Pub Date : 1992-06-24DOI: 10.23919/ACC.1992.4792171
P. Gahinet
The state-space formulas for the usual H∞ central controller become singular when approaching the optimum γopt. A new approach is taken to circumvent this difficulty. It consists of extending the notion of central controller to include proper controllers with a feedthrough term. While such controllers are still derived from the usual Riccati solutions X∞, and Y∞, their feedthrough gain can be selected so as to neutralize the singularities near γopt. This provides numerically stable formulas for the controller parameters and eliminates the discontinuity between the realizations of nearly optimal and of reduced-order optimal central controllers. The advantages of this method are illustrated on a few examples.
{"title":"Reliable computation of H∞ central controllers near the optimum","authors":"P. Gahinet","doi":"10.23919/ACC.1992.4792171","DOIUrl":"https://doi.org/10.23919/ACC.1992.4792171","url":null,"abstract":"The state-space formulas for the usual H<sub>∞</sub> central controller become singular when approaching the optimum γ<sub>opt</sub>. A new approach is taken to circumvent this difficulty. It consists of extending the notion of central controller to include proper controllers with a feedthrough term. While such controllers are still derived from the usual Riccati solutions X<sub>∞</sub>, and Y<sub>∞</sub>, their feedthrough gain can be selected so as to neutralize the singularities near γ<sub>opt</sub>. This provides numerically stable formulas for the controller parameters and eliminates the discontinuity between the realizations of nearly optimal and of reduced-order optimal central controllers. The advantages of this method are illustrated on a few examples.","PeriodicalId":297258,"journal":{"name":"1992 American Control Conference","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126450104","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 : 1992-06-24DOI: 10.23919/ACC.1992.4792584
H. Zhuang, Y. Shiu
An iterative algorithm for calibration of wrist-mounted robotic sensors is presented. The sensor-wrist calibration can be performed by solving a system of homogeneous transformation equations of the form AiX = XBi, where X is the unknown sensor position relative to the robot wrist, Ai is the ith robot motion, and Bi is the ith sensor motion [1-4]. Unlike existing approaches, the algorithm presented here solves kinematic parameters of X in one stage, thus eliminating error propagations and improving noise sensitivities. Moreover, with the iterative algorithm, the parameters of X are observable even when the rotation part of Bi is unknown. This is important in practice since position is easier to measure than orientation. Comparative simulation studies show that the accuracy performance of the iterative algorithm is, in general, better than that of noniterative two-stage algorithms, regardless whether the orientation part of Bi is used. The approach presented in this paper also has wide applications for wrist-mounted tool calibration.
{"title":"An Iterative Algorithm for Wrist-Mounted Robotic Sensor Calibration with or without External Orientation Measurement","authors":"H. Zhuang, Y. Shiu","doi":"10.23919/ACC.1992.4792584","DOIUrl":"https://doi.org/10.23919/ACC.1992.4792584","url":null,"abstract":"An iterative algorithm for calibration of wrist-mounted robotic sensors is presented. The sensor-wrist calibration can be performed by solving a system of homogeneous transformation equations of the form AiX = XBi, where X is the unknown sensor position relative to the robot wrist, Ai is the ith robot motion, and Bi is the ith sensor motion [1-4]. Unlike existing approaches, the algorithm presented here solves kinematic parameters of X in one stage, thus eliminating error propagations and improving noise sensitivities. Moreover, with the iterative algorithm, the parameters of X are observable even when the rotation part of Bi is unknown. This is important in practice since position is easier to measure than orientation. Comparative simulation studies show that the accuracy performance of the iterative algorithm is, in general, better than that of noniterative two-stage algorithms, regardless whether the orientation part of Bi is used. The approach presented in this paper also has wide applications for wrist-mounted tool calibration.","PeriodicalId":297258,"journal":{"name":"1992 American Control Conference","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128181048","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 : 1992-06-24DOI: 10.1109/ACC.1992.4175583
Xiangbo Feng, K. Loparo
In this paper, we study the effect of state (or output) quantization in scalar discrete-time linear control systems by regarding the quantized state as a partial observation of the true state rather than an approximation. With this point of view, the quantized system is analyzed as a partially observed stochastic system and the problem of optimal state information gathering-from the history of the quantized output is investigated. It is shown that this problem is equivalent to an optimal control problem for a controlled Markov chain.
{"title":"On the Design of Active Learning Controllers for Linear Systems with Quantized State Measurements","authors":"Xiangbo Feng, K. Loparo","doi":"10.1109/ACC.1992.4175583","DOIUrl":"https://doi.org/10.1109/ACC.1992.4175583","url":null,"abstract":"In this paper, we study the effect of state (or output) quantization in scalar discrete-time linear control systems by regarding the quantized state as a partial observation of the true state rather than an approximation. With this point of view, the quantized system is analyzed as a partially observed stochastic system and the problem of optimal state information gathering-from the history of the quantized output is investigated. It is shown that this problem is equivalent to an optimal control problem for a controlled Markov chain.","PeriodicalId":297258,"journal":{"name":"1992 American Control Conference","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128191777","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 : 1992-06-24DOI: 10.23919/ACC.1992.4792602
B. Brogliato, A. Trofino-Neto
In this paper we deal with robust control of a class of nonlinear systems which contain partially known uncertainties. To cope with the uncertainties an adaptive controller is proposed and both the uniform boundedness of all the closed-loop signals and uniform ultimate boundedness of the system state are guaranted. In contrast with some previous attempts to relax some a priori knowledge on the uncertainties bounds by using a discontinuous control law [8], in this paper we propose a continuous control law. Hence chattering problems (which have practical importance) can be avoided. The results are illustrated with motion control of rigid robot manipulators.
{"title":"Adaptive Robust Control of a Class of Nonlinear Dynamic Systems Containing Partially Known Uncertainties","authors":"B. Brogliato, A. Trofino-Neto","doi":"10.23919/ACC.1992.4792602","DOIUrl":"https://doi.org/10.23919/ACC.1992.4792602","url":null,"abstract":"In this paper we deal with robust control of a class of nonlinear systems which contain partially known uncertainties. To cope with the uncertainties an adaptive controller is proposed and both the uniform boundedness of all the closed-loop signals and uniform ultimate boundedness of the system state are guaranted. In contrast with some previous attempts to relax some a priori knowledge on the uncertainties bounds by using a discontinuous control law [8], in this paper we propose a continuous control law. Hence chattering problems (which have practical importance) can be avoided. The results are illustrated with motion control of rigid robot manipulators.","PeriodicalId":297258,"journal":{"name":"1992 American Control Conference","volume":"198 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121606428","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 : 1992-06-24DOI: 10.23919/ACC.1992.4792649
P. Maghami, S. Gupta, S. M. Joshi
A new method for the design of dissipative, low-authority controllers has been developed. The method uses a sequential approach along with eigensystem assignment to compute rate and position gain matrices that assign a number of closed-loop poles of the system to desired locations. A numerical example is worked out for a flexible structure in order to demonstrate the proposed technique.
{"title":"Design of Dissipative Low-Authority Controllers Using An Eigensystem Assignment Technique","authors":"P. Maghami, S. Gupta, S. M. Joshi","doi":"10.23919/ACC.1992.4792649","DOIUrl":"https://doi.org/10.23919/ACC.1992.4792649","url":null,"abstract":"A new method for the design of dissipative, low-authority controllers has been developed. The method uses a sequential approach along with eigensystem assignment to compute rate and position gain matrices that assign a number of closed-loop poles of the system to desired locations. A numerical example is worked out for a flexible structure in order to demonstrate the proposed technique.","PeriodicalId":297258,"journal":{"name":"1992 American Control Conference","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131382470","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 : 1992-06-24DOI: 10.23919/ACC.1992.4792438
Hansil Kim, C. Sims, K. Nagpal
In this paper we consider the problem of estimation with reduced order filter/observers with an H∞ type performance criterion. For a give n-th order linear system, we give necessary and sufficient conditions for there to exist an "Unbiased" (precise definition given in the Definition 2 of the paper) filter of order l ≪ n to estimate l states of the system. When the necessary and sufficient conditions ar met, state space formulae are given for a reduced order filter that achieves the desired performance.
{"title":"Reduced order filtering in an H∞ setting","authors":"Hansil Kim, C. Sims, K. Nagpal","doi":"10.23919/ACC.1992.4792438","DOIUrl":"https://doi.org/10.23919/ACC.1992.4792438","url":null,"abstract":"In this paper we consider the problem of estimation with reduced order filter/observers with an H∞ type performance criterion. For a give n-th order linear system, we give necessary and sufficient conditions for there to exist an \"Unbiased\" (precise definition given in the Definition 2 of the paper) filter of order l ≪ n to estimate l states of the system. When the necessary and sufficient conditions ar met, state space formulae are given for a reduced order filter that achieves the desired performance.","PeriodicalId":297258,"journal":{"name":"1992 American Control Conference","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131997099","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 : 1992-06-24DOI: 10.1109/ACC.1992.4175125
M. Sartori, P. Antsaklis
Using neural networks, a method for the failure behavior identification of a space antenna model is investigated. The proposed method employs three stages. If a fault is suspected by the first stage of fault detection, a diagnostic test is performed on the antenna. The diagnostic test's results are used by the second and third stages to identify which fault occurred and to diagnose the extent of the fault, respectively. The first stage uses a multi-layer perceptron, the second uses a multi-layer perceptron and neural networks trained with the quadratic optimization algorithm, a novel training procedure, and the third stage uses back-propagation trained neural networks.
{"title":"Failure Behavior Identification for a Space Antenna via Neural Networks","authors":"M. Sartori, P. Antsaklis","doi":"10.1109/ACC.1992.4175125","DOIUrl":"https://doi.org/10.1109/ACC.1992.4175125","url":null,"abstract":"Using neural networks, a method for the failure behavior identification of a space antenna model is investigated. The proposed method employs three stages. If a fault is suspected by the first stage of fault detection, a diagnostic test is performed on the antenna. The diagnostic test's results are used by the second and third stages to identify which fault occurred and to diagnose the extent of the fault, respectively. The first stage uses a multi-layer perceptron, the second uses a multi-layer perceptron and neural networks trained with the quadratic optimization algorithm, a novel training procedure, and the third stage uses back-propagation trained neural networks.","PeriodicalId":297258,"journal":{"name":"1992 American Control Conference","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132012469","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 : 1992-06-24DOI: 10.23919/ACC.1992.4792489
G. Vinnicombe
{"title":"Robust Design in the Graph Topology; A Benchmark Example","authors":"G. Vinnicombe","doi":"10.23919/ACC.1992.4792489","DOIUrl":"https://doi.org/10.23919/ACC.1992.4792489","url":null,"abstract":"","PeriodicalId":297258,"journal":{"name":"1992 American Control Conference","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132492186","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 : 1992-06-24DOI: 10.23919/ACC.1992.4792662
B. Ninness, G. Goodwin
This paper addresses the problem of providing bounds on estimated plant frequency response in a form suitable for robust control design. Our approach is to consider the undermodelling as a particular realisation of a random variable and to derive bounds based on averages over all possible noise realisations and over all possible undermodeling realisations. We critically examine the performance of these bounds relative to those that would be obtained by fitting a high order model to the data and then truncating to a low order model. We also show that the parameter in the distribution for the undermodelling can be estimated from the data analagously to the way measurement noise variance is estimated from prediction errors. We propose several new estimators and examine their finite data and asymptotic properties.
{"title":"Robust Frequency Response Estimation Accounting for Noise and Undermodelling","authors":"B. Ninness, G. Goodwin","doi":"10.23919/ACC.1992.4792662","DOIUrl":"https://doi.org/10.23919/ACC.1992.4792662","url":null,"abstract":"This paper addresses the problem of providing bounds on estimated plant frequency response in a form suitable for robust control design. Our approach is to consider the undermodelling as a particular realisation of a random variable and to derive bounds based on averages over all possible noise realisations and over all possible undermodeling realisations. We critically examine the performance of these bounds relative to those that would be obtained by fitting a high order model to the data and then truncating to a low order model. We also show that the parameter in the distribution for the undermodelling can be estimated from the data analagously to the way measurement noise variance is estimated from prediction errors. We propose several new estimators and examine their finite data and asymptotic properties.","PeriodicalId":297258,"journal":{"name":"1992 American Control Conference","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130076334","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 : 1992-06-24DOI: 10.23919/ACC.1992.4792371
M. Soroush, C. Kravaris
In this paper, a general continuous-time nonlinear formulation of model predictive control is proposed. The control law calculates the manipulated input that minimizes a quadratic performance index in the presence of input constraints and process dead-time. Connections between the proposed approach and existing controllers in the differential geometric literature are established. The theory is illustrated by a CSTR example.
{"title":"A Continuous-Time Formulation of Nonlinear Model Predictive Control","authors":"M. Soroush, C. Kravaris","doi":"10.23919/ACC.1992.4792371","DOIUrl":"https://doi.org/10.23919/ACC.1992.4792371","url":null,"abstract":"In this paper, a general continuous-time nonlinear formulation of model predictive control is proposed. The control law calculates the manipulated input that minimizes a quadratic performance index in the presence of input constraints and process dead-time. Connections between the proposed approach and existing controllers in the differential geometric literature are established. The theory is illustrated by a CSTR example.","PeriodicalId":297258,"journal":{"name":"1992 American Control Conference","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134543217","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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