Automated Model Generation and Simulation 3

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Book reviewModeling,Simulation,and Control of Flexible Manufacturing Systems ±A Petri Net Approach;Meng Chu Zhou;Kurapati Venkatesh;Yushun Fan;World Scienti®c,Singapore,19991.IntroductionA ¯exible manufacturing system (FMS)is an automated,mid-volume,mid-va-riety,central computer-controlled manufacturing system.It can be used to produce a variety of products with virtually no time lost for changeover from one product to the next.FMS is a capital-investment intensive and complex system.In order to get the best economic bene®ts,the design,implementation and operation of FMS should be carefully made.A lot of researches have been done regarding the modeling,simulation,scheduling and control of FMS [1±6].From time to time,Petri net (PN)method has also been used as a tool by di erent researcher in studying the problems regarding the modeling,simulation,scheduling and control of FMS.A lot of papers and books have been published in this area [7±14].``Modeling,Simulation,and Control of Flexible Manufacturing Systems ±A PN Approach''is a new book written by Zhou and Venkatesh which is focused on studying FMS using PN as a systematic method and integrated tool.The book's contents can be classi®ed into four parts.The four parts are introduction part (Chapter 1to Chapter 4),PNs application part (Chapter 5to Chapter 8),new research results part (Chapter 9to Chapter 13),and future development trend part (Chapter 14).In the introduction part,the background,motivation and objectives of the book are described in Chapter 1.The brief history of manufacturing systems and PNs is also presented in Chapter 1.The basic de®nitions and problems in FMS design and implementation are introduced in Chapter 2.The authors divide FMS related problems into two major areas ±managerial and technical.In Chapter 4,basic de®nitions,properties,and analysis techniques of PNs are presented,Chapter 4can be used as the fundamentals of PNs for those who are not familiar with PN method.In Chapter 3,the authors presented their approach to studying FMS related prob-lems,the approach uses PNs as an integrated tool and methodology in FMS design and implementation.In Chapter 3,various applications in modeling,analysis,sim-ulation,performance evaluation,discrete event control,planning and scheduling of FMS using PNs are presented.Through reading the introduction part,the readers can obtain basic concepts and methods about FMS and PNs.The readers can also get a clear picture about the relationshipbetween FMS and PNs.Mechatronics 11(2001)947±9500957-4158/01/$-see front matter Ó2001Elsevier Science Ltd.All rights reserved.PII:S 0957-4158(00)00057-X948Book review/Mechatronics11(2001)947±950The second part of the book is about PNs applications.In this part,various applications of using PNs in solving FMS related problems are introduced.FMS modeling is the basis for simulation,analysis,planning and scheduling.In Chapter5, after introduction of several kinds of PNs,a general modeling method of FMS using PNs is given.The systematic bottom-up and top-down modeling method is pre-sented.The presented method is demonstrated by modeling a real FMS cell in New Jersey Institute of Technology.The application of PNs in FMS performance analysis is introduced in Chapter 6.The stochastic PNs and the time distributions are introduced in this Chapter. The analysis of a¯exible workstation performance using the PN tool called SPNP developed at Duke University is given in Section6.4.In Chapter7,the procedures and steps involved for discrete event simulation using PNs are discussed.The use of various modeling techniques such as queuing network models,state-transition models,high-level PNs,object-oriented models for simulations are brie¯y explained.A software package that is used to simulate PN models is introduced.Several CASE tools for PNs simulations are brie¯y intro-duced.In Chapter8,PNs application in studying the di erent e ects between push and pull paradigms is shown.The presented application method is useful for the selection of suitable management paradigm for manufacturing systems.A manufacturing system is modeled considering both push and pull paradigms in Section8.3which is used as a practical example.The general procedures for performance evaluation of FMS with pull paradigm are given in Section8.4.The third part of the book is mainly the research results of the authors in the area of PNs applications.In Chapter9,an augmented-timed PN is put forward. The proposed method is used to model the manufacturing systems with break-down handling.It is demonstrated using a¯exible assembly system in Section9.3. In Chapter10,a new class of PNs called Real-time PN is proposed.The pro-posed PN method is used to model and control the discrete event control sys-tems.The comparison of the proposed method and ladder logic diagrams is given in Chapter11.Due to the signi®cant advantages of Object-oriented method,it has been used in PNs to de®ne a new kind of PNs.In Chapter12,the authors propose an Object-oriented design methodology for the development of FMS control software.The OMT and PNs are integrated in order to developreusable, modi®able,and extendible control software.The proposed methodology is used in a FMS.The OMT is used to®nd the static relationshipamong di erent objects.The PN models are formulated to study the performance of the FMS.In Chapter12,the scheduling methods of FMS using PNs are introduced.Some examples are presented for automated manufacturing system and semiconductor test facility.In the last Chapter,the future research directions of PNs are pointed out.The contents include CASE tool environment,scheduling of large production system,su-pervisory control,multi-lifecycle engineering and benchmark studies.Book review/Mechatronics11(2001)947±950949 mentsAs a monograph in PNs and its applications in FMS,the book is abundant in contents.Besides the rich knowledge of PNs,the book covers almost every aspects regarding FMS design and analysis,such as modeling,simulation,performance evaluation,planning and scheduling,break down handling,real-time control,con-trol software development,etc.So,the reader can obtain much knowledge in PN, FMS,discrete event system control,system simulation,scheduling,as well as in software development.The book is a very good book in the combinations of PNs theory and prac-tical applications.Throughout the book,the integrated style is demonstrated.It is very well suited for the graduate students and beginners who are interested in using PN methods in studying their speci®c problems.The book is especially suited for the researchers working in the areas of FMS,CIMS,advanced man-ufacturing technologies.The feedback messages from our graduate students show that compared with other books about PNs,this book is more interested and easy to learn.It is easy to get a clear picture about what is PNs method and how it can be used in the FMS design and analysis.So,the book is a very good textbook for the graduate students whose majors are manufacturing systems, industrial engineering,factory automation,enterprise management,and computer applications.Both PNs and FMS are complex and research intensive areas.Due to the deep understanding for PNs,FMS,and the writing skills of the authors,the book has good advantages in describing complex problems and theories in a very easy read and understandable fashion.The easy understanding and abundant contents enable the book to be a good reference book both for the students and researchers. Through reading the book,the readers can also learn the new research results in PNs and its applications in FMS that do not contained in other books.Because the most new results given in the book are the study achievements of the authors,the readers can better know not only the results,but also the background,history,and research methodology of the related areas.This would helpthe researchers who are going to do the study to know the state-of-art of relevant areas,thus the researchers can begin the study in less preparing time and to get new results more earlier.As compared to other books,the organization of the book is very application oriented.The aims are to present new research results in FMS applications using PNs method,the organization of the book is cohesive to the topics.A lot of live examples have reinforced the presented methods.These advantages make the book to be a very good practical guide for the students and beginners to start their re-search in the related areas.The history and reference of related research given in this book provides the reader a good way to better know PNs methods and its applications in FMS.It is especially suited for the Ph.D.candidates who are determined to choose PNs as their thesis topics.950Book review/Mechatronics11(2001)947±9503.ConclusionsDue to the signi®cant importance of PNs and its applications,PNs have become a common background and basic method for the students and researchers to do re-search in modeling,planning and scheduling,performance analysis,discrete event system control,and shop-¯oor control software development.The book under re-view provides us a good approach to learn as well as to begin the research in PNs and its application in manufacturing systems.The integrated and application oriented style of book enables the book to be a very good book both for graduate students and researchers.The easy understanding and step-by-step deeper introduction of the contents makes it to be a good textbook for the graduate students.It is suited to the graduated students whose majors are manufacturing system,industrial engineering, enterprise management,computer application,and automation.References[1]Talavage J,Hannam RG.Flexible manufacturing systems in practice:application,design,andsimulation.New York:Marcel Dekker Inc.;1988.[2]Tetzla UAW.Optimal design of¯exible manufacturing systems.New York:Springer;1990.[3]Jha NK,editor.Handbook of¯exible manufacturing systems.San Diego:Academic Press,1991.[4]Carrie C.Simulation of manufacturing.New York:John Wiley&Sons;1988.[5]Gupta YP,Goyal S.Flexibility of manufacturing systems:concepts and measurements.EuropeanJournal of Operational Research1989;43:119±35.[6]Carter MF.Designing¯exibility into automated manufacturing systems.In:Stecke KE,Suri R,editors.Proceedings of the Second ORSA/TIMS Conference on FMS:Operations Research Models and Applications.New York:Elsevier;1986.p.107±18.[7]David R,Alla H.Petri nets and grafcet.New York:Prentice Hall;1992.[8]Zhou MC,DiCesare F.Petri net synthesis for discrete event control of manufacturing systems.Norwell,MA:Kluwer Academic Publishers;1993.[9]Desrochers AA,Al-Jaar RY.Applications of petri nets in manufacturing systems.New York:IEEEPress;1995.[10]Zhou MC,editor.Petri nets in¯exible and agile automation.Boston:Kluwer Academic Publishers,1995.[11]Lin C.Stochastic petri nets and system performance evaluations.Beijing:Tsinghua University Press;1999.[12]Peterson JL.Petri net theory and the modeling of systems.Englewood Cli s,NJ:Prentice-Hall;1981.[13]Resig W.Petri nets.New York:Springer;1985.[14]Jensen K.Coloured Petri Nets.Berlin:Springer;1992.Yushun FanDepartment of Automation,Tsinghua UniversityBeijing100084,People's Republic of ChinaE-mail address:*****************。

上海交大彭程博士生船舶气电混合动力模式切换动力学建模及鲁棒自适应控制

上海交大彭程博士生船舶气电混合动力模式切换动力学建模及鲁棒自适应控制

上海交大彭程博士生船舶气电混合动力模式切换动力学建模及
鲁棒自适应控制
上海交通大学彭程博士生的研究领域是船舶气电混合动力系统,他的研究内容包括船舶气电混合动力模式切换动力学建模及鲁棒自适应控制。

在船舶气电混合动力系统中,彭程博士生主要研究如何根据不同的工况或环境进行动力模式切换。

船舶的工作环境复杂多变,需要根据实际情况切换不同的动力模式,如传统柴油动力、天然气动力、电力等。

彭程博士生通过建立动力学模型,包括船舶的结构、动力系统、能量转换等方面的模型,来研究不同动力模式的切换过程。

另外,彭程博士生还研究如何设计鲁棒自适应控制算法来实现船舶气电混合动力系统的控制。

由于船舶气电混合动力系统的复杂性,控制算法需要具备鲁棒性和自适应性,能够在各种情况下保证系统的性能和稳定性。

彭程博士生的研究目标是开发出高效、稳定的控制算法,实现船舶气电混合动力系统的优化控制。

总之,彭程博士生的研究主要集中在船舶气电混合动力模式切换动力学建模和鲁棒自适应控制方面,旨在提高船舶动力系统的效率和稳定性。

无人驾驶的英语课件PPT

无人驾驶的英语课件PPT
It can also improve road safety by reducing human errors, which is a leading cause of accidents
Other potential applications include long haul trucking, public transportation, and even self driving taxis or shared mobility services
3D Reconstruction
The creation of a 3D model of the environment from sensor data to provide more accurate representation of the scene
Path planning technology
Application scenarios for autonomous driving
Autonomous driving has the potential to revolutionize transportation, particularly in urban areas where traffic congestion and pollution are major issues
Techniques used to regulate the vehicle's velocity, acceleration, and steel angle to achieve desired performance and safety standards
Risk Assessment
The evaluation of potential hazards and their associated risks to inform decision making processes

自主移动机器人模拟器英文文献

自主移动机器人模拟器英文文献
An autonomous mobile robot must achieve its goal in very complex environments with uncertainties of sensors and actuators. Due to such uncertainties, the control algorithm of robot behavior must have the ability to cope with various possible environmental situations and robot status. To develop such a control algorithm of robot behavior, the algorithm must be tested under numerous conditions of the robot's environment. Such a process requires a large number of experiments using real robots and because of high experimental cost and environmental complexity, a realistic simulator should be developed for verification of behavior algorithms. In this paper, we demonstrate the necessity and usefulness of an autonomous mobile robot simulator as a programming tool which simulates all robot functions and environments including dynamic motion of a robot, control software of robot's subsystems, sensor characteristics and behavior level software. And we point why such a simulator can act as the center of a programming environment for developing robot behavior algorithms. Accordingly, we describe Autonomous Mobile RObot Simulator (AMROS) which is developed as a programming tool for sensor based behavior. AMROS consists of simulation of vehicle controller process, simulation of vehicle motion based on dynamics model, simulation of ultrasonic range sensor, simulation of ROBOL/0 behavior program execution and simulation of indoor environment. To realize AMROS, synchronization method among all parts of the simulation is considered. Synchronization mechanism that a behavior description language ROBOL/0 has, is utilized for this synchronization. Due to the fact that sensory information is the only way to know environmental conditions, a realistic simulation of sensor interaction with robot's environment is necessary. Based on this concept, an ultrasonic range sensor simulator, which simulates propagation process of ultrasonic wave, is developed and described in this paper. AMROS targets the real mobile robot "Yamabico" operating in an indoor environment. The efficiency of the results obtained through simulation are presented by comparing to the results obtained by real experiment. Lastly, we present our experience of implementing behaviors of the mobile robot with some examples that show the high performance of the developed simulator.

基于模型预测的纯电动汽车动力总成热管理策略

基于模型预测的纯电动汽车动力总成热管理策略

基于模型预测的纯电动汽车动力总成热管理策略1. 引言1.1 背景介绍随着全球对环境保护和能源可持续性的日益关注,纯电动汽车作为清洁能源汽车的代表之一,受到了越来越多的关注和推广。

纯电动汽车在使用过程中存在着热管理方面的挑战。

动力总成在工作过程中会产生大量热量,而过高或过低的温度会影响电池性能、电机效率以及车辆整体性能和安全。

如何有效地控制纯电动汽车的动力总成温度,提高能源利用效率,延长车辆寿命成为了当前研究的热点之一。

传统的热管理策略通常是基于经验和规则制定,存在着效率低下、控制精度不高等问题。

而基于模型预测的热管理策略则能够通过建立热力学模型和控制算法,根据实时数据进行预测和优化控制,实现动态调节系统的温度,提高系统的效率和性能。

本研究旨在基于模型预测技术,设计一种高效的纯电动汽车动力总成热管理策略,以提高车辆的能源利用效率,延长动力系统的寿命,推动纯电动汽车技术的进一步发展和应用。

1.2 研究目的研究目的是通过基于模型预测的方法,设计一种有效的纯电动汽车动力总成热管理策略。

具体目的包括:优化电池和电机的工作温度,提高系统效率和性能;延长电池和电机的使用寿命,减少系统能量损耗;提高车辆的安全性和稳定性,优化车辆的动力性能和行驶舒适性;降低能源消耗和排放,促进纯电动汽车的可持续发展。

通过研究动力总成热管理策略,旨在为纯电动汽车的技术进步和市场推广提供有效的支持和指导,推动新能源汽车的普及和发展。

深入探讨热管理系统的设计与优化,从而实现对纯电动汽车动力总成系统的有效控制和管理。

本研究旨在为纯电动汽车的热管理技术提升和创新提供理论支持和实践指导,为新能源汽车行业的发展做出积极贡献。

1.3 研究意义纯电动汽车作为未来绿色交通的重要发展方向,其热管理系统对整车性能和安全性具有至关重要的影响。

而基于模型预测的动力总成热管理策略,可以有效地提高电池系统的利用率,延长电池寿命,提高车辆续航里程,降低能源消耗,减少对环境的影响。

工业机器人刚度的辨识方法与性能分析

工业机器人刚度的辨识方法与性能分析
设计了关节刚度辨识的实验方法。通过在机器人末端施加重物负载,使用激光跟踪 仪测量末端的位置变化,根据操作刚度模型,结合最小二乘法,求解出机器人的关节刚 度。运用 MATLAB/SimMechanics 工具箱,进行了柔性关节机器人的建模和仿真实验; 针对实际中的一台工业机器人,进行了关节刚度的辨识实验,结果表明实验方法可行。
1
华中科技大学硕士学位论文
人的弹性变形主要体现在组成关节的传动部件上。 机器人关节变形的一个直接影响是引起末端的静态变形误差。在机器人的自重和外
部负载的作用下,各关节会发生相应的变形,而这种变形又会累积到机器人的末端。对 串联机器人,这种作用尤为明显。机器人关节变形的另一个影响是引起末端的动态变形 误差,即振荡,从而降低了机器人的动态性能。当机器人高速运行时,这种影响较为显 著。因此,若要提高机器人的位置精度和动态性能,必须减小关节变形的影响。
柔性机器人的研究初期,研究者们主要集中在柔性连杆的研究上。柔性连杆机器人 的建模方法主要分为三种:集中参数法、有限元法和假设模态法。
集中参数法[21,22]包括集中质量法和集中刚度法。集中质量模型将机械臂简化为集中 质量和无质量的弹性连杆,集中刚度模型则将机械臂简化为由弹簧连接的刚性杆。这两 种方法大大简化了计算,可以很方便地写出系统动力学方程。但由于简化过多,这两种 方法都很不完善,有待进一步的研究。
除了对位置精度和动态性能的不良影响之外,目前,弹性变形已在某些场合作为一 项有利因素加以应用。对于刚性机器人,其位置控制已经得到了充分的研究[4],但由于 实际中经常需要机器人与环境接触,而环境的位置往往具有不确定性,因此传统的位置 控制难以满足任务要求。以自动装配为例,当装配机器人与零件的容差大于装配间隙时, 装配将难以顺利完成。在这一场合,要求机器人在与装配零件的接触处受到作用力时, 能发生相应的变形,这种性能被称为顺应。顺应性的实现有两种方式,包括主动顺应和 被动顺应。通过在机器人的控制中采用一定的控制算法,实现机器人末端的操作刚度, 这种方式为主动顺应[5]。由于弹性是机械结构的固有特性,通过机械结构(包括连杆, 关节,末端执行器)的设计,可以使机器人的末端具有一定的操作刚度,这种方式称之 为被动顺应[6]。在主动顺应中,为使其控制更稳定,比如提高抗干扰能力[7]和稳定力反 馈环[8],往往会加入被动顺应[9]。

多模态大模型在汽车领域的应用

多模态大模型在汽车领域的应用

多模态大模型在汽车领域的应用多模态大模型(Multimodal Generative Models)在汽车领域具有广泛的应用。

多模态大模型是一种综合利用多种数据模态(如文本、图像、音频等)进行训练和生成的模型。

在汽车领域,多模态大模型可以用于车辆识别、自动驾驶、智能交通系统等方面。

首先,多模态大模型在车辆识别方面有重要的应用。

车辆识别是指通过分析车辆的特征和属性来进行车辆分类和识别的技术。

传统的车辆识别方法主要基于图像处理技术,但是只使用图像数据可能存在信息不全、难以处理复杂场景等问题。

多模态大模型可以结合图像、文本和音频等多种数据模态,通过综合分析多种数据模态的特征,提高车辆识别的准确性和鲁棒性。

例如,可以通过结合图像和音频数据,提取车辆的外观特征和引擎声音特征,进行车辆的识别和分类。

其次,多模态大模型在自动驾驶方面也具有重要的应用。

自动驾驶技术是指汽车能够在无人驾驶的情况下进行行驶和操作的技术。

为了实现安全可靠的自动驾驶,需要将多种传感器数据(如摄像头、激光雷达、雷达等)进行综合分析和处理。

多模态大模型可以将传感器数据转化为多种数据模态(如图像、文本等),通过综合分析多种数据模态,提取道路、交通标志、行人等信息,从而实现对道路环境的感知和决策。

同时,多模态大模型还可以结合地图数据、车辆状态数据等进行综合分析,提高自动驾驶的精确性和稳定性。

此外,多模态大模型在智能交通系统方面也有重要的应用。

智能交通系统是指利用信息技术和通信技术对交通进行智能化管理和调度的系统。

多模态大模型可以融合多种数据模态(如交通图像、道路状态、交通预测等),利用深度学习和生成模型的方法,实现对交通流量、交通拥堵、交通事故等问题的预测和分析。

通过综合分析多种数据模态,可以实现交通信号控制、路线规划、交通事故预警等智能交通系统的功能。

总之,多模态大模型在汽车领域具有广泛的应用前景。

通过综合分析多种数据模态,可以提高车辆识别的准确性、实现安全可靠的自动驾驶、并实现智能交通系统的功能。

四足机器人运动及稳定控制关键技术综述

四足机器人运动及稳定控制关键技术综述

四足机器人运动及稳定控制关键技术综述目录一、内容概览 (2)1. 四足机器人概述 (3)2. 研究背景与意义 (4)3. 研究现状和发展趋势 (5)二、四足机器人运动原理及结构 (7)1. 四足机器人运动原理 (8)1.1 动力学模型建立 (9)1.2 运动规划与控制策略 (10)2. 四足机器人结构组成 (11)2.1 主体结构 (13)2.2 关节与驱动系统 (14)2.3 感知与控制系统 (17)三、四足机器人运动控制关键技术 (19)1. 运动规划算法研究 (20)1.1 基于模型预测控制的运动规划算法 (21)1.2 基于优化算法的运动规划策略 (22)2. 稳定性控制策略研究 (23)2.1 静态稳定性控制策略 (25)2.2 动态稳定性控制策略 (26)3. 路径规划与轨迹跟踪控制技术研究 (27)3.1 路径规划算法研究 (28)3.2 轨迹跟踪控制策略设计 (29)四、四足机器人稳定控制实现方法 (31)1. 基于传感器反馈的稳定控制方法 (32)1.1 传感器类型与布局设计 (34)1.2 传感器数据采集与处理技术研究 (35)2. 基于优化算法的稳定控制方法应用探讨 (37)一、内容概览四足机器人运动机制:阐述四足机器人的基本运动模式,包括行走、奔跑、跳跃等,以及不同运动模式之间的转换机制。

稳定性分析:探讨四足机器人在运动过程中的稳定性问题,包括静态稳定性和动态稳定性,以及影响稳定性的因素。

运动控制关键技术:详细介绍四足机器人运动控制的关键技术,包括运动规划、轨迹跟踪、力控制等,以及这些技术在实现机器人稳定运动中的应用。

传感器与感知技术:介绍四足机器人运动及稳定控制中涉及的传感器与感知技术,包括惯性测量单元(IMU)、激光雷达、视觉传感器等,以及这些技术在机器人运动控制中的作用。

控制算法与策略:探讨四足机器人运动及稳定控制中常用的控制算法与策略,包括基于模型的控制、智能控制方法等,以及这些算法在实际应用中的效果。

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1 Introduction Solving problems about complex physical systems generally involves the creation and execution of models of the physics needed to reason about the problem. Models are normally constructed by the person studying the system. Despite the considerable time and e ort spent, a handcrafted model is often error-prone. Modifying a handcrafted model to solve similar problems about other physical systems is also dicult, and may take more time than building a new model for the systems. The work of this paper is motivated by two goals. The rst goal is to automate the model formulation and simulation process for complex spatial reasoning tasks. In particular, we focus on an important subclass of spatial reasoning
an example)
Di erent forms of these problems require spatial rea-
soning to formulate equations of motion, in particu-
lar the ability to reason explicitly about vector quan-
physical object
primitive object
composite object
Figure 2: 3 blocks connected by 2 springs. The middle block is pulled directly to the side and released.
duplicated.
Consider a spring with one end attached to a xed
point and the other end attached to a block, as illus-
trated in Figure 1a. This harmonic oscillator is a com-
Abstract Understanding or predicting the behavior of a complex physical system requires the construction and execution of a model of the system. Such a model is often handcrafted by the person studying the system, and the modeling process is not formalized to be reusable by others. We describe a method which uses rst principles to automatically create models and simulators for complex motions, and an implemented system called . Oracle Given a description of a problem involving a physical system, Oracle automatically identi es relevant model fragments, instantiates them for the particular entities and physical phenomena in the problem, composes the instantiated fragments to form a model, and executes the model. Knowledge of physical phenomena is represented with general model fragments which can be shared and reused by many models. Experimental results show that the method is capable of generating correct models of several di erent types of physical systems if enough domain knowledge is available.
solid
fluid
rigid body flexible body water
air
spring-block ship system
sailboat
block hull spring sail
Figure 4: Taxonomy of entities for the examples of the paper. Properties of a class are inherited to its subclasses. For example, properties of rigid body are inherited by block and hull.
solve 11998864];
cannot handle the more complex problems we describe
above because they lack this spatial reasoning ability.
Consider, now, predicting the behavior of another
Kyungsook Han and Andrew Gelsey
kshan@ gelsey@ Department of Computer Science Rutgers University New Brunswick, NJ 08903 U. S. A.
to a corner of a block instead of the center of the face?

(2) What if a block attached to a spring is put in arbi-
trary position and orientation before being released? (3)
physical system, a sailboat (Figure 3), which appears
(a)
(b)
Figure 1: (a) The block on a spring is pulled from its equilibrium position and released. (b) The block is pulled and rotated from its equilibrium position and released.
{ moving objects. The second goal is to make the mod-
eling process as general as possible so that common do-
main theories can be shared and reused instead of being
mon textbook example which is often used in qualitative
physics research. It is well known that the oscillator has
one degree of freedom, i.e., displacement of the block
predicting the behavior is not as simple as before. Is
the motion going to be still oscillatory? More interest-
ing questions include: (1) What if a spring is attached
3This research was partially supported by the Advanced Research Projects Agency (ARPA) and National Aeronautics and Space Administration under NASA grant NAG2-645 and by the National Science Foundation through grant CCR9209793.
from its equilibrium position, and its motion is oscilla-
tory on a straight line. However, if you consider a block
and a spring in more general con guration (Figure 1b),
tities and moving frames of reference. Many qualitative
tphheysliicnseaarpphraoramchoensicbyoscAilIlarteosreaprrcohbelresmwh[Ficohrbcuasn, Kuipers, 1986; Struss, 1988; Weld, 1988; Williams,
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