Maximum-likelihood soft-decision decoding of linear block codes is addressed. A binary multiple-check generalization of the Wagner rule is presented, and two methods for its implementation, one of which resembles the ...
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Maximum-likelihood soft-decision decoding of linear block codes is addressed. A binary multiple-check generalization of the Wagner rule is presented, and two methods for its implementation, one of which resembles the suboptimal Forney-Chase algorithms, are described. Besides efficient soft decoding of small codes, the generalized rule enables utilization of subspaces of a wide variety, thereby yielding maximum-likelihood decoders with substantially reduced computational complexity for some larger binary codes. More sophisticated choice and exploitation of the structure of both a subspace and the coset representatives are demonstrated for the (24, 12) Golay code, yielding a computational gain factor of about 2 with respect to previous methods. A ternary single-check version of the Wagner rule is applied for efficient soft decoding of the (12, 6) ternary Golay code.< >
Maximum likelihood soft decision decoding of block and lattice codes has recently gained renewed interest. This is partially due to the major role of block and lattice codes in block-coded modulation techniques for ba...
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In this paper, the Linear Constrained Regulation Problem for continuous-time systems will be studied and a design algorithm for a linear constrained feedback controller will be developed. Both state and control vector...
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In this paper, the Linear Constrained Regulation Problem for continuous-time systems will be studied and a design algorithm for a linear constrained feedback controller will be developed. Both state and control vectors are assumed to be subjected to linear constraints The approach presented, is based on the notion of positive invariance of polyhedral sets. Existence conditions for a control law that transfers asymptotically to the origin all initial states in a polyhedral subset of the state space is formulated. Then, a solution to the LCRP is derived solving a non-linear optimization problem
A multiple model adaptive controller that provides for reconfiguration in response to sensor and/or actuator failures is developed for an approach and landing profile for the short take-off and landing (STOL) F-15 air...
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A multiple model adaptive controller that provides for reconfiguration in response to sensor and/or actuator failures is developed for an approach and landing profile for the short take-off and landing (STOL) F-15 aircraft. Each elemental controller within the multiple model controller is based on a command generator tracker/proportional plus integral/Kalman filter design, with residual monitoring used as the mechanism to select the appropriate controller. The elemental controllers are each based on an assumed system status: no failures or a single failed surface or sensor. controller selection is evaluated for controller mixing based on all algorithm-computed probabilities of each elemental controller being the 'correct' controller to use. The entire multiple model controller is evaluated against a truth model with a selected failure, and then repeating the process for all failure modes of interest.< >
In this paper several techniques are given for the identification of stable LSI discrete time systems from input-output data. Explicit H ∞ norm error bounds are given and convergence in the noise free and the unifor...
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In this paper several techniques are given for the identification of stable LSI discrete time systems from input-output data. Explicit H ∞ norm error bounds are given and convergence in the noise free and the uniformly bounded deterministic noise case are established. The assumptions made on the unknown system are minimal and are limited throughout the paper to a lower bound on the decay rate of the unknown system and an upper bound on the gain of the unknown system. Given this information an experiment and a construction are specified: the experiment involves obtaining a specified number of frequency measurements of the unknown systems at a set of specified frequencies; the construction uses this experimental data to generate an identified model with prescribed H ∞ norm error tolerance to the unknown system. The resulting model identification process is highly efficient from a computational point of view.
This paper is a condensed version of recent work [17] wherein several fundamental practical concerns pertaining to the use of linear, time-invariant, distributed parameter systems as models of physical processes are i...
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This paper is a condensed version of recent work [17] wherein several fundamental practical concerns pertaining to the use of linear, time-invariant, distributed parameter systems as models of physical processes are investigated. In particular, it is argued here that certain common distributed parameter systems exhibit properties which make them unsuitable for use as plant models in the design of feedback compensation. Classes of distributed parameter systems exhibiting these properties are defined and are said to be ill-posed for use in feedback compensator design. The structure of these classes is investigated within an extremely general mathematical framework which imposes no a priori restrictions on the class of distributed parameter systems under consideration. Within this framework necessary and sufficient conditions are given which completely characterise the classes of ill-posed models and establish their equivalence. These conditions are concretely illustrated by way of applications to several well-known flexible structure models. Surprisingly, several of these models are determined to be ill-posed for use in feedback compensator design.
There has been a great deal of excitement recently over the development of a theory for explicitly linearizing the input-output response of a nonlinear system using state feedback. One shortcoming of this theory is th...
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There has been a great deal of excitement recently over the development of a theory for explicitly linearizing the input-output response of a nonlinear system using state feedback. One shortcoming of this theory is the inability to deal with non-minimum phase nonlinear systems. Highly maneuverable jet aircraft, such as the V/STOL Harrier, belong to an important class of a slightly non-minimum phase nonlinear systems. The non-minimum phase character of these aircraft is clue in part to a slight coupling between rolling moments and lateral accelerations. In this paper, we show that, while straightforward application of the linearization theory to a non-minimum phase system results in a system with a linear input-output response but unstable internal dynamics, designing a feedback control based on a minimum phase approximation to the true system results in a system with desirable properties such as bounded tracking and asymptotic stability.
The GE multidisciplinary expert-aided analysis and design (MEAD) project, which involves the integration of several computer-aided controlengineering (CACE) packages under a supervisor which coordinates the execution...
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The GE multidisciplinary expert-aided analysis and design (MEAD) project, which involves the integration of several computer-aided controlengineering (CACE) packages under a supervisor which coordinates the execution of these packages with a database manager, an expert system, and an advanced user interface, is discussed. The principal components are, in functional terms: a supervisor, which integrates the underlying CACE packages and coordinates all activity within the GE MEAD computer program (GMCP); an expert system shell and rule bases for expert aiding of specific procedures to relieve the user from unnecessary low-level detail; a database manager for tracking system models that evolve over time along with associated results; and a user interface that facilitates access to the CACE package capabilities by permitting the user to work in several modalities, i.e. menu/forms style, using GE MEAD commands, the core packages' native commands, or the GE MEAD macro facility. The operation of the GMCP, including the user interface, expert system, and database manager, is illustrated by examples.< >
Calculation of voltages in a mine electrical distribution system using a power-flow program may fail to yield meaningful results if the iterative power-flow procedure fails to converge. A modified power-flow technique...
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Calculation of voltages in a mine electrical distribution system using a power-flow program may fail to yield meaningful results if the iterative power-flow procedure fails to converge. A modified power-flow technique that converges for most of the mine electrical power-flow input data, even though the same input data do not yield a convergent solution with a traditional Newton power-flow algorithm, is presented. When no operable solution to the power-flow problem exists, the results tend to indicate the location of the modeling error that is responsible for nonconvergence. An extensive case study using data for a mine electrical power system is presented to demonstrate the robustness and error identification properties of the power-flow algorithm.< >
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