The present paper develops a framework for the analysis and synthesis of linear time-varying (LTV) digital filters in the frequency domain. LTV filters are modeled by the successive use of linear time-invariant (LTI) filters. The time-varying digital filtering is also discussed in relation to the notion of the short-time spectrum and the generalized frequency function. In addition, we present an efficient implementation procedure which reduces the number of filter coefficients.
{"title":"Time-varying digital signal processing","authors":"N. Huang, J. Aggarwal","doi":"10.1109/CDC.1980.271863","DOIUrl":"https://doi.org/10.1109/CDC.1980.271863","url":null,"abstract":"The present paper develops a framework for the analysis and synthesis of linear time-varying (LTV) digital filters in the frequency domain. LTV filters are modeled by the successive use of linear time-invariant (LTI) filters. The time-varying digital filtering is also discussed in relation to the notion of the short-time spectrum and the generalized frequency function. In addition, we present an efficient implementation procedure which reduces the number of filter coefficients.","PeriodicalId":332964,"journal":{"name":"1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1980-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114965477","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}
This paper presents an application of multi-input, multi-output (MIMO) model reference adaptive control (MRAC) to a typical power plant. Three MRAC designs are presented, two analog and one digital. With one analog algorithm, the system output errors (plant and reference model) are asymptotically stable, provided a positive real constraint is satisfied. A second analog algorithm results in a bounded output error but relies on a less restrictive constraint. The third algorithm is digital and is similar to the second. The power plant model is based on the Cromby model with the addition of a governor valve management algorithm, turbine dynamics and turbine interactions with extraction flows.
{"title":"Model reference adaptive control of electric generating plants","authors":"L. Mabius, K. Kalnitsky, H. Kaufman","doi":"10.1109/CDC.1980.271801","DOIUrl":"https://doi.org/10.1109/CDC.1980.271801","url":null,"abstract":"This paper presents an application of multi-input, multi-output (MIMO) model reference adaptive control (MRAC) to a typical power plant. Three MRAC designs are presented, two analog and one digital. With one analog algorithm, the system output errors (plant and reference model) are asymptotically stable, provided a positive real constraint is satisfied. A second analog algorithm results in a bounded output error but relies on a less restrictive constraint. The third algorithm is digital and is similar to the second. The power plant model is based on the Cromby model with the addition of a governor valve management algorithm, turbine dynamics and turbine interactions with extraction flows.","PeriodicalId":332964,"journal":{"name":"1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1980-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115363024","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}
A method of actively controlling the apparent stiffness of a manipulator end effecter is presented. The approach allows the programmer to specify the three transnational and three rotational stiffness of a frame located arbitrarily in hand coordinates. Control of the nominal position of the hand then permits simultaneous position and force control. Stiffness may be changed under program control to match varying task requirements. A rapid servo algorithm is made possible by transformation of the problem into joint space at run time. Applications examples are given.
{"title":"Active stiffness control of a manipulator in cartesian coordinates","authors":"J. Salisbury","doi":"10.1109/CDC.1980.272026","DOIUrl":"https://doi.org/10.1109/CDC.1980.272026","url":null,"abstract":"A method of actively controlling the apparent stiffness of a manipulator end effecter is presented. The approach allows the programmer to specify the three transnational and three rotational stiffness of a frame located arbitrarily in hand coordinates. Control of the nominal position of the hand then permits simultaneous position and force control. Stiffness may be changed under program control to match varying task requirements. A rapid servo algorithm is made possible by transformation of the problem into joint space at run time. Applications examples are given.","PeriodicalId":332964,"journal":{"name":"1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1980-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124398470","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}
{"title":"Nonlinear zero distributions","authors":"A. Krener, A. Isidori","doi":"10.1109/CDC.1980.271882","DOIUrl":"https://doi.org/10.1109/CDC.1980.271882","url":null,"abstract":"","PeriodicalId":332964,"journal":{"name":"1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1980-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116759015","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}
We consider the solutions of the equation XR + QY + Φ. Here Q, R, Φ are given p x q, m x t and p x t polynomial matrices over a field k. X and Y are p x m and q x t polynomial matrices which are unknown. Using certain recent results on the realization of matrix fraction descriptions of transfer matrices, we give a characterization (parameterization) of all possible (X, Y) which solve this equation. This also provides a system theoretic interpretation for this equation.
我们考虑方程XR + QY + Φ的解。这里Q R Φ是给定域k上的p x Q m x t和p x t多项式矩阵，x和Y是未知的p x m和Q x t多项式矩阵。利用最近关于转移矩阵的矩阵分数描述实现的一些结果，给出了求解该方程的所有可能(X, Y)的表征(参数化)。这也为该方程提供了系统理论解释。
{"title":"The polynomial equation XR + QY = Φ: A characterization of solutions","authors":"E. Emre, L. Silverman","doi":"10.1109/CDC.1980.271845","DOIUrl":"https://doi.org/10.1109/CDC.1980.271845","url":null,"abstract":"We consider the solutions of the equation XR + QY + Φ. Here Q, R, Φ are given p x q, m x t and p x t polynomial matrices over a field k. X and Y are p x m and q x t polynomial matrices which are unknown. Using certain recent results on the realization of matrix fraction descriptions of transfer matrices, we give a characterization (parameterization) of all possible (X, Y) which solve this equation. This also provides a system theoretic interpretation for this equation.","PeriodicalId":332964,"journal":{"name":"1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1980-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127131127","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}
Recently lattice filters structures have been employed in numerous adaptive filtering applications such as noise cancelling; speech processing; and data equalization. In this paper we will be concerned with the algorithms that have been proposed to update the lattice filter coefficients. These algorithms typically fall into one of two classes, those based on stochastic (gradient) formulations and those founded on a least squares criterion. The latter are more complex; however, they provide for a faster response to sudden changes in the input data (e.g., a rapid initial convergence). It is the purpose of this paper to provide a brief exposition of the algorithms and to point out their various parallels. In particular, it is hoped that the simpler structure of the stochastic algorithms will shed some light on the more complex least squares procedures.
{"title":"Recursive lattice filters - A brief overview","authors":"E. Satorius, M. Shensa","doi":"10.1109/CDC.1980.271942","DOIUrl":"https://doi.org/10.1109/CDC.1980.271942","url":null,"abstract":"Recently lattice filters structures have been employed in numerous adaptive filtering applications such as noise cancelling; speech processing; and data equalization. In this paper we will be concerned with the algorithms that have been proposed to update the lattice filter coefficients. These algorithms typically fall into one of two classes, those based on stochastic (gradient) formulations and those founded on a least squares criterion. The latter are more complex; however, they provide for a faster response to sudden changes in the input data (e.g., a rapid initial convergence). It is the purpose of this paper to provide a brief exposition of the algorithms and to point out their various parallels. In particular, it is hoped that the simpler structure of the stochastic algorithms will shed some light on the more complex least squares procedures.","PeriodicalId":332964,"journal":{"name":"1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1980-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124961104","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}
A "first principles" argument is used to obtain the Mayne-Fraser two-filter smoother. The built-in asymmetry of the Mayne-Fraser smoother is pointed out, and it is shown how the asymmetry may be removed. Reversed-time Markov models play a key role here in forming a state estimate from future observations.
{"title":"The fixed-interval smoother for continuous-time processes","authors":"J. Wall, A. Willsky, N. Sandell","doi":"10.1109/CDC.1980.271822","DOIUrl":"https://doi.org/10.1109/CDC.1980.271822","url":null,"abstract":"A \"first principles\" argument is used to obtain the Mayne-Fraser two-filter smoother. The built-in asymmetry of the Mayne-Fraser smoother is pointed out, and it is shown how the asymmetry may be removed. Reversed-time Markov models play a key role here in forming a state estimate from future observations.","PeriodicalId":332964,"journal":{"name":"1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1980-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124987554","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}
This paper gives a qualitative comparison of Model Algorithmic Control (MAC) with other adaptive control techniques and discusses problems of active vs. passive adaptation, on-line vs. off-line identification and model compensation for nonminimum phase and time delay systems. Results of an application of MAC to Boiler-Steam Generator (BSG) systems are presented.
{"title":"Model algorithmic control for electric power plants","authors":"R. Mehra, J. Eterno","doi":"10.1109/CDC.1980.271800","DOIUrl":"https://doi.org/10.1109/CDC.1980.271800","url":null,"abstract":"This paper gives a qualitative comparison of Model Algorithmic Control (MAC) with other adaptive control techniques and discusses problems of active vs. passive adaptation, on-line vs. off-line identification and model compensation for nonminimum phase and time delay systems. Results of an application of MAC to Boiler-Steam Generator (BSG) systems are presented.","PeriodicalId":332964,"journal":{"name":"1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes","volume":"190 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1980-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123288296","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 we consider the decentralized stabilization problem for a class of large systems formed by the dynamic interconnection of several multivariable systems. For this structured class of systems, we establish the conditions under which the interconnected system is controllable and observable. We then simplify and interpret these conditions to obtain simple sufficient conditions in terms of the subsystem and interconnection subsystem coefficient matrices to guarantee controllability. Also, the conditions under which stabilization is possible, using decentralized feedback, are explicitly stated. We then simplify these to obtain subsystem level sufficient conditions. These conditions imply that if the interaction subsystems are stable and, in addition, certain mild restrictions on the subsystems and the interconnections hold, then the large system is stabilizable with decentralized feed-back. Finally, we state the conditions for stabilizing this class of systems via local state feedback.
{"title":"Decentralized control of interconnected dynamical systems","authors":"A. Ramakrishna, N. Viswanadham","doi":"10.1109/CDC.1980.271855","DOIUrl":"https://doi.org/10.1109/CDC.1980.271855","url":null,"abstract":"In this paper we consider the decentralized stabilization problem for a class of large systems formed by the dynamic interconnection of several multivariable systems. For this structured class of systems, we establish the conditions under which the interconnected system is controllable and observable. We then simplify and interpret these conditions to obtain simple sufficient conditions in terms of the subsystem and interconnection subsystem coefficient matrices to guarantee controllability. Also, the conditions under which stabilization is possible, using decentralized feedback, are explicitly stated. We then simplify these to obtain subsystem level sufficient conditions. These conditions imply that if the interaction subsystems are stable and, in addition, certain mild restrictions on the subsystems and the interconnections hold, then the large system is stabilizable with decentralized feed-back. Finally, we state the conditions for stabilizing this class of systems via local state feedback.","PeriodicalId":332964,"journal":{"name":"1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1980-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125348386","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 : 1980-12-01DOI: 10.1109/TCS.1981.1085013
R. Bitmead, B. O. Anderson
We present two new structures for adaptive filters based on the idea of frequency sampling filters and gradient based estimation algorithms. These filters have a finite impulse response (FIR) and can be thought of as attempting to approximate a desired frequency response at given points on the unit circle. The filters operate in real time with no batch processing of signals as is the case when using the discrete Fourier transform. They result in a marked reduction in dimension of the time-domain problem of fitting an Nth order FIR transversal filter to a collection of length 2 transversal filters and further to a collection of N scalar filters. The advantages of this are then discussed.
{"title":"Adaptive frequency sampling filters","authors":"R. Bitmead, B. O. Anderson","doi":"10.1109/TCS.1981.1085013","DOIUrl":"https://doi.org/10.1109/TCS.1981.1085013","url":null,"abstract":"We present two new structures for adaptive filters based on the idea of frequency sampling filters and gradient based estimation algorithms. These filters have a finite impulse response (FIR) and can be thought of as attempting to approximate a desired frequency response at given points on the unit circle. The filters operate in real time with no batch processing of signals as is the case when using the discrete Fourier transform. They result in a marked reduction in dimension of the time-domain problem of fitting an Nth order FIR transversal filter to a collection of length 2 transversal filters and further to a collection of N scalar filters. The advantages of this are then discussed.","PeriodicalId":332964,"journal":{"name":"1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1980-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125479508","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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