Showing papers on "Autonomous system (mathematics) published in 1995"

A multisteering trailer system: conversion into chained form using dynamic feedback

Abstract: This paper examines the kinematic model of an autonomous mobile robot system consisting of a chain of steerable cars and passive trailers, linked together with rigid bars. The state space and kinematic equations of the system are defined, and it is shown how these kinematic equations may be converted into a multiinput chained form. The advantages of the chained form are that many methods are available for the open-loop steering of such systems as well as for point-stabilization; some of these methods are discussed here. Dynamic state feedback is used to convert the system to this multiinput chained form. It is shown how the dynamic state feedback that is used in this paper corresponds to adding, in front of the steerable cars, a chain of virtual axles which diverges from the original chain of trailers. Two different example systems are also presented, along with simulation results for a parallel-parking maneuver.

An on-line adaptation method in a neural network based control system for AUVs

Abstract: A neural network based control system "Self-Organizing Neural-Net-Controller System: SONCS" has been developed as an adaptive control system for Autonomous Underwater Vehicles (AUVs) In this paper, an on-line adaptation method "Imaginary Training" is proposed to improve the time-consuming adaptation process of the original SONCS The Imaginary Training can be realized by a parallel structure which enables the SONCS to adjust the controller network independently of actual operation of the controlled object The SONCS is divided into two separate parts: the Real-World Part where the controlled object is operated according to the objective, and the Imaginary-World Part where the Imaginary Training is carried out In order to adjust the controller network by the Imaginary Training, it is necessary to introduce a forward model network which can generate simulated state variables without involving actual data A neural network "Identification Network" which has a specific structure to simulate the behavior of dynamical systems is proposed as the forward model network The effectiveness of the Imaginary Training is demonstrated by applying to the heading keeping control of an AUV "Twin-Burger" It is shown that the SONCS adjusts the controller network-through on-line processes in parallel with the actual operation >

Rigorous computational shadowing of orbits of ordinary differential equations

Abstract: The existence of a true orbit near a numerically computed approximate orbit -- shadowing -- of autonomous system of ordinary differential equations is investigated. A general shadowing theorem for finite time, which guarantees the existence of shadowing in ordinary differential equations and provides error bounds for the distance between the true and the approximate orbit in terms of computable quantities, is proved. The practical use and the effectiveness of this theorem is demonstrated in the numerical computations of chaotic orbits of the Lorenz equations.

A Shadowing Theorem for ordinary differential equations

Abstract: A new notion of shadowing of a pseudo orbit, an approximate solution, of an autonomous system of ordinary differential equations by an associated nearby true orbit is introduced. Then a general theorem which guarantees the existence of shadowing of pseudo orbits in compact hyperbolic sets is proved.

Cooperation between the human operator and the multi-agent robotic system: evaluation of agent monitoring methods for the human interface system

Abstract: This paper first discusses the relation between the human operator and the decentralized autonomous robotic system. The operator relates himself to the system loosely in the decentralized autonomous system. The authors position the operator as a problem solver and a monitor of the system. The human operator is regarded as an agent in the decentralized autonomous robotic system. Then strategies of communication between the human operator and agents are discussed. The authors propose explicit and implicit communication strategies to monitor the system, and several monitoring methods to implement them: time-based and event-based monitoring for explicit communication and eavesdropping messages for implicit communication. The authors compare the monitoring methods in order to ascertain how much information the human operator can gather in each method using simulation. Finally, the characteristics of each monitoring method are analyzed.

Intelligent Simulation in Designing Complex Dynamic Control Systems

Abstract: We develop Phase Space Navigator, an autonomous system for control synthesis of nonlinear dynamical systems The Phase Space Navigator automatically designs a controller for a nonlinear system in phase space It generates global control laws by synthesizing the desired phase-space flow “shapes” for the system and intelligently planning and navigating the system along desired control trajectories in phase space It is particularly suitable for synthesizing high-performance control systems that do not lend themselves to traditional design and analysis techniques It can also assist control engineers in exploring much larger design spaces than otherwise possible

Autonomous Navigation of Heavy Construction Equipment

Abstract: A John Deere model 690 excavator, mounted on a Standard Manufacturing Company wheeled undercarriage, has been automated for the purpose of autonomously uncovering and removing unexploded buried ordnance. This paper describes the development effort, with emphasis placed on the autonomous navigation of the excavator system. Accurate navigation is required in order to properly position the excavator system so that it can uncover and remove the target buried munition. Autonomous navigation is accomplished by use of an A* search algorithm for path planning, an inertial navigation system (INS) integrated with a global positioning system (GPS) for vehicle positioning, and proportional control for path-following. Data gathered from eight navigation test runs show that the excavator, on average, can navigate to within 0.67 m of a goal position and to within 0.021 rad of a goal orientation.

Identification and control of a particular class of chaotic systems

Abstract: We show how it is possible to exploit a priori knowledge of the nonlinear dynamics of a system. Given a signal produced by a system, we first identify the parameters of the system and second we code sub-intervals of the signal into initial state-space points of the identified system. As a result of this method a whole waveform is coded as a sequence of points in state- space, a sequence of interval durations and a system of ordinary differential equations. We test these concepts on a challenging example in which the signal to be coded and compressed is produced by a chaotic oscillator.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Chaos in an anharmonic oscillator

Abstract: Using Melnikov's method, the existence of chaotic behaviour in the sense of Smale in a particular time-periodically perturbed planar autonomous system of ordinary differential equations is established. Examples of planar autonomous differential systems with homoclinic orbits are provided, and an application to the dynamics of a one-dimensional anharmonic oscillator is given.

Data and Event Handling for the MARIE Vehicle

Abstract: In autonomous control systems the sensor-actuator control loop plays a dominant role. It is essential to give the system the capability to react to changes in its environment. A flexible autonomous system needs to reconfigure its sensor-actuator control loops depending on its surroundings, the task at hand, and the available sources of information. In the system architecture of the MARIE vehicle there is a clear difference between control and data flow. In this article we describe our general approach to realise the data interfaces between the several sensingand actuation-modules. Information users can dynamically select their sources and monitoring is transparently supported. Also we describe how the modules can be controlled (initialised, parameterised, activated, suspended) from a higher abstraction layer through the so called elementary operation interface.

Automatic autonomous system for correlative control of traffic

Abstract: A system of automatic control for car traffic is proposed based on the similarity with physical thermodynamical systems and providing effective correlations between moving cars in flow. The control force on a car is defined through an “artificial force” function, depending on the distance between the adjacent cars but also possessing a nonconservative velocity dependence. The latter assures existence of stable equilibrium states of the system under control in various traffic situations. A practical realization mode for such correlative control is outlined. Several simple examples of the system action are considered, demonstrating its capacities in establishing a secure and fluid mode of traffic flow.

Further results on the construction of general solutions to some non-linear, second order, non-conservative systems

Abstract: In some of the author's previous work, it was shown that the general solutions to certain autonomous second order systems can be constructed. In this paper, the specific requirement for these systems is shown to be very mild and any second order autonomous system can meet it. Several examples are included. The general solutions to some damped non-linear oscillator equations are given.

Application of a Cooperative Control System to the Collision Avoidance Guidance of AUVs

Abstract: A decentralized control system is proposed for the control architecture of an autonomous underwater vehicle (AUV). The software concept is based on the object-oriented model and its specialization, a “agent oriented model”. Such control system was implemented on a network of transputers. First tests of such control system were related to the collision avoidance guidance for an AUV which follows the sea bed profile. The guidance system combines a pursuit guidance algorithm and a grid map built in real-time, which is based on the information acquired from a sonar system. First tests concerned simulations using a model of the vehicle Pteroa-150. Experiments were also carried out using the carriage system of a model basin adapted to a test bed for underwater robotics. A robotic system was achieved by using an automatic pursuing system aimed originally to experiments with free running ship models, and attaching underwater acoustic sensors to one of the carriages. Thus, automatic guidance in collision avoidance experiments was made possible for investigating the response of the cooperative control system when it faces the input of a real sensory system. Computer simulations and experimental tests have shown the usefulness and feasibility in real-time of the map assisted guidance system.

Enhanced Mark Flow Graph to Control Autonomous Guided Vehicles

Abstract: The aim of this work is the evaluation of the modeling power of Enhanced Mark Flow Graph (E-MFG) when approaching manufacturing plants whose transportation systems are based on autonomous guided vehicles (AGV). We present main concepts regarding E-MFG and its application in the description of the control part as well as the operative part of production systems. Through the information associated with the structural components of E-MFG it is possible to represent complex control strategies involving different routes of AGV systems in the production of a mix of parts in a highly flexible environment.