Learning soft computing control strategies in a modular neural network architecture

Modelling and control of nonlinear dynamical systems is a challenging problem since the dynamics of such systems change over their parameter space. Conventional methodologies for designing nonlinear control laws, such as gain scheduling, are effective because the designer partitions the overall complex control into a number of simpler sub-tasks. This paper describes a new genetic algorithm based method for the design of a modular neural network (MNN) control architecture that learns such partitions of an overall complex control task. Here a chromosome represents both the structure and parameters of an individual neural network in the MNN controller and a hierarchical fuzzy approach is used to select the chromosomes required to accomplish a given control task. This new strategy is applied to the end-point tracking of a single-link flexible manipulator modelled from experimental data. Results show that the MNN controller is simple to design and produces superior performance compared to a single neural network (SNN) controller which is theoretically capable of achieving the desired trajectory. (C) 2003 Elsevier Ltd. All rights reserved.

Effects of Constraint Errors on Parallel Manipulators with Decoupled Motion

From perspective of structure synthesis, certain special geometric constraints, such as joint axes intersecting at one point or perpendicular to each other, are necessary in realizing the end-effector motion of kinematically decoupled parallel manipulators (PMs) along individual motion axes. These requirements are difficult to achieve in the actual system due to assembly errors and manufacturing tolerances. Those errors that violate the geometric constraint requirements are termed “constraint errors”. The constraint errors usually are more troublesome than other manipulator errors because the decoupled motion characteristics of the manipulator may no longer exist and the decoupled kinematic models will be rendered useless due to these constraint errors. Therefore, identification and prevention of these constraint errors in initial design and manufacturing stage are of great significance. In this article, three basic types of constraint errors are identified, and an approach to evaluate the effects of constraint errors on decoupling characteristics of PMs is proposed. This approach is illustrated by a 6-DOF PM with decoupled translation and rotation. The results show that the proposed evaluation method is effective to guide design and assembly.

A hierarchical multiclass support vector machine incorporated with holistic triple learning units

This paper proposes a new hierarchical learning structure, namely the holistic triple learning (HTL), for extending the binary support vector machine (SVM) to multi-classification problems. For an N-class problem, a HTL constructs a decision tree up to a depth of A leaf node of the decision tree is allowed to be placed with a holistic triple learning unit whose generalisation abilities are assessed and approved. Meanwhile, the remaining nodes in the decision tree each accommodate a standard binary SVM classifier. The holistic triple classifier is a regression model trained on three classes, whose training algorithm is originated from a recently proposed implementation technique, namely the least-squares support vector machine (LS-SVM). A major novelty with the holistic triple classifier is the reduced number of support vectors in the solution. For the resultant HTL-SVM, an upper bound of the generalisation error can be obtained. The time complexity of training the HTL-SVM is analysed, and is shown to be comparable to that of training the one-versus-one (1-vs.-1) SVM, particularly on small-scale datasets. Empirical studies show that the proposed HTL-SVM achieves competitive classification accuracy with a reduced number of support vectors compared to the popular 1-vs-1 alternative.

Juxtaposition and Non-Motion: Varese Bridges Modernism and Electroacoustic Music

Edgard Vare` se’s Poe` me e´ lectronique can be viewed as a bridge between early twentieth-century modernism and electroacoustic music. This connection to early modernism is most clearly seen in its use of musical juxtaposition, a favoured technique of early modernist composers, especially those active in Paris. Juxtaposition and non-motion are considered here, particularly in relationship to Smalley’s exposition of spectromorphology (Smalley 1986), which in its preoccupation with motion omits any significant consideration of non-motion. Juxtaposition and non-motion have an important history within twentieth-century music, and as an early classic of electroacoustic music, Poe` me e´ lectronique is a particularly striking example of a composition that is rich in juxtapositions similar to those found in passages of early modernist music. Examining Poe` me e´ lectronique through the lens of juxtaposition and non-motion reveals how the organisation of its juxtaposed sounds encourages the experience of sound structure suspended time.

Fast automatic two-stage nonlinear model identification based on the extreme learning machine

It is convenient and effective to solve nonlinear problems with a model that has a linear-in-the-parameters (LITP) structure. However, the nonlinear parameters (e.g. the width of Gaussian function) of each model term needs to be pre-determined either from expert experience or through exhaustive search. An alternative approach is to optimize them by a gradient-based technique (e.g. Newton’s method). Unfortunately, all of these methods still need a lot of computations. Recently, the extreme learning machine (ELM) has shown its advantages in terms of fast learning from data, but the sparsity of the constructed model cannot be guaranteed. This paper proposes a novel algorithm for automatic construction of a nonlinear system model based on the extreme learning machine. This is achieved by effectively integrating the ELM and leave-one-out (LOO) cross validation with our two-stage stepwise construction procedure [1]. The main objective is to improve the compactness and generalization capability of the model constructed by the ELM method. Numerical analysis shows that the proposed algorithm only involves about half of the computation of orthogonal least squares (OLS) based method. Simulation examples are included to confirm the efficacy and superiority of the proposed technique.

Playful structure: a novel image of early years pedagogy for primary school classrooms

Playful structure is a new pedagogic image representing a more balanced and integrated perspective on early years pedagogy, aiming to blend apparent dichotomies and contradictions and to sustain and evolve play-based practice beyond Year 1. Playful structure invites teachers and children to initiate and maintain a degree of playfulness in the child’s whole learning experience, even when the learning intentions demand a supportive structure. Thus, playfulness becomes characteristic of the interaction between adult and the child and not just characteristic of child-initiated versus adult-initiated activities, or of play-time versus task-time. The paper is based on intensive observations and interviews with teachers in Northern Ireland who participated in a play-based and informal curriculum. This paper explains how playful structure rests on complementary processes of infusion of structure into play-based activities and infusion of playfulness into more structured activities, illustrated by cameos. ‘Infusion’ suggests the subtle blending process that allows apparent dichotomies and contradictions to be resolved in practice.

Using location-aware technology for learning Geography in a real digital space outside the classroom

The use of new mobile technologies is still in its infancy in many secondary schools and there is limited evidence of the educational and pedagogical benefits on pupils’ learning in the formal school context. This qualitative study focuses on the use of handheld devices to teach a topic in geography to an examination class. Action research combined with pupil observations and focus group interviews are used to capture the pupils’ experiences of using mediascapes. Activity Theory is used as a lens to structure the analysis of the data and to report on the cognitive and affective impact of m-learning on pupils’ academic performance in the topic. Increased attainment and the development of wider skills for lifelong learning were identified in the study. The adaptability of the majority of pupils to the technology resulted in increased levels of willingness to learn in this novel context.

A New Gradient Descent Approach for Local Learning of Fuzzy Neural Models

The majority of reported learning methods for Takagi-Sugeno-Kang fuzzy neural models to date mainly focus on the improvement of their accuracy. However, one of the key design requirements in building an interpretable fuzzy model is that each obtained rule consequent must match well with the system local behaviour when all the rules are aggregated to produce the overall system output. This is one of the distinctive characteristics from black-box models such as neural networks. Therefore, how to find a desirable set of fuzzy partitions and, hence, to identify the corresponding consequent models which can be directly explained in terms of system behaviour presents a critical step in fuzzy neural modelling. In this paper, a new learning approach considering both nonlinear parameters in the rule premises and linear parameters in the rule consequents is proposed. Unlike the conventional two-stage optimization procedure widely practised in the field where the two sets of parameters are optimized separately, the consequent parameters are transformed into a dependent set on the premise parameters, thereby enabling the introduction of a new integrated gradient descent learning approach. A new Jacobian matrix is thus proposed and efficiently computed to achieve a more accurate approximation of the cost function by using the second-order Levenberg-Marquardt optimization method. Several other interpretability issues about the fuzzy neural model are also discussed and integrated into this new learning approach. Numerical examples are presented to illustrate the resultant structure of the fuzzy neural models and the effectiveness of the proposed new algorithm, and compared with the results from some well-known methods.

Computational learning of the conditional phase-type (C-Ph) distribution: Learning C-Ph distributions

This paper presents a new algorithm for learning the structure of a special type of Bayesian network. The conditional phase-type (C-Ph) distribution is a Bayesian network that models the probabilistic causal relationships between a skewed continuous variable, modelled by the Coxian phase-type distribution, a special type of Markov model, and a set of interacting discrete variables. The algorithm takes a dataset as input and produces the structure, parameters and graphical representations of the fit of the C-Ph distribution as output.The algorithm, which uses a greedy-search technique and has been implemented in MATLAB, is evaluated using a simulated data set consisting of 20,000 cases. The results show that the original C-Ph distribution is recaptured and the fit of the network to the data is discussed.

Learning transfer in multinational companies:Explaining inter-organisation variation

This article addresses the extent to which multinational companies (MNCs) in Ireland deploy practices aimed at the transfer of learning in their operations and the factors explaining inter-organisation variation in so doing. Using data from 260 MNCs, we find that comparatively large numbers of firms deploy practices to transfer learning in their Irish operations. Most notably, we find that almost half of all MNCs have a formal policy on organisational learning, while more than six in every ten MNCs in Ireland utilise three or more learning transfer mechanisms. In investigating inter-organisation variation with respect to these, we test a number of hypotheses involving nationality, sectoral, MNC (e.g. organisation structure) and HR factors. Our results show that the presence of international HR structures is a significant factor in explaining learning transfer in MNCs. We also find support that employment size, sector and integration between the MNC's global operations are useful variables in explaining variation in the deployment of practices on learning transfer in MNCs. © 2009 Blackwell Publishing Ltd.

Influence of a Single Grain Boundary on Domain Wall Motion in Ferroelectrics

Epitaxial tetragonal 425 and 611 nm thick Pb(ZrTi)O (PZT) films are deposited by pulsed laser deposition on SrRuO-coated (100) SrTiO 24° tilt angle bicrystal substrates to create a single PZT grain boundary with a well-defined orientation. On either side of the bicrystal boundary, the films show square hysteresis loops and have dielectric permittivities of 456 and 576, with loss tangents of 0.010 and 0.015, respectively. Using piezoresponse force microscopy (PFM), a decrease in the nonlinear piezoelectric response is observed in the vicinity (720-820 nm) of the grain boundary. This region represents the width over which the extrinsic contributions to the piezoelectric response (e.g., those associated with the domain density/configuration and/or the domain wall mobility) are influenced by the presence of the grain boundary. Transmission electron microscope (TEM) images collected near and far from the grain boundary indicate a strong preference for (101)/(1-01) type domain walls at the grain boundary, whereas (011)/(01-1) and (101)/(1-01) are observed away from this region. It is proposed that the elastic strain field at the grain boundary interacts with the ferro-electric/elastic domain structure, stabilizing (101)/(1-01) rather than (011)/(01-1) type domain walls, which inhibits domain wall motion under applied field and decreases non-linearity. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Protracted Peace processes: Policy (Un)learning and the Cyprus Debacle

The article examines why a comprehensive settlement to resolve the Cyprus problem has yet to be reached despite the existence of a positive incentive structure and the proactive involvement of regional and international organizations, including the European Union and the United Nations. To address this question, evidence from critical turning points in foreign policy decision-making in Turkey, Greece and the two communities in Cyprus is drawn on. The role of hegemonic political discourses is emphasized, and it is argued that the latter have prevented an accurate evaluation of incentives that could have set the stage for a constructive settlement. However, despite the political debacle in the Cypriot negotiations, success stories have emerged, such as the reactivation of the Committee for Missing Persons (CMP), a defunct body for almost 25 years, to become the most successful bi-communal project following Cyprus’s EU accession. Contradictory evidence in the Cypriot peace process is evaluated and policy lessons to be learned from the CMP ‘success story’ are identified.

Group work in elementary science:Towards organisational principles for supporting pupil learning

Group work has been promoted in many countries as a key component of elementary science. However, little guidance is given as to how group work should be organised, and because previous research has seldom been conducted in authentic classrooms, its message is merely indicative. A study is reported, which attempts to address these limitations. Twenty-four classes of 10-12-year-old pupils engaged in programmes of teaching on evaporation and condensation, and force and motion. Both programmes were delivered by classroom teachers, and made extensive use of group work. Pupil understanding progressed from pre-tests prior to the programmes to post-tests afterwards, and results suggest that group work played a critical role. Organisational principles are extrapolated from the findings, which could be readily adopted in classrooms. © 2007 Elsevier Ltd. All rights reserved.

Self-Feedback Motion Control for Cable-Driven Parallel Manipulators

This article proposes a closed-loop control scheme based on joint-angle feedback for cable-driven parallel manipulators (CDPMs), which is able to overcome various difficulties resulting from the flexible nature of the driven cables to achieve higher control accuracy. By introducing a unique structure design that accommodates built-in encoders in passive joints, the seven degrees of freedom (7-DOF) CDPM can obtain joint angle values without external sensing devices, and it is used for feedback control together with a proper closed-loop control algorithm. The control algorithm has been derived from the time differential of the kinematic formulation, which relates the joint angular velocities to the time derivative of cable lengths. In addition, the Lyapunov stability theory and Monte Carlo method have been used to mathematically verify the self-feedback control law that has tolerance for parameter errors. With the aid of co-simulation technique, the self-feedback closed-loop control is applied on a 7-DOF CDPM and it shows higher motion accuracy than the one with an open-loop control. The trajectory tracking experiment on the motion control of the 7-DOF CDPM demonstrated a good performance of the self-feedback control method.

Wave loads on the foundation of a bottom-hinged modular flap structure

Large loads result in expensive foundations which are a substantial proportion of the capital cost of flap-type Wave Energy Converters (WECs). Devices such as Oyster 800, currently deployed at the European Marine Energy Centre (EMEC), comprise a single flap for the full width of the machine. Splitting a flap-type device into smaller vertical flap modules, to make a ‘modular-flap’, might reduce the total foundation loads, whilst still providing acceptable performance in terms of energy conversion.
This paper investigates the foundation loads of an undamped modular-flap device, comparing them to those for a rigid flap of an equivalent width. Physical modelling in a wave tank is used, with loads recorded using a six degree of freedom (DoF) load cell. Both fatigue and extreme loading analysis was conducted. The rotations of the flaps were also recorded, using a motion-tracking system.