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Publications

2004

Gait selection for quadruped and hexapod walking systems

Authors
Silva, MF; Machado, JAT; Lopes, AM; Tar, JK;

Publication
ICCC 2004: SECOND IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL CYBERNETICS, PROCEEDINGS

Abstract
This paper studies periodic gaits of quadruped and hexapod locomotion systems. The purpose is to determine the best set of gait and locomotion variables for different robot velocities based on the system dynamics during walking. In this perspective, several performance measures are formulated and a set of experiments that reveal the influence of the gait and locomotion variables upon those proposed indices are performed.

2004

Recursive canonical variate subspace algorithm

Authors
Delgado, CJM; dos Santos, PL;

Publication
SICE 2004 ANNUAL CONFERENCE, VOLS 1-3

Abstract
In this paper, a recursive algorithm is presented, based on the CVA subspace identification algorithm. The main idea was to explore the relations between the orthogonal and oblique projections involved and to provide simpler expressions that allowed a recursive version of the algorithm - guaranteeing most of the advantages of this kind of methods, and still improving the numerical efficiency.

2004

USING OPTIMIZATION TO ESTIMATE SOIL INPUTS OF CROP MODELS FOR USE IN SITE-SPECIFIC MANAGEMENT

Authors
R. P. Braga and J. W. Jones,;

Publication
Transactions of the ASAE

Abstract

2004

Robust MOESP type algorithm with improved efficiency on the estimation of input matrices

Authors
Delgado, CJM; dos Santos, PL;

Publication
SICE 2004 ANNUAL CONFERENCE, VOLS 1-3

Abstract
In this paper, a new approach to estimate matrices B and D, in subspace methods, is provided. The starting point was one method proposed by Van Overschee and De Moor (1996). We have derived new (and simpler) expressions and we found that the original method can be rewritten as a weighted least squares problem, involving the future outputs and inputs and the observability matrix.

2004

Using optimization to estimate soil inputs of crop models for use in site-specific management

Authors
Braga, RP; Jones, JW;

Publication
TRANSACTIONS OF THE ASAE

Abstract
Predicting the spatial variability of grain yield is of crucial importance for site-specific management (SSM) because it allows for testing of management prescriptions and for correct assessment of agronomic and economic outcomes. One common limitation of crop simulation model use in SSM is the need for accurate values of many inputs from numerous sites in afield. Optimization can be of great help in the estimation of parameters using more easily measured variables such as yield. We have used simulated annealing and compared parameter estimates and yield predictions resulting from the use of two distinct objective function variables: grain yield and soil-water content. Estimating site-specific soil parameters from grain yield measurements led to acceptable errors in grain yield estimates. However soil-water was not accurately predicted, which made the strategy unreliable. The errors in soil-water were particularly high in the bottom soil layer In addition, most of the soil-water holding limits were not valid, especially for the lower limit and saturation. Estimating site-specific soil parameters from soil-water content measurements led to acceptable errors in grain yield and soil-water estimates. The estimated soil-water holding limits were valid with an exception of saturation for the intermediate soil layers.

2004

On subspace system identification algorithms implemented through sequences of modified householder algorithms

Authors
Delgado, CJM; dos Santos, PL;

Publication
MSV'04 & AMCS'04, PROCEEDINGS

Abstract
In this paper we present two subspace identification methods implemented through sequences of modified Householder algorithm. The main idea was to show that subspace identification methods can be represented as sequences of least squares problems and implemented wing QR factorizations. Therefore, it is possible to develop iterative algorithms with most of the advantages of this kind of methods, and still improve the numerical efficiency, in order to deal with real-tme applications and minimize the computational burden.

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