This paper introduces a mechanism for assessment of local optimality of closed-loop performance. The basis of this result is the estimation of the first and second derivatives of a cost function with respect to the co...
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This paper introduces a mechanism for assessment of local optimality of closed-loop performance. The basis of this result is the estimation of the first and second derivatives of a cost function with respect to the controller parameters. The criterion adopted to measure the system performance is the linear quadratic cost function, in the time domain, although its derivatives are obtained in the frequency domain via spectral analysis of closed-loop signals. These estimates of first and second derivatives of the cost function are also valuable for computing appropriate directions for tuning the controller parameters. Even though the derivatives are computed in the frequency domain, the actual cost function is computed with time-domain measurements taken along the tuning directions. The tuning scheme can be direct (model free) or based on a nonparametric model of the plant. Moreover, this scheme includes a mechanism for guaranteeing stability of the closed-loop system.
Channel errors significantly reduce the performance of adaptive dequantizers. In this paper, we extend the techniques used in Kaiman filter based adaptive quantization to arrive at new dequantization schemes which are...
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Channel errors significantly reduce the performance of adaptive dequantizers. In this paper, we extend the techniques used in Kaiman filter based adaptive quantization to arrive at new dequantization schemes which are more robust to channel errors. This is achieved by utilising the estimates produced by a Kalman filter based on a linear signal model which embodies the entire encoder/channel combination. Extensions to Kaiman smoothing based on the same signal model result in further performance improvement at the expense of a small delay.
This paper considers two refinements to an existing iterative identification/control design scheme in which the model adjustment and controller enhancement stages are coupled. The first refinement explicitly decouples...
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This paper considers two refinements to an existing iterative identification/control design scheme in which the model adjustment and controller enhancement stages are coupled. The first refinement explicitly decouples these stages to demonstrate the individual effects of each stage upon the other. The second refinement foregoes the model adjustment stage and concentrates solely upon the controller enhancement with respect to achieved and designed performance measures.< >
The asymptotic properties of inhomogeneous products in the max-plus algebra context have been investigated. In particular, for products involving matrices with the same unique critical circuit, we have obtained some s...
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The asymptotic properties of inhomogeneous products in the max-plus algebra context have been investigated. In particular, for products involving matrices with the same unique critical circuit, we have obtained some sufficiency conditions under which the rank of the final product matrix is less than or equal to the length of the critical circuit of the matrices in the product. For a product comprising matrices with the same unique critical circuit of length 1, the asymptotic rank is 1.
Discusses the use of a variable bit rate ADPCM system for speech coding. The authors present an ADPCM system, using arithmetic coding and Kalman filtering techniques, that can code signals at very low bit rates, where...
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Discusses the use of a variable bit rate ADPCM system for speech coding. The authors present an ADPCM system, using arithmetic coding and Kalman filtering techniques, that can code signals at very low bit rates, where standard fixed bit rate ADPCM systems fail. The proposed system, at an average bit rate of 16 kbps, produces a reconstructed speech signal that by informal listening tests has been judged to be of significantly higher quality than the LD-CELP 16 kbps speech coding standard. The authors believe that the output quality is comparable to that of LD-CELP at an average rate of around 12 kbps, and the quality at 8 kbps is very promising. Other advantages of the scheme are a reduction in complexity over the LD-CELP standard, and an increase in design flexibility.< >
Presents a nonlinear extension of the /spl nu/-gap metric introduced in Vinnicombe (1993). Indeed, we present an input-output version of the generalized stability margin and the /spl nu/-gap metric. The notion of imag...
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Presents a nonlinear extension of the /spl nu/-gap metric introduced in Vinnicombe (1993). Indeed, we present an input-output version of the generalized stability margin and the /spl nu/-gap metric. The notion of image representation as presented in van der Schaft (1996) allows one to use these alternative definitions in a nonlinear context for the derivation of a robust stability theorem.
Several new methods for the identification of approximate models of an open loop plant on the basis of closed loop data have been presented. In this paper, we extend two of these methods to the nonlinear case: we cons...
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Several new methods for the identification of approximate models of an open loop plant on the basis of closed loop data have been presented. In this paper, we extend two of these methods to the nonlinear case: we consider that both the plant and the controller can be nonlinear. The first method is a two-step procedure. The sensitivity function of the closed loop system is identified through a high order nonlinear model and it is used in the second step to simulate a noise free input signal for an open loop like identification of the plant. The second method identifies the right coprime factors of the plant through an open loop like identification of the filtered sensitivity and complementary sensitivity functions. For both methods, we assume that the measurement noise enters the system under a high S/N ratio assumption.
In this paper we develop two sequential or "on-line" estimation schemes in the time domain for dynamic shock-error models which are special cases of errors-in-variables models. Our approach utilizes a state ...
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In this paper we develop two sequential or "on-line" estimation schemes in the time domain for dynamic shock-error models which are special cases of errors-in-variables models. Our approach utilizes a state space representation of the model, Kalman filtering techniques and on-line algorithms. The first on-line algorithm is based on the Expectation Maximization (EM) algorithm and uses stochastic approximations to maximize the Kullback Leibler (KL) information measure. The second on-line algorithm we propose is a gradient based scheme and uses stochastic approximations to maximize the log likelihood. In comparison to the off-line Maximum Likelihood estimation scheme used in [1], our on-line algorithms have significantly reduced computational costs and negligible memory requirements.
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