A three step method for obtaining nearly maximum likelihood ARMA spectral estimates is presented. The computational complexity of the algorithm is comparable to Yule-Walker methods, but the method gives asymptotically...
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A three step method for obtaining nearly maximum likelihood ARMA spectral estimates is presented. The computational complexity of the algorithm is comparable to Yule-Walker methods, but the method gives asymptotically efficient estimates. The implementation of the algorithm is discussed, and numerical examples are presented to illustrate its performance.
作者：
STIMSON, WAMARSH, MTUTTICH, RMWilliam A. Stimsonreceived his B.S. degree in mathematics from the University of Texas at El Paso in 1964
and his M.S. degree in engineering from the University of Santa Clara in 1971. He served in the U.S. Army Artillery during the Korean Conflict and subsequently was employed at IBM Huntsville Alabama until 1968 where he worked in the design of automatic control systems of the Saturn vehicle. From 1968 until 1971 he was employed at Ames Research Center Moffett Field in the design of nonlinear control systems for sounding rockets and pencil-shaped spacecraft. Following this Mr. Stimson worked at Hewlett Packard Sunnyvale California as a test engineer in automatic test systems. Since 1973 Mr. Stimson has been employed at the Naval Ship Weapon Systems Engineering Station Port Hueneme. He was a ship qualification trials project supervisor for many years and is now serving as master ordnance repair deputy program manager. Mr. Stimson is a member of the American Society of Naval Engineers and is program chairman of the Channel Islands Section. Cdr. Michael T. Marsh
USNreceived a B.S. in mathematics from the University of Nebraska and was commissioned via the NESEP program in 1970. He holds an M.S. in computer science from the U.S. Navy Postgraduate School and an MBA from the State University of New York. Cdr. Marsh has served in the weapons department of USSFrancis Hammond (FF-1067) and of USSJohn S. McCain (DDG-36). He was weapons officer aboard USSSampson (DDG-10). As an engineering duty officer Cdr. Marsh was the technical design officer for PMS-399 at the FFG-7 Class Combat System Test Center from 1978 to 1982. He is presently combat system officer at SupShip Jacksonville and has been active in the MOR program since its inception. Cdr. Marsh is also the vice chairman of the Jacksonville Section of ASNE. LCdr. Richard M. Uttich
USNholds B.S. and M.S. degrees in mechanical engineering from Stanford University. He enlisted in the Navy in 1965 serving as an electronics technician aboard USSNereus (A
The 600-ship United States Navy offers private shipyards an unprecedented opportunity for overhaul of surface combatants with complex combat systems. Recognizing the new challenge associated with the overhaul of high ...
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The 600-ship United States Navy offers private shipyards an unprecedented opportunity for overhaul of surface combatants with complex combat systems. Recognizing the new challenge associated with the overhaul of high technology combat systems in the private sector, the Navy in 1983 established the master ordnance repair (MOR) program. This program, a joint effort of the Naval Sea systems Command (NAVSEA) and the Shipbuilders Council of America (SCA), was designed to identify and qualify those companies and private shipyards technically capable of managing combat systems work and conducting combat system testing. Standard Item 009–67 describes the role of the MOR company in combat system overhaul. It defines terms that are important to understanding the item itself, and imposes upon the prime contractor an obligation to utilize the MOR subcontractor in a managerial capacity. Specific tasks are assigned to the MOR company in planning, production, and testing. Finally, this standard item describes to the Navy planner how to estimate the size of the MOR team appropriate to the work package, a feature that will ensure that combat system bids are tailored to a specific availability.
The recently obtained evidence of the need for a positive real element in an adaptive system leaves us with a disturbing gap in adaptive control theory. It is a fact that in some applications adaptive controllers are ...
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The recently obtained evidence of the need for a positive real element in an adaptive system leaves us with a disturbing gap in adaptive control theory. It is a fact that in some applications adaptive controllers are performing well in practice. How can these systems behave well in practical situations which must contain modeling error? This paper introduces a preliminary result which indicates that it may be possible to maintain the needed positive real system in the presence of modeling error. The result shows that if a continuous-time system with large high frequency uncertainty is treated appropriately with antialiasing filters and sampled slowly enough, the resulting discrete-time system may contain very little uncertainty. With small enough uncertainty in the plant, a positive real system in the adaptive loop is possible.
In this paper, two theorems are quoted which, when applied together, provide much information about the robustness of adaptive control schemes. From these two theorems, another theorem is developed which can explain w...
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In this paper, two theorems are quoted which, when applied together, provide much information about the robustness of adaptive control schemes. From these two theorems, another theorem is developed which can explain why adaptive controllers can perform robustly in certain practical situations, while possibly failing in other situations. In particular, if the bandwidth constraints on a controlsystems are lenient enough to allow the use of a sampling frequency which is smaller than the frequency at which unstructured uncertainty becomes significant, an adaptive controller can behave robustly. Many, if not all, of the applications of adaptive control which have been successful employ relatively slow sampling of the process. Thus, the results of this paper provide a theoretical explanation of how certain adaptive controllers are performing robustly in practice. In addition, the final theorem is of a form which provides insight into what a priori knowledge is required to achieve robust adaptive control and how this knowledge say be used.
This paper presents a new method for calculating a rational transfer function matrix using a Walsh expansion of the impulse response matrix. The algorithm proposed appears to be computationally convenient owing to cer...
This paper presents a new method for calculating a rational transfer function matrix using a Walsh expansion of the impulse response matrix. The algorithm proposed appears to be computationally convenient owing to certain properties of the Walsh functions. An example is given to illustrate the method.
An examination is made of linear regulator problems with an additional cost for applying a nonzero control at each instant. The dual of this problem is the least-squares filtering problem with a cost for taking measur...
An examination is made of linear regulator problems with an additional cost for applying a nonzero control at each instant. The dual of this problem is the least-squares filtering problem with a cost for taking measurements. Because a solution to the general problem involves solving a two point boundary value problem in nonlinear matrix differential or defference equations, two easily-computed suboptimal control schemes and some useful bounds are proposed. A class of problems is also delineated for which the optimum solution has some special properties which enable it to be computed simply and directly.
This book introduces an optimal iterative learning control (ILC) design framework from the end user's point of view. Its central theme is the understanding of model dynamics, the construction of a procedure for sy...
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ISBN:
(数字)9783031802362
ISBN:
(纸本)9783031802355;9783031802386
This book introduces an optimal iterative learning control (ILC) design framework from the end user's point of view. Its central theme is the understanding of model dynamics, the construction of a procedure for systematic input updating and their contribution to successful algorithm design. The authors discuss the many applications of ILC in industrial systems, applications such as robotics and mechanical testing.
The text covers a number of optimal ILC design methods, including gradient-based and norm-optimal ILC. Their convergence properties are described and detailed design guidelines, including performance-improvement mechanisms, are presented. Readers are given a clear picture of the nature of ILC and the benefits of the optimization-based approach from the conceptual and mathematical foundations of the problem of algorithm construction to the impact of available parameters in making acceleration of algorithmic convergence possible. Three case studies on robotic platforms, an electro-mechanical machine, and robot-assisted stroke rehabilitation are included to demonstrate the application of these methods in the real-world.
With its emphasis on basic concepts, detailed design guidelines and examples of benefits,
Optimal Iterative Learning control
will be of value to practising engineers and academic researchers alike.
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