Pub Date : 2001-11-11DOI: 10.1115/imece2001/dsc-24575
Cheng-Lun Chen, G.T.-C. Chiu
In this paper, a repetitive control based 2 degree-of-freedom (DOF) controller for a SISO motor/gear-train system is proposed. Instead of sequential design, it is shown that the optimal 2 DOF controller for such system can be obtained simultaneously by solving an mixed-sensitivity problem. The simulation results are presented to show the feasibility and effectiveness of the proposed control structure for periodic and non-periodic disturbance reduction for motor/gear-train velocity regulation.
{"title":"Disturbance Rejection Using Two Degree of Freedom Repetitive Control Through Mixed Sensitivity Optimization","authors":"Cheng-Lun Chen, G.T.-C. Chiu","doi":"10.1115/imece2001/dsc-24575","DOIUrl":"https://doi.org/10.1115/imece2001/dsc-24575","url":null,"abstract":"\u0000 In this paper, a repetitive control based 2 degree-of-freedom (DOF) controller for a SISO motor/gear-train system is proposed. Instead of sequential design, it is shown that the optimal 2 DOF controller for such system can be obtained simultaneously by solving an mixed-sensitivity problem. The simulation results are presented to show the feasibility and effectiveness of the proposed control structure for periodic and non-periodic disturbance reduction for motor/gear-train velocity regulation.","PeriodicalId":90691,"journal":{"name":"Proceedings of the ASME Dynamic Systems and Control Conference. ASME Dynamic Systems and Control Conference","volume":"66 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2001-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85050465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2001-11-11DOI: 10.1115/imece2001/dsc-24578
Dong-Jun Lee, M. Tomizuka
In this paper, the use of an accelerometer in precision motion control of linear motors is investigated. The acceleration measurement can provide several advantages. In particular, it can be used with the position measurement for estimation of the position and velocity based on a kinematic model. It can be further utilized for identification of dynamic parameters such as coulomb friction and cogging force as well as for estimation of disturbance. Experimental results verify the effectiveness of the proposed estimation/identification schemes. These schemes are integrated into a two-degree of freedom control system for precision motion control of linear motors. The proposed schemes are evaluated by experiments performed on a linear permanent-magnet motor.
{"title":"State/Parameter/Disturbance Estimation With an Accelerometer in Precision Motion Control of a Linear Motor","authors":"Dong-Jun Lee, M. Tomizuka","doi":"10.1115/imece2001/dsc-24578","DOIUrl":"https://doi.org/10.1115/imece2001/dsc-24578","url":null,"abstract":"\u0000 In this paper, the use of an accelerometer in precision motion control of linear motors is investigated. The acceleration measurement can provide several advantages. In particular, it can be used with the position measurement for estimation of the position and velocity based on a kinematic model. It can be further utilized for identification of dynamic parameters such as coulomb friction and cogging force as well as for estimation of disturbance. Experimental results verify the effectiveness of the proposed estimation/identification schemes. These schemes are integrated into a two-degree of freedom control system for precision motion control of linear motors. The proposed schemes are evaluated by experiments performed on a linear permanent-magnet motor.","PeriodicalId":90691,"journal":{"name":"Proceedings of the ASME Dynamic Systems and Control Conference. ASME Dynamic Systems and Control Conference","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2001-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89276048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2001-11-11DOI: 10.1115/imece2001/dsc-24545
Samuel Y. Chang, Christopher R. Carlson, J. Gerdes
Model reduction based upon the idea of eliminating coordinates with low levels of associated power, energy or activity has been proposed by a number of researchers. None of these results, however, produce the sort of computable bounds on the neglected dynamics that would be useful in the design of controllers with guaranteed robustness properties. This paper outlines an approach to model reduction based upon Lyapunov functions that represent a modified version of the system energy of Lagrangian subsystems. The Lyapunov functions are used to bound the states of subsystems to be removed, enabling these states to be treated as time-varying perturbations in a simplified set of dynamic equations. In contrast to other results in energy-based model reduction, this approach provides bounds on the disturbances caused by the unmodeled dynamics though at the cost of the implementation ease associated with other methods.
{"title":"A Lyapunov Function Approach to Energy Based Model Reduction","authors":"Samuel Y. Chang, Christopher R. Carlson, J. Gerdes","doi":"10.1115/imece2001/dsc-24545","DOIUrl":"https://doi.org/10.1115/imece2001/dsc-24545","url":null,"abstract":"\u0000 Model reduction based upon the idea of eliminating coordinates with low levels of associated power, energy or activity has been proposed by a number of researchers. None of these results, however, produce the sort of computable bounds on the neglected dynamics that would be useful in the design of controllers with guaranteed robustness properties. This paper outlines an approach to model reduction based upon Lyapunov functions that represent a modified version of the system energy of Lagrangian subsystems. The Lyapunov functions are used to bound the states of subsystems to be removed, enabling these states to be treated as time-varying perturbations in a simplified set of dynamic equations. In contrast to other results in energy-based model reduction, this approach provides bounds on the disturbances caused by the unmodeled dynamics though at the cost of the implementation ease associated with other methods.","PeriodicalId":90691,"journal":{"name":"Proceedings of the ASME Dynamic Systems and Control Conference. ASME Dynamic Systems and Control Conference","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2001-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89648375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2001-11-11DOI: 10.1115/imece2001/dsc-24577
B. Yao, Li Xu
A new perspective on dealing with the noise sensitive problem of repetitive control algorithms is given in the paper. It is firstly shown that, in continuous-time domain, what the conventional repetitive learning algorithm does is equivalent to adapting all the values of the periodic uncertainties over one period. Such an endeavor means very high bandwidth of the learning algorithm as an infinite number of parameters need to be adapted, which puts a great demand on microprocessor memory in implementing the algorithms. At the same time, such a formulation also makes the algorithm very sensitive to noise as it treats the values of the periodic uncertainties over the same period totally independent from each other, just like a random noise. Based on this new perspective on the noise sensitive problem of repetitive algorithm, a simple remedy is provided for the recently proposed adaptive robust repetitive control (ARRC) design by recognizing the physical dependence of the values of the periodic uncertainties over the same period and using certain known basis functions to capture these physical dependence. By doing so, only the amplitudes of these known basis functions need to be adapted on-line. The net results are that, not only the number of the parameters to be adapted is reduced drastically, but also the noise sensitive problem of the conventional learning algorithm is overcome. The precision motion control of a linear motor drive system is used as an application example. The comparative experimental results demonstrate that, with the new adaptive robust repetitive control design, not only the noise sensitive problem of repetitive learning is completely eliminated, but also a much improved tracking performance is achieved due to the built-in extrapolation capability of the basis functions used.
{"title":"On the Design of Adaptive Robust Repetitive Controllers","authors":"B. Yao, Li Xu","doi":"10.1115/imece2001/dsc-24577","DOIUrl":"https://doi.org/10.1115/imece2001/dsc-24577","url":null,"abstract":"\u0000 A new perspective on dealing with the noise sensitive problem of repetitive control algorithms is given in the paper. It is firstly shown that, in continuous-time domain, what the conventional repetitive learning algorithm does is equivalent to adapting all the values of the periodic uncertainties over one period. Such an endeavor means very high bandwidth of the learning algorithm as an infinite number of parameters need to be adapted, which puts a great demand on microprocessor memory in implementing the algorithms. At the same time, such a formulation also makes the algorithm very sensitive to noise as it treats the values of the periodic uncertainties over the same period totally independent from each other, just like a random noise. Based on this new perspective on the noise sensitive problem of repetitive algorithm, a simple remedy is provided for the recently proposed adaptive robust repetitive control (ARRC) design by recognizing the physical dependence of the values of the periodic uncertainties over the same period and using certain known basis functions to capture these physical dependence. By doing so, only the amplitudes of these known basis functions need to be adapted on-line. The net results are that, not only the number of the parameters to be adapted is reduced drastically, but also the noise sensitive problem of the conventional learning algorithm is overcome. The precision motion control of a linear motor drive system is used as an application example. The comparative experimental results demonstrate that, with the new adaptive robust repetitive control design, not only the noise sensitive problem of repetitive learning is completely eliminated, but also a much improved tracking performance is achieved due to the built-in extrapolation capability of the basis functions used.","PeriodicalId":90691,"journal":{"name":"Proceedings of the ASME Dynamic Systems and Control Conference. ASME Dynamic Systems and Control Conference","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2001-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91376807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2001-11-11DOI: 10.1115/imece2001/dsc-24544
R. Rosenberg, E. Goodman, Kisung Seo
Mechatronic system design differs from design of single-domain systems, such as electronic circuits, mechanisms, and fluid power systems, in part because of the need to integrate the several distinct domain characteristics in predicting system behavior. The goal of our work is to develop an automated procedure that can explore mechatronic design space in a topologically open-ended manner, yet still find appropriate configurations efficiently enough to be useful. Our approach combines bond graphs for model representation with genetic programming for generating suitable design candidates as a means of exploring the design space. Bond graphs allow us to capture the common energy behavior underlying the several physical domains of mechatronic systems in a uniform notation. Genetic programming is an effective way to generate design candidates in an open-ended, but statistically structured, manner. Our initial goal is to identify the key issues in merging the bond graph modeling tool with genetic programming for searching. The first design problem we chose is that of finding a model that has a specified set of eigenvalues. The problem can be studied using a restricted set of bond graph elements to represent suitable topologies. We present the initial results of our studies and identify key issues in advancing the approach toward becoming an effective and efficient open-ended design tool for mechatronic systems.
{"title":"Some Key Issues in Using Bond Graphs and Genetic Programming for Mechatronic System Design","authors":"R. Rosenberg, E. Goodman, Kisung Seo","doi":"10.1115/imece2001/dsc-24544","DOIUrl":"https://doi.org/10.1115/imece2001/dsc-24544","url":null,"abstract":"\u0000 Mechatronic system design differs from design of single-domain systems, such as electronic circuits, mechanisms, and fluid power systems, in part because of the need to integrate the several distinct domain characteristics in predicting system behavior. The goal of our work is to develop an automated procedure that can explore mechatronic design space in a topologically open-ended manner, yet still find appropriate configurations efficiently enough to be useful.\u0000 Our approach combines bond graphs for model representation with genetic programming for generating suitable design candidates as a means of exploring the design space. Bond graphs allow us to capture the common energy behavior underlying the several physical domains of mechatronic systems in a uniform notation. Genetic programming is an effective way to generate design candidates in an open-ended, but statistically structured, manner.\u0000 Our initial goal is to identify the key issues in merging the bond graph modeling tool with genetic programming for searching. The first design problem we chose is that of finding a model that has a specified set of eigenvalues. The problem can be studied using a restricted set of bond graph elements to represent suitable topologies. We present the initial results of our studies and identify key issues in advancing the approach toward becoming an effective and efficient open-ended design tool for mechatronic systems.","PeriodicalId":90691,"journal":{"name":"Proceedings of the ASME Dynamic Systems and Control Conference. ASME Dynamic Systems and Control Conference","volume":"84 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2001-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90307247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2001-11-11DOI: 10.1115/imece2001/dsc-24581
F. Bu, B. Yao
Compared to conventional robot manipulators driven by electrical motors, hydraulic robot arms have richer nonlinear dynamics and stronger couplings among various joints (or hydraulic cylinders). This paper focuses on the physical model based coordinated adaptive robust control (ARC) strategies that explicitly take into account the strong coupling among various hydraulic cylinders (or joints). In our recent studies, two such methods were proposed to avoid the need of acceleration feedback in doing ARC backstepping designs. The first method uses an observer to recover the state needed for the ARC backstepping design. The second method utilizes the property that the adjoint matrix and the determinant of the inertial matrix can be linearly parametrized by certain suitably selected parameters and employ certain over-parametrizing techniques. Theoretically, both the resulting ARC controllers guarantee a prescribed output tracking transient performance and final tracking accuracy while achieving asymptotic output tracking in the presence of parametric uncertainties only. This paper focuses on the comparative studies of these two methods under various practical constraints. Extensive simulation results which are based on a three degree-of-freedom (DOF) hydraulic robot arm are presented to illustrate the advantages and drawbacks of each method.
{"title":"Nonlinear Model Based Coordinated Adaptive Robust Control of Electro-Hydraulic Robotic Manipulators: Methods and Comparative Studies","authors":"F. Bu, B. Yao","doi":"10.1115/imece2001/dsc-24581","DOIUrl":"https://doi.org/10.1115/imece2001/dsc-24581","url":null,"abstract":"\u0000 Compared to conventional robot manipulators driven by electrical motors, hydraulic robot arms have richer nonlinear dynamics and stronger couplings among various joints (or hydraulic cylinders). This paper focuses on the physical model based coordinated adaptive robust control (ARC) strategies that explicitly take into account the strong coupling among various hydraulic cylinders (or joints). In our recent studies, two such methods were proposed to avoid the need of acceleration feedback in doing ARC backstepping designs. The first method uses an observer to recover the state needed for the ARC backstepping design. The second method utilizes the property that the adjoint matrix and the determinant of the inertial matrix can be linearly parametrized by certain suitably selected parameters and employ certain over-parametrizing techniques. Theoretically, both the resulting ARC controllers guarantee a prescribed output tracking transient performance and final tracking accuracy while achieving asymptotic output tracking in the presence of parametric uncertainties only. This paper focuses on the comparative studies of these two methods under various practical constraints. Extensive simulation results which are based on a three degree-of-freedom (DOF) hydraulic robot arm are presented to illustrate the advantages and drawbacks of each method.","PeriodicalId":90691,"journal":{"name":"Proceedings of the ASME Dynamic Systems and Control Conference. ASME Dynamic Systems and Control Conference","volume":"55 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2001-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90744840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2001-11-11DOI: 10.1115/imece2001/dsc-24519
G. Paganelli, Y. Guezennec, HanSung Kim, A. Brahma
On-line Sate-of-Charge (SOC) estimation in pure electric or hybrid-electric (HEV) vehicles is a challenging problem, due to the very dynamic nature of the current/voltage history under actual driving conditions. However, on-line, reliable SOC estimation is critical in these applications, particularly in charge-sustaining HEV, where the battery capacity is relatively small and where the energy management strategy needs an accurate SOC estimation in order to optimize the power split between the ICE and EM. The research described in this paper focuses on two aspects of the same problem. The first aspect is the development, calibration and validation of a dynamic battery model which represents the essential dynamic behavior of the battery pack HEV application. The second part of this paper is the development, implementation and validation of an appropriate in-vehicle SOC estimator for use with our supervisory HEV controller. While the implementation approaches for theses two facets of the same problem are significantly different due to the real-time computational requirements, they represent the same battery dynamics. This algorithm has been applied to a real charge-sustaining HEV vehicle and the experimental results are presented.
{"title":"Battery Dynamic Modeling and Real-Time State-of-Charge Estimation in Hybrid Electric Vehicle Application","authors":"G. Paganelli, Y. Guezennec, HanSung Kim, A. Brahma","doi":"10.1115/imece2001/dsc-24519","DOIUrl":"https://doi.org/10.1115/imece2001/dsc-24519","url":null,"abstract":"\u0000 On-line Sate-of-Charge (SOC) estimation in pure electric or hybrid-electric (HEV) vehicles is a challenging problem, due to the very dynamic nature of the current/voltage history under actual driving conditions. However, on-line, reliable SOC estimation is critical in these applications, particularly in charge-sustaining HEV, where the battery capacity is relatively small and where the energy management strategy needs an accurate SOC estimation in order to optimize the power split between the ICE and EM. The research described in this paper focuses on two aspects of the same problem. The first aspect is the development, calibration and validation of a dynamic battery model which represents the essential dynamic behavior of the battery pack HEV application. The second part of this paper is the development, implementation and validation of an appropriate in-vehicle SOC estimator for use with our supervisory HEV controller. While the implementation approaches for theses two facets of the same problem are significantly different due to the real-time computational requirements, they represent the same battery dynamics. This algorithm has been applied to a real charge-sustaining HEV vehicle and the experimental results are presented.","PeriodicalId":90691,"journal":{"name":"Proceedings of the ASME Dynamic Systems and Control Conference. ASME Dynamic Systems and Control Conference","volume":"50 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2001-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85726445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, a methodology is proposed for determination of optimal actuator and sensor locations for the control of combustion instabilities. The proposed approach relies on certain quantitative measures of degree of controllability and observability based on the controllability and observability grammians. These criteria are arrived at by considering the energies of system’s inputs and outputs. The optimality criteria for sensor and actuator locations provide a balance between the importance of the lower order and the higher order modes. It is assumed that the control input is provided by a finite number of point actuators, and the instantaneous conditions in the chamber are monitored, in general, by multiple sensors.
{"title":"Optimal Actuator/Sensor Placement for Control of Combustion Instabilities","authors":"Nidal Al-Masoud, T. Singh","doi":"10.2514/2.6092","DOIUrl":"https://doi.org/10.2514/2.6092","url":null,"abstract":"\u0000 In this paper, a methodology is proposed for determination of optimal actuator and sensor locations for the control of combustion instabilities. The proposed approach relies on certain quantitative measures of degree of controllability and observability based on the controllability and observability grammians. These criteria are arrived at by considering the energies of system’s inputs and outputs. The optimality criteria for sensor and actuator locations provide a balance between the importance of the lower order and the higher order modes. It is assumed that the control input is provided by a finite number of point actuators, and the instantaneous conditions in the chamber are monitored, in general, by multiple sensors.","PeriodicalId":90691,"journal":{"name":"Proceedings of the ASME Dynamic Systems and Control Conference. ASME Dynamic Systems and Control Conference","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2001-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85928856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Driver steering models have been extensively studied. However, driver model uncertainty has received relatively little attention. For active safety systems that function while the driver is still in the control loop, such uncertainty can affect overall system performance significantly. In this paper, an approach to obtain both the driver model and its uncertainty from driving simulator data is presented. The structured uncertainty is used to represent the driver’s time-varying behavior, and the unstructured uncertainty is used to account for unmodeled dynamics. The uncertainty models can be used to represent both the uncertainty within one driver and the uncertainty across multiple drivers. The results show that the unstructured uncertainty is significant, probably due to randomness in driver behavior. The structured uncertainty suggests that an estimation and adaptation scheme might be applicable for the design of controllers for active safety systems.
{"title":"Identification of a Driver Steering Model, and Model Uncertainty, From Driving Simulator Data","authors":"Liang-kuang Chen, A. Galip Ulsoy","doi":"10.1115/1.1409554","DOIUrl":"https://doi.org/10.1115/1.1409554","url":null,"abstract":"\u0000 Driver steering models have been extensively studied. However, driver model uncertainty has received relatively little attention. For active safety systems that function while the driver is still in the control loop, such uncertainty can affect overall system performance significantly. In this paper, an approach to obtain both the driver model and its uncertainty from driving simulator data is presented. The structured uncertainty is used to represent the driver’s time-varying behavior, and the unstructured uncertainty is used to account for unmodeled dynamics. The uncertainty models can be used to represent both the uncertainty within one driver and the uncertainty across multiple drivers. The results show that the unstructured uncertainty is significant, probably due to randomness in driver behavior. The structured uncertainty suggests that an estimation and adaptation scheme might be applicable for the design of controllers for active safety systems.","PeriodicalId":90691,"journal":{"name":"Proceedings of the ASME Dynamic Systems and Control Conference. ASME Dynamic Systems and Control Conference","volume":"57 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2001-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84854578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2001-11-11DOI: 10.1115/imece2001/dsc-24523
Y. Kojima, H. Nishigaki, H. Sugiura, S. Nishiwaki, N. Kikuchi
In current automotive development, innovations to reduce development time and to use a virtual prototype have been numerous and progressive. Computer Aided Engineering (CAE) has played an important role in these innovations. CAE numerically estimates the performance of automobiles and proposes alternative ideas that lead to higher performance without building physical prototypes. However, current CAE can not usually be used at the initial design phase due to their difficult, and complex functions and characteristics. In this paper, we propose a new type of CAE, First Order Analysis (FOA). The basic ideas include: (1) graphic interfaces using Microsoft /Excel to achieve a product-oriented analysis, (2) use of mechanics of materials to provide useful information regarding structural mechanisms, and (3) a topology optimization method using function oriented elements. Also, some prototype software is presented to confirm the applicability of method presented here to the automotive designs.
{"title":"First Order Analysis for Automotive Designs","authors":"Y. Kojima, H. Nishigaki, H. Sugiura, S. Nishiwaki, N. Kikuchi","doi":"10.1115/imece2001/dsc-24523","DOIUrl":"https://doi.org/10.1115/imece2001/dsc-24523","url":null,"abstract":"\u0000 In current automotive development, innovations to reduce development time and to use a virtual prototype have been numerous and progressive. Computer Aided Engineering (CAE) has played an important role in these innovations. CAE numerically estimates the performance of automobiles and proposes alternative ideas that lead to higher performance without building physical prototypes. However, current CAE can not usually be used at the initial design phase due to their difficult, and complex functions and characteristics. In this paper, we propose a new type of CAE, First Order Analysis (FOA). The basic ideas include: (1) graphic interfaces using Microsoft /Excel to achieve a product-oriented analysis, (2) use of mechanics of materials to provide useful information regarding structural mechanisms, and (3) a topology optimization method using function oriented elements. Also, some prototype software is presented to confirm the applicability of method presented here to the automotive designs.","PeriodicalId":90691,"journal":{"name":"Proceedings of the ASME Dynamic Systems and Control Conference. ASME Dynamic Systems and Control Conference","volume":"37 3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2001-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85003984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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