from I am cues clustered around the time of emergence for that particular self image. We argue that, when a new self-image is formed, it is associated with the encoding of memories that are relevant to that self and that remain highly accessible to the rememberer later in life. This study offers a new methodology for academics and clinicians interested in the relationship between memory and identity.

Simplified PID self-tuning controller for robotic manipulators

The paper describes a self-tuning adaptive PID controller suitable for use in the control of robotic manipulators. The scheme employs a simple recursive estimator which reduces the computational effort to an acceptable level for many applications in robotics.

Self-tuning property of state-space self tuners

The basic assumption from implicit self-tuning theory is that, for self tuning to occur, the control input obtained from the estimated system model converges to the value whic would be obtained if the system parameters were known. As as direct result of this, only certain control strategies are acceptable. Here a general rule for the self-tuning property of pole-placement self tuners is obtained, and previous strategies are shown to be special cases of this.

Control of strand registry by attachment of PEG chains to amyloid peptides influences nanostructure

The self-assembly in aqueous solution of PEG-peptide conjugates comprising a model amyloid peptide sequence FFKLVFF that contains the Ab(16–20) KLVFF motif is investigated. X-ray diffraction reveals different packing motifs dependent on PEG chain length. This is correlated to remarkable differences in self-assembled nanostructures. The control of strand registry points to a subtle interplay between aromatic stacking, electrostatic and amphiphilic interactions.

Selecting valuable information to remember: age-related differences and similarities in self-regulated learning

It is often necessary to selectively attend to important information, at the expense of less important information, especially if you know you cannot remember large amounts of information. The present study examined how younger and older adults select valuable information to study, when given unrestricted choices about how to allocate study time. Participants were shown a display of point values ranging from 1–30. Participants could choose which values to study, and the associated word was then shown. Study time, and the choice to restudy words, was under the participant's control during the 2-minute study session. Overall, both age groups selected high value words to study and studied these more than the lower value words. However, older adults allocated a disproportionately greater amount of study time to the higher-value words, and age-differences in recall were reduced or eliminated for the highest value words. In addition, older adults capitalized on recency effects in a strategic manner, by studying high-value items often but also immediately before the test. A multilevel mediation analysis indicated that participants strategically remembered items with higher point value, and older adults showed similar or even stronger strategic process that may help to compensate for poorer memory. These results demonstrate efficient (and different) metacognitive control operations in younger and older adults, which can allow for strategic regulation of study choices and allocation of study time when remembering important information. The findings are interpreted in terms of life span models of agenda-based regulation and discussed in terms of practical applications. (PsycINFO Database Record (c) 2013 APA, all rights reserved)(journal abstract)

Bioactive films produced from self-assembling peptide amphiphiles as versatile substrates for tuning cell adhesion and tissue architecture in serum-free conditions

The development of versatile bioactive surfaces able to emulate in vivo conditions is of enormous importance to the future of cell and tissue therapy. Tuning cell behaviour on two-dimensional surfaces so that the cells perform as if they were in a natural three-dimensional tissue represents a significant challenge, but one that must be met if the early promise of cell and tissue therapy is to be fully realised. Due to the inherent complexities involved in the manufacture of biomimetic three-dimensional substrates, the scaling up of engineered tissue-based therapies may be simpler if based upon proven two-dimensional culture systems. In this work, we developed new coating materials composed of the self-assembling peptide amphiphiles (PAs) C16G3RGD (RGD) and C16G3RGDS (RGDS) shown to control cell adhesion and tissue architecture while avoiding the use of serum. When mixed with the C16ETTES diluent PA at 13 : 87 (mol mol-1) ratio at 1.25 times 10-3 M, the bioactive {PAs} were shown to support optimal adhesion, maximal proliferation, and prolonged viability of human corneal stromal fibroblasts ({hCSFs)}, while improving the cell phenotype. These {PAs} also provided stable adhesive coatings on highly-hydrophobic surfaces composed of striated polytetrafluoroethylene ({PTFE)}, significantly enhancing proliferation of aligned cells and increasing the complexity of the produced tissue. The thickness and structure of this highly-organised tissue were similar to those observed in vivo, comprising aligned newly-deposited extracellular matrix. As such, the developed coatings can constitute a versatile biomaterial for applications in cell biology, tissue engineering, and regenerative medicine requiring serum-free conditions.

Self-assembling amphiphilic peptides

The self-assembly of several classes of amphiphilic peptides is reviewed, and selected applications are discussed. We discuss recent work on the self-assembly of lipopeptides, surfactant-like peptides and amyloid peptides derived from the amyloid-β peptide. The influence of environmental variables such as pH and temperature on aggregate nanostructure is discussed. Enzyme-induced remodelling due to peptide cleavage and nanostructure control through photocleavage or photo-cross-linking are also considered. Lastly, selected applications of amphiphilic peptides in biomedicine and materials science are outlined.