Robustness analysis of evolutionary controller tuning using real systems

A genetic algorithm (GA) presents an excellent method for controller parameter tuning. In our work, we evolved the heading as well as the altitude controller for a small lightweight helicopter. We use the real flying robot to evaluate the GA's individuals rather than an artificially consistent simulator. By doing so we avoid the ldquoreality gaprdquo, taking the controller from the simulator to the real world. In this paper we analyze the evolutionary aspects of this technique and discuss the issues that need to be considered for it to perform well and result in robust controllers

Intensity-based image registration using multiple distributed agents

Image registration is the process of geometrically aligning images taken from different sensors, viewpoints or instances in time. It plays a key role in the detection of defects or anomalies for automated visual inspection. A multiagent distributed blackboard system has been developed for intensity-based image registration. The images are divided into segments and allocated to agents on separate processors, allowing parallel computation of a similarity metric that measures the degree of likeness between reference and sensed images after the application of a transform. The need for a dedicated control module is removed by coordination of agents via the blackboard. Tests show that additional agents increase speed, provided the communication capacity of the blackboard is not saturated. The success of the approach in achieving registration, despite significant misalignment of the original images, is demonstrated in the detection of manufacturing defects on screen-printed plastic bottles and printed circuit boards

Web Usage Mining with Evolutionary Extraction of Temporal Fuzzy Association Rules

In Web usage mining, fuzzy association rules that have a temporal property can provide useful knowledge about when associations occur. However, there is a problem with traditional temporal fuzzy association rule mining algorithms. Some rules occur at the intersection of fuzzy sets' boundaries where there is less support (lower membership), so the rules are lost. A genetic algorithm (GA)-based solution is described that uses the flexible nature of the 2-tuple linguistic representation to discover rules that occur at the intersection of fuzzy set boundaries. The GA-based approach is enhanced from previous work by including a graph representation and an improved fitness function. A comparison of the GA-based approach with a traditional approach on real-world Web log data discovered rules that were lost with the traditional approach. The GA-based approach is recommended as complementary to existing algorithms, because it discovers extra rules. (C) 2013 Elsevier B.V. All rights reserved

Supervised Control of a Flying Performing Robot using its Intrinsic Sound

We present the current results of our ongoing research in achieving efficient control of a flying robot for a wide variety of possible applications. A lightweight small indoor helicopter has been equipped with an embedded system and relatively simple sensors to achieve autonomous stable flight. The controllers have been tuned using genetic algorithms to further enhance flight stability. A number of additional sensors would need to be attached to the helicopter to enable it to sense more of its environment such as its current location or the location of obstacles like the walls of the room it is flying in. The lightweight nature of the helicopter very much restricts the amount of sensors that can be attached to it. We propose utilising the intrinsic sound signatures of the helicopter to locate it and to extract features about its current state, using another supervising robot. The analysis of this information is then sent back to the helicopter using an uplink to enable the helicopter to further stabilise its flight and correct its position and flight path without the need for additional sensors

Managing uncertainty in sound based control for an autonomous helicopter

In this paper we present our ongoing research using a multi-purpose, small and low cost autonomous helicopter platform (Flyper ). We are building on previously achieved stable control using evolutionary tuning. We propose a sound based supervised method to localise the indoor helicopter and extract meaningful information to enable the helicopter to further stabilise its flight and correct its flightpath. Due to the high amount of uncertainty in the data, we propose the use of fuzzy logic in the signal processing of the sound signature. We discuss the benefits and difficulties using type-1 and type-2 fuzzy logic in this real-time systems and give an overview of our proposed system

A multi-agent-based novel framework for flexible and tailorable modeling and smart simulation for supply chains

To achieve competitive advantage in today’s global markets, supply chains need to be reconfigured in order to respond to unpredictable changes. Aiming to enable and deliver agile responses and rapid reaction, we propose a multi-agent framework for flexible modeling and simulation of supply chains using reconfigurable production cells. Our novel approach will enable the structural model and the controller model to be considered separately, and enable high quality simulation models to be rapidly built and reconfigured using relevant production cells. To accomplish these capabilities, a four-layered conceptual modeling framework is proposed, which provides an adaptable and tailorable mechanism to support simulation model reconfiguration. In addition, two categories of reconfigurable production cells can be extracted from the bottom layer of the framework to help users to quickly create a conceptual model using functional “building” blocks or templates

Real-time evolution of an embedded controller for an autonomous helicopter

In this paper we evolve the parameters of a proportional, integral, and derivative (PID) controller for an unstable, complex and nonlinear system. The individuals of the applied genetic algorithm (GA) are evaluated on the actual system rather than on a simulation of it, thus avoiding the ldquoreality gaprdquo. This makes implicit a formal model identification for the implementation of a simulator. This also calls for the GA to be approached in an unusual way, where we need to consider new aspects not normally present in the usual situations using an unnaturally consistent simulator for fitness evaluation. Although elitism is used in the GAs, no monotonic increase in fitness is exhibited by the algorithm. Instead, we show that the GApsilas individuals converge towards more robust solutions

A new splitting-based displacement prediction approach for location-based services

In location-based services (LBSs), the service is provided based on the users' locations through location determination and mobility realization. Several location prediction models have been proposed to enhance and increase the relevance of the information retrieved by users of mobile information systems, but none of them studied the relationship between accuracy rate of prediction and the performance of the model in terms of consuming resources and constraints of mobile devices. Most of the current location prediction research is focused on generalized location models, where the geographic extent is divided into regular-shape cells. These models are not suitable for certain LBSs where the objectives are to compute and present on-road services. One such technique is the Prediction Location Model (PLM), which deals with inner cell structure. The PLM technique suffers from memory usage and poor accuracy. The main goal of this paper is to propose a new path prediction technique for Location-Based Services. The new approach is competitive and more efficient compared to PLM regarding measurements such as accuracy rate of location prediction and memory usage

Introduction of misfit dislocations into strained-layer GaAs/In_xGa_1–xAs/GaAs heterostructures by mechanical bending

The stability of strained-layer heterostructure lasers can be assessed by their response to stimuli for the introduction of dislocations. Three-point bending at elevated temperatures has been applied to GaAs/InxGa1−xAs/GaAs heterostructures to apply such a thermomechanical stimulus. In each case, the middle-layer thickness was below the critical thickness predicted by the Matthews–Blakeslee model, so that the pre-test structures were fully strained with no observed misfit dislocations. The tensile stress of 46.4 MPa produced during the tests resulted in the formation of 60° misfit dislocations whose configurations changed according to the alignment of the bending axis. For bending in the [110] orientation, the misfit dislocations formed parallel to each other and to the bending axis. For [100] bending, they formed an orthogonal pattern with each dislocation at 45° to the bending axis. In each case, these misfit dislocations caused relaxation of the strained-layer structures, even though the unloaded structures had been considered thermodynamically stable and the test temperatures were lower than those used during the original fabrication of the structures. These findings challenge existing assumptions of strained-layer stability and have implications for the design of lasers intended to be “buried and forgotten” in optical telecommunications

Accelerating genetic schema processing through local search

peer reviewedAchieving a balance between the exploration and exploitation capabilities of genetic algorithms is a key factor for their success in solving complicated search problems. Incorporating a local search method within a genetic algorithm can enhance the exploitation of local knowledge but it risks decelerating the schema building process. This paper defines some features of a local search method that might improve the balance between exploration and exploitation of genetic algorithms. Based on these features a probabilistic local search method is proposed. The proposed search method has been tested as a secondary method within a staged hybrid genetic algorithm and as a standalone method. The experiments conducted showed that the proposed method can speed up the search without affecting the schema processing of genetic algorithms. The experiments also showed that the proposed algorithm as a standalone algorithm can, in some cases, outperform a pure genetic algorithm