Bicchi, A. and G. Canepa (1994). Optimal design of multivariate sensors. Meas. Sci. Technol. 5, 319-- 332.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....In particular, the reader may wish to This research was supported by Council for Scientific Research compare sensors allocations considered here and those obtained for DPS 1. eigenvalues and or parameter identification [9] 10] 16] 20] 18] 19] 2. state estimation [11] 5] [1]. The main difference between this paper and the earlier approaches is in the goal of sensors allocation, which in turn, influences their optimal positions. We remark that also choice of moving sensors trajectories have been considered in [12] 13] 14] 21] 22] 2] 23] while in [7] ....

Bicchi A. and Canepa G. "Optimal design of multivariate sensors.". Meas. Sci. Technol., 5:319--322, 1994.

....quasistatic and in full dynamic case, is dependent on the placement of the sensing device (the strain gauges) on the mechanical structure. In this paper some criteria for the selection of the optimal sensor placement are proposed, motivated from general consideration on multivariate sensor design (Bicchi and Canepa, 1994). Moreover, it is shown, by means of experimental results, how the algorithm introduced in (Bicchi et al. 1997) can produce effective estimates of the applied force when the quasi static approximation is not respected. The analysis carried out in the rest of the paper specializes to the case of ....

....literature, as for instance those in (Sain and Massey, 1969) Silverman, 1969) Moylan, 1977) Tan and Vandewalle, 1988) to name a few. However, for the aim of this paper the test on matrix M has been chosen since it plays the role of the measurement matrix for dynamic system in equation (6) (Bicchi and Canepa, 1994). For further details on this point the reader is referred to the proof of the above proposition as given in (Sain and Massey, 1969) It ensues that the knowledge of matrix M is relevant for the analysis of the system invertibility as pointed out in the following remark. Remark 1 Matrix M gives ....

Bicchi, A. and G. Canepa (1994). Optimal design of multivariate sensors. Meas. Sci. Technol. 5, 319-- 332.

....or in the full dynamic case, is dependent on the placement of the sensing device (the strain gauges) on the mechanical structure. Certain placements can be more convenient than others, in order to retrieve the force. A general setting for the optimal design of multivariate sensors is described in (Bicchi and Canepa, 1994), and its application to the specific case of quasistatic force torque sensors is illustrated in (Bicchi, 1992) The case of optimal design of force torque sensors in the dynamic situation is much less explored, at least in the robotic literature. The objective of this paper is to investigate the ....

....is invertible. Several other methods have been proposed in more recent years ( Sain and Massey, 1969) Silverman, 1969) Moylan, 1977) Tan and Vandewalle, 1988) to name a few) However, it is important to remark that matrix M plays the role of the measurement matrix of equation (1) in (Bicchi and Canepa, 1994) (see the demonstration of the above theorem as given in (Sain and Massey, 1969) for more details on this point) Matrix M gives information on the invertibility of the system, and on the properties of the inversion result, independently from the numerical algorithm that will be actually used. ....

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Bicchi, A. and G. Canepa (1994). Optimal design of multivariate sensors. Meas. Sci. Technol. 5, 319--332.

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