13,562 research outputs found
Assembly and Disassembly Planning by using Fuzzy Logic & Genetic Algorithms
The authors propose the implementation of hybrid Fuzzy Logic-Genetic
Algorithm (FL-GA) methodology to plan the automatic assembly and disassembly
sequence of products. The GA-Fuzzy Logic approach is implemented onto two
levels. The first level of hybridization consists of the development of a Fuzzy
controller for the parameters of an assembly or disassembly planner based on
GAs. This controller acts on mutation probability and crossover rate in order
to adapt their values dynamically while the algorithm runs. The second level
consists of the identification of theoptimal assembly or disassembly sequence
by a Fuzzy function, in order to obtain a closer control of the technological
knowledge of the assembly/disassembly process. Two case studies were analyzed
in order to test the efficiency of the Fuzzy-GA methodologies
Evolutionary Networks for Multi-Behavioural Robot Control : A thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Computer Science Massey University, Albany, New Zealand
Artificial Intelligence can be applied to a wide variety of real world problems, with
varying levels of complexity; nonetheless, real world problems often demand for
capabilities that are difficult, if not impossible to achieve using a single Artificial
Intelligence algorithm. This challenge gave rise to the development of hybrid systems
that put together a combination of complementary algorithms. Hybrid approaches
come at a cost however, as they introduce additional complications for the developer,
such as how the algorithms should interact and when the independent algorithms
should be executed. This research introduces a new algorithm called Cascading
Genetic Network Programming (CGNP), which contains significant changes to the
original Genetic Network Programming. This new algorithm has the facility to
include any Artificial Intelligence algorithm into its directed graph network, as either
a judgement or processing node. CGNP introduces a novel ability for a scalable
multiple layer network, of independent instances of the CGNP algorithm itself. This
facilitates problem subdivision, independent optimisation of these underlying layers
and the ability to develop varying levels of complexity, from individual motor control
to high level dynamic role allocation systems. Mechanisms are incorporated to
prevent the child networks from executing beyond their requirement, allowing the
parent to maintain control. The ability to optimise any data within each node
is added, allowing for general purpose node development and therefore allowing
node reuse in a wide variety of applications without modification. The abilities
of the Cascaded Genetic Network Programming algorithm are demonstrated and
proved through the development of a multi-behavioural robot soccer goal keeper, as
a testbed where an individual Artificial Intelligence system may not be sufficient.
The overall role is subdivided into three components and individually optimised
which allow the robot to pursue a target object or location, rotate towards a target
and provide basic functionality for defending a goal. These three components are
then used in a higher level network as independent nodes, to solve the overall multi-
behavioural goal keeper. Experiments show that the resulting controller defends the
goal with a success rate of 91%, after 12 hours training using a population of 400
and 60 generations
Self-tuning run-time reconfigurable PID controller
Digital PID control algorithm is one of the most commonly used algorithms in the control systems area. This algorithm is very well known, it is simple, easily implementable in the computer control systems and most of all its operation is very predictable. Thus PID control has got well known impact on the control system behavior. However, in its simple form the controller have no reconfiguration support. In a case of the controlled system substantial changes (or the whole control environment, in the wider aspect, for example if the disturbances characteristics would change) it is not possible to make the PID controller robust enough. In this paper a new structure of digital PID controller is proposed, where the policy-based computing is used to equip the controller with the ability to adjust it's behavior according to the environmental changes. Application to the electro-oil evaporator which is a part of distillation installation is used to show the new controller structure in operation
- …