The robustness of a bank-to-turn missile autopilot to uncertain aerodynamic parameters is determined using six robustness tests. The six robustness tests are: 1) small gain theorem; 2) structured singular value; 3) stability hypersphere - polynomial; 4) stability hypersphere - Lyapunov; 5) Kharitonov's theorem; and 6) multiloop stability margin. Exact parameter variation tolerances were determined by a Monte Carlo eigen analysis and are compared with the theoretical predictions.
{"title":"A Comparison of Six Robustness Tests Evaluating Missile Autopilot Robustness to Uncertain Aerodynamics","authors":"K. Wise","doi":"10.2514/3.20918","DOIUrl":"https://doi.org/10.2514/3.20918","url":null,"abstract":"The robustness of a bank-to-turn missile autopilot to uncertain aerodynamic parameters is determined using six robustness tests. The six robustness tests are: 1) small gain theorem; 2) structured singular value; 3) stability hypersphere - polynomial; 4) stability hypersphere - Lyapunov; 5) Kharitonov's theorem; and 6) multiloop stability margin. Exact parameter variation tolerances were determined by a Monte Carlo eigen analysis and are compared with the theoretical predictions.","PeriodicalId":307181,"journal":{"name":"1990 American Control Conference","volume":"54 Suppl 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116786694","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 : 1990-05-23DOI: 10.23919/ACC.1990.4790923
K. Srinivasan, F. Shaw
The absolute and relative stability of continuous-time SISO repetitive control systems is examined here using a function of frequency termed the regeneration spectrum. The regeneration spectrum is easily computed and is related to important of the characteristic root distribution of such systems, for large values of the time delay. The regeneration spectrum is combined with other frequency domain measures of control system performance such as the sensitivity and complementary sensitivity functions to obtain improved insight into the trade-offs in repetitive control system design. The result is a more rational approach to repetitive control system design and is illustrated by an example.
{"title":"Analysis and Design of Repetitive Control Systems using the Regeneration Spectrum","authors":"K. Srinivasan, F. Shaw","doi":"10.23919/ACC.1990.4790923","DOIUrl":"https://doi.org/10.23919/ACC.1990.4790923","url":null,"abstract":"The absolute and relative stability of continuous-time SISO repetitive control systems is examined here using a function of frequency termed the regeneration spectrum. The regeneration spectrum is easily computed and is related to important of the characteristic root distribution of such systems, for large values of the time delay. The regeneration spectrum is combined with other frequency domain measures of control system performance such as the sensitivity and complementary sensitivity functions to obtain improved insight into the trade-offs in repetitive control system design. The result is a more rational approach to repetitive control system design and is illustrated by an example.","PeriodicalId":307181,"journal":{"name":"1990 American Control Conference","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115132360","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 : 1990-05-23DOI: 10.1109/ACC.1990.4174181
Jean Saint Donat, N. Bhat, T. McAvoy
Neural networks hold great promise for application in the general area of process control. This paper focuses on using a backpropagation network in an optimization based model predictive control scheme. Since analytical expressions for the gradient and Hessian of the neural net model can be derived and these expressions can be calculated in paralle, extremely fast computation times are possible. The control approach is illustrated on a pH CSTR example.
{"title":"Optimizing Neural Net based Predictive Control","authors":"Jean Saint Donat, N. Bhat, T. McAvoy","doi":"10.1109/ACC.1990.4174181","DOIUrl":"https://doi.org/10.1109/ACC.1990.4174181","url":null,"abstract":"Neural networks hold great promise for application in the general area of process control. This paper focuses on using a backpropagation network in an optimization based model predictive control scheme. Since analytical expressions for the gradient and Hessian of the neural net model can be derived and these expressions can be calculated in paralle, extremely fast computation times are possible. The control approach is illustrated on a pH CSTR example.","PeriodicalId":307181,"journal":{"name":"1990 American Control Conference","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116948435","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 : 1990-05-23DOI: 10.1109/ACC.1990.4173761
H. Hjalmarsson, L. Ljung
In System Identification, traditionally, the uncertainty estimate provided with the model is based on the assumption that the model structure used is capable of achieving a correct system description. This estimate is however not correct unless the parameter estimate is close to a "true" model parameter, that yields white noise residuals. The correct expression is known but more complex. The main difficulty, though, is that it is not easily estimated. We suggest a simple and explicit method for estimating the model uncertainty, applicable also to severe under-modelling. The method is illustrated by an example.
{"title":"How to Estimate Model Uncertainty in the Case of Under-Modelling","authors":"H. Hjalmarsson, L. Ljung","doi":"10.1109/ACC.1990.4173761","DOIUrl":"https://doi.org/10.1109/ACC.1990.4173761","url":null,"abstract":"In System Identification, traditionally, the uncertainty estimate provided with the model is based on the assumption that the model structure used is capable of achieving a correct system description. This estimate is however not correct unless the parameter estimate is close to a \"true\" model parameter, that yields white noise residuals. The correct expression is known but more complex. The main difficulty, though, is that it is not easily estimated. We suggest a simple and explicit method for estimating the model uncertainty, applicable also to severe under-modelling. The method is illustrated by an example.","PeriodicalId":307181,"journal":{"name":"1990 American Control Conference","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127121486","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 : 1990-05-23DOI: 10.23919/ACC.1990.4791297
Kent H. Rasmussen, C. S. Nielsen, S. Jørgensen
A distillation plant equipped with a heat pump separates a mixture of isopropanol and methanol. The mixture contains some water as impurity. The model development aims at dual composition control design, where top and bottom compositions should follow the setpoints, and disturbances should be rejected. Disturbances may occur in feed low rate and feed composition. Identification is performed using multivariable linear discrete time model structure development tools: a process knowledge based and a black box approach. In the process knowledge based approach, the model structure is developed from qualitative process knowledge which presently may require modification to guarantee identifiability. The black box approach is based on pseudocanonical MFD model representation, where the model stracture is determined by a set of structure indices. The identifications are performed on experimental data obtained in closed loop operation of the distillation plant. In the present work, the two approaches are compared in terms of how well the model fits, and predicts the data, the conditioning of the model parameter estimation, and convenience of usage.
{"title":"Identification of Distillation Process Dynamics Comparing Process Knowledge and Black Box Based Approaches","authors":"Kent H. Rasmussen, C. S. Nielsen, S. Jørgensen","doi":"10.23919/ACC.1990.4791297","DOIUrl":"https://doi.org/10.23919/ACC.1990.4791297","url":null,"abstract":"A distillation plant equipped with a heat pump separates a mixture of isopropanol and methanol. The mixture contains some water as impurity. The model development aims at dual composition control design, where top and bottom compositions should follow the setpoints, and disturbances should be rejected. Disturbances may occur in feed low rate and feed composition. Identification is performed using multivariable linear discrete time model structure development tools: a process knowledge based and a black box approach. In the process knowledge based approach, the model structure is developed from qualitative process knowledge which presently may require modification to guarantee identifiability. The black box approach is based on pseudocanonical MFD model representation, where the model stracture is determined by a set of structure indices. The identifications are performed on experimental data obtained in closed loop operation of the distillation plant. In the present work, the two approaches are compared in terms of how well the model fits, and predicts the data, the conditioning of the model parameter estimation, and convenience of usage.","PeriodicalId":307181,"journal":{"name":"1990 American Control Conference","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124947036","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 : 1990-05-23DOI: 10.1109/ACC.1990.4174123
Chun-Yao Lien, Tsewei Wang
This paper presents the procedures and results of Using the input-output linearization technique in the design of a controller for a generic nonlinear continuous bioreactor. Of special interest is the existence of singular points which renders direct application of the input-output linearization theory infeasible. In this paper, we present a modified scheme which allows us to approximately extend the input-output linearization technique across the singular points. The feasibility and effectiveness of the proposed method are demonstrated through computer simulation. This modified method provides a more intuitive insight into the nonlinear system control.
{"title":"Application of Feedback Linearization to Bioreactor Control","authors":"Chun-Yao Lien, Tsewei Wang","doi":"10.1109/ACC.1990.4174123","DOIUrl":"https://doi.org/10.1109/ACC.1990.4174123","url":null,"abstract":"This paper presents the procedures and results of Using the input-output linearization technique in the design of a controller for a generic nonlinear continuous bioreactor. Of special interest is the existence of singular points which renders direct application of the input-output linearization theory infeasible. In this paper, we present a modified scheme which allows us to approximately extend the input-output linearization technique across the singular points. The feasibility and effectiveness of the proposed method are demonstrated through computer simulation. This modified method provides a more intuitive insight into the nonlinear system control.","PeriodicalId":307181,"journal":{"name":"1990 American Control Conference","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125802355","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 : 1990-05-23DOI: 10.23919/ACC.1990.4791162
W. Bennett, O. Akhrif, T. Dwyer
In this paper we describe results on the robust implementation of decoupling control for multibody systems with flexible interactions. Requirements for decoupling control arise in input-output linearization of certain principal system outputs with respect to available controls. In many applications it is desired to decouple multibody dynamic interactions from critical system outputs using available controls. For decoupling control implementation to be robust it should be insensitive to model perturbations Here we consider parasitic dynamics arising from flexible interactions and consider the role of reduced order modeling and the implementation of Partial (input-output) Linearizing Feedback control. We highlight the importance of model reduction based on time scaling of the decoupled or zero dynamics.
{"title":"Robust Nonlinear Control of Flexible Space Structures","authors":"W. Bennett, O. Akhrif, T. Dwyer","doi":"10.23919/ACC.1990.4791162","DOIUrl":"https://doi.org/10.23919/ACC.1990.4791162","url":null,"abstract":"In this paper we describe results on the robust implementation of decoupling control for multibody systems with flexible interactions. Requirements for decoupling control arise in input-output linearization of certain principal system outputs with respect to available controls. In many applications it is desired to decouple multibody dynamic interactions from critical system outputs using available controls. For decoupling control implementation to be robust it should be insensitive to model perturbations Here we consider parasitic dynamics arising from flexible interactions and consider the role of reduced order modeling and the implementation of Partial (input-output) Linearizing Feedback control. We highlight the importance of model reduction based on time scaling of the decoupled or zero dynamics.","PeriodicalId":307181,"journal":{"name":"1990 American Control Conference","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125904355","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 : 1990-05-23DOI: 10.1109/ACC.1990.4174195
H. Chapellat, M. Dahleh, S. Bhattacharyya
In this paper we present a complete set of results concerning the robust stability analysis of single input single output Interval Plants in continuous time. Robust stability is considered under bounded real perturbations, non linear, sector-bounded perturbations, and unstructured (H¿) feedback perturbations. In each case, a solution to the problem is given based on the generalization of Kharitonov's theorem obtained in [1] and called the Box Theorem. The Box Theorem gives necessary and sufficient conditions for stabilization of an interval plant. This theorem introduced the so-called Kharitonov Segments associated with an interval plant, and the paper shows that these segments play a fundamental role in the robust stability analysis of such systems. Next we analyse the absolute stability of a closed loop system containing an interval plant in the forward path. The resulting theorem gives conditions for robust stability under nonlinear perturbations. This theorem is based on a result concerning the strict positive realness of families of interval rational functions. Finally, robust stability under unstructured (H¿ type) perturbations is considered and we deduce the necessary and sufficient conditions for robust stabilization in the presence of perturbations of this type. This result is again a generalization of a theorem on the H¿ norm of interval rational functions.
{"title":"Robust Stability of Interval Plants: A Review","authors":"H. Chapellat, M. Dahleh, S. Bhattacharyya","doi":"10.1109/ACC.1990.4174195","DOIUrl":"https://doi.org/10.1109/ACC.1990.4174195","url":null,"abstract":"In this paper we present a complete set of results concerning the robust stability analysis of single input single output Interval Plants in continuous time. Robust stability is considered under bounded real perturbations, non linear, sector-bounded perturbations, and unstructured (H¿) feedback perturbations. In each case, a solution to the problem is given based on the generalization of Kharitonov's theorem obtained in [1] and called the Box Theorem. The Box Theorem gives necessary and sufficient conditions for stabilization of an interval plant. This theorem introduced the so-called Kharitonov Segments associated with an interval plant, and the paper shows that these segments play a fundamental role in the robust stability analysis of such systems. Next we analyse the absolute stability of a closed loop system containing an interval plant in the forward path. The resulting theorem gives conditions for robust stability under nonlinear perturbations. This theorem is based on a result concerning the strict positive realness of families of interval rational functions. Finally, robust stability under unstructured (H¿ type) perturbations is considered and we deduce the necessary and sufficient conditions for robust stabilization in the presence of perturbations of this type. This result is again a generalization of a theorem on the H¿ norm of interval rational functions.","PeriodicalId":307181,"journal":{"name":"1990 American Control Conference","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126143168","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 : 1990-05-23DOI: 10.23919/ACC.1990.4791202
Y.H. Chen, J. Chen
The problem of stabilising a class of linear uncertain systems by using linear state feedback is addressed. The system possesses uncertainty which is time-varying, unknown, but lies within a prescribed set (hence bounded). No statistical information of the uncertainty is imposed. Nor any match condition is required. Necessary and sufficient conditions for quadratic stabilisability are formulated. The controller synthesis and stability analysis are investigated by a two level optimisation process. The result is believed to be practical (in the sense that it can be implemented for non-trivial physical systems) and non-conservative.
{"title":"Robust Control of Uncertain Systems with Time-Varying Uncertainty: A Computer-Aided Setup with Illustrations","authors":"Y.H. Chen, J. Chen","doi":"10.23919/ACC.1990.4791202","DOIUrl":"https://doi.org/10.23919/ACC.1990.4791202","url":null,"abstract":"The problem of stabilising a class of linear uncertain systems by using linear state feedback is addressed. The system possesses uncertainty which is time-varying, unknown, but lies within a prescribed set (hence bounded). No statistical information of the uncertainty is imposed. Nor any match condition is required. Necessary and sufficient conditions for quadratic stabilisability are formulated. The controller synthesis and stability analysis are investigated by a two level optimisation process. The result is believed to be practical (in the sense that it can be implemented for non-trivial physical systems) and non-conservative.","PeriodicalId":307181,"journal":{"name":"1990 American Control Conference","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123317001","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 : 1990-05-23DOI: 10.1109/ACC.1990.4174113
A. Blackwell, C. Blackwell
In support of development of bioregenerative life support systems for space habitats, a chamber for conducting research on the biophysical response of crop plants in controlled environments is being designed by the National Aeronautics and Space Administration. The imprecision of mathematical descriptions of the behavior of biological systems led to the development of a model which can be used to derive a strategy for control of the chamber environment which is robust to the system uncertainties. The modeling approach and observations of the characteristics of the model are described.
{"title":"Development of a Model for Control of the NASA CELSS Crop Growth Research Chamber","authors":"A. Blackwell, C. Blackwell","doi":"10.1109/ACC.1990.4174113","DOIUrl":"https://doi.org/10.1109/ACC.1990.4174113","url":null,"abstract":"In support of development of bioregenerative life support systems for space habitats, a chamber for conducting research on the biophysical response of crop plants in controlled environments is being designed by the National Aeronautics and Space Administration. The imprecision of mathematical descriptions of the behavior of biological systems led to the development of a model which can be used to derive a strategy for control of the chamber environment which is robust to the system uncertainties. The modeling approach and observations of the characteristics of the model are described.","PeriodicalId":307181,"journal":{"name":"1990 American Control Conference","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123446428","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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