289,264 research outputs found
An Intelligent Traction Control for Motorcycles
The appearance of anti-lock braking systems (ABS) and traction control systems
(TCS) have been some of the most major developments in vehicle safety. These systems have
been evolving since their origin, always keeping the same objective, by using increasingly
sophisticated algorithms and complex brake and torque control architectures. The aim of this
work is to develop and implement a new control model of a traction control system to be
installed on a motorcycle, regulating the slip in traction and improving dynamic performance of
two-wheeled vehicles. This paper presents a novel traction control algorithm based on the use of
Artificial Neural Networks (ANN) and Fuzzy Logic. An ANN is used to estimate the optimal
slip of the surface the vehicle is moving on. A fuzzy logic control block, which makes use of the
optimal slip provided by the ANN, is developed to control the throttle position. Two control
blocks have been tuned. The first control block has been tuned according to the experience of an
expert operator. The second one has been optimized using Evolutionary Computation (EC).
Simulation shows that the use of EC can improve the fuzzy logic based control algorithm,
obtaining better results than those produced with the control tuned only by experience.Universidad de Málaga. Campus de Excelencia Internacional AndalucĂa Tech
Technical Report: A Receding Horizon Algorithm for Informative Path Planning with Temporal Logic Constraints
This technical report is an extended version of the paper 'A Receding Horizon
Algorithm for Informative Path Planning with Temporal Logic Constraints'
accepted to the 2013 IEEE International Conference on Robotics and Automation
(ICRA). This paper considers the problem of finding the most informative path
for a sensing robot under temporal logic constraints, a richer set of
constraints than have previously been considered in information gathering. An
algorithm for informative path planning is presented that leverages tools from
information theory and formal control synthesis, and is proven to give a path
that satisfies the given temporal logic constraints. The algorithm uses a
receding horizon approach in order to provide a reactive, on-line solution
while mitigating computational complexity. Statistics compiled from multiple
simulation studies indicate that this algorithm performs better than a baseline
exhaustive search approach.Comment: Extended version of paper accepted to 2013 IEEE International
Conference on Robotics and Automation (ICRA
Generalized disjunction decomposition for the evolution of programmable logic array structures
Evolvable hardware refers to a self reconfigurable electronic circuit, where the circuit configuration is under the control of an evolutionary algorithm. Evolvable hardware has shown one of its main deficiencies, when applied to solving real world applications, to be scalability. In the past few years several techniques have been proposed to avoid and/or solve this problem. Generalized disjunction decomposition (GDD) is one of these proposed methods. GDD was successful for the evolution of large combinational logic circuits based on a FPGA structure when used together with bi-directional incremental evolution and with (1+Ă«) evolution strategy. In this paper a modified generalized disjunction decomposition, together with a recently introduced multi-population genetic algorithm, are implemented and tested for its scalability for solving large combinational logic circuits based on Programmable Logic Array (PLA) structures
HYTESS 2: A Hypothetical Turbofan Engine Simplified Simulation with multivariable control and sensor analytical redundancy
A hypothetical turbofan engine simplified simulation with a multivariable control and sensor failure detection, isolation, and accommodation logic (HYTESS II) is presented. The digital program, written in FORTRAN, is self-contained, efficient, realistic and easily used. Simulated engine dynamics were developed from linearized operating point models. However, essential nonlinear effects are retained. The simulation is representative of the hypothetical, low bypass ratio turbofan engine with an advanced control and failure detection logic. Included is a description of the engine dynamics, the control algorithm, and the sensor failure detection logic. Details of the simulation including block diagrams, variable descriptions, common block definitions, subroutine descriptions, and input requirements are given. Example simulation results are also presented
Comparison Between Different Algorithms for Maximum PPT in Photovoltaic Systems and its Implementation on Microcontroller
This paper presents the practical implementation of fuzzy logic control algorithm for maximum power point tracking (MPPT) in photovoltaic (PV) systems. A prototyping PV system is implemented with a boost DC-DC converter using Microchip® PIC18F452 microcontroller to execute the MPPT algorithms. The common algorithms like perturbation and observation (P&O) and incremental conductance (IncCon.) as well as the proposed fuzzy logic control algorithm are implemented and tested under different conditions, and the test results are analyzed and compared. The results show that the proposed fuzzy logic control algorithm can give better performance than perturbation and observation and incremental conductance algorithms. Keywords: Photovoltaic, Maximum power point tracking, Fuzzy logic control, Microcontrollers
The Divide-and-Conquer Subgoal-Ordering Algorithm for Speeding up Logic Inference
It is common to view programs as a combination of logic and control: the
logic part defines what the program must do, the control part -- how to do it.
The Logic Programming paradigm was developed with the intention of separating
the logic from the control. Recently, extensive research has been conducted on
automatic generation of control for logic programs. Only a few of these works
considered the issue of automatic generation of control for improving the
efficiency of logic programs. In this paper we present a novel algorithm for
automatic finding of lowest-cost subgoal orderings. The algorithm works using
the divide-and-conquer strategy. The given set of subgoals is partitioned into
smaller sets, based on co-occurrence of free variables. The subsets are ordered
recursively and merged, yielding a provably optimal order. We experimentally
demonstrate the utility of the algorithm by testing it in several domains, and
discuss the possibilities of its cooperation with other existing methods
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
CAR TRACTION CONTROL SYSTEM
This project explores the potential of implementing fuzzy logic algorithm for traction
control system using VHDL. Previously, the project on car traction control was done
by simulation using fuzzy logic approach. The Fuzzy Logic Toolbox in MATLAB
software is used to create simulation for fuzzy logic system. The challenge of the
project is to design the control system using hardware description language for future
implementation on hardware using FPGA. Fuzzy logic controller provides optimum
control according to the conditions specify. It is useful when the driving condition is
uncontrolled. The core programming language which will be used as the hardware
description language is VHSIC Hardware Description Language (VHDL). VHDL is
used in FPGA - based implementation. The methodology includes designing the
fuzzy logic controller, development of the algorithm and codes programming. After
that, the following phase includes testing and troubleshooting. Lastly, carry out the
documentation. In conclusion, it is possible to develop the algorithm for fuzzy - based
car traction control system using VHDL. The implementation of the control system
using VHDL is viable for future implementation onto FPGA. Thus the performance
of the car traction control would be enhance
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