This paper focuses on applying the two-level optimal estimator to the problem of attitude determination using GPS. The derivations are based on the criteria of not only a traditional one using a set of positive scalar...
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This paper focuses on applying the two-level optimal estimator to the problem of attitude determination using GPS. The derivations are based on the criteria of not only a traditional one using a set of positive scalars as the weighted factors, but also one employing the inverse of covariance of measurements as the weighted matrix. It is shown that the configuration to formulate Wahba's problem as the criterion of the second level is numerically efficient. The solution of the two-level optimal estimator turns out to be optimal under the so-called balanced condition. The experiment results show the efficacy of the two-level optimal estimation method.
Precise underwater navigation is crucial in a number of marine applications. Navigation of most autonomous underwater vehicles (AUVs) is based on inertial navigation. Such navigation systems drift off with time and ex...
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Precise underwater navigation is crucial in a number of marine applications. Navigation of most autonomous underwater vehicles (AUVs) is based on inertial navigation. Such navigation systems drift off with time and external fixes are needed. This paper concentrates on terrain-based navigation, where position fixes are found by comparing measurements with a prior map. Nonlinear Bayesian methods like point mass and particle filters are often used for this problem. Such methods are often computationally demanding. The sigma point Kalman filter (or unscented Kalman filter) is a nonlinear filter that does not resort to local linearizations, representing the probability densities using a few deterministically chosen sigma points. The sigma point Kalman filter is not as computationally demanding as the aforementioned methods, and using real AUV data, the accuracies obtained are comparable to those of the point mass and particle filters.
This paper describes a multi-scale stochastic model defined on a multiwavelet structure. Previously such stochastic models are based either on a single or multiple binary tree as well as on an ordinary wavelet structu...
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This paper describes a multi-scale stochastic model defined on a multiwavelet structure. Previously such stochastic models are based either on a single or multiple binary tree as well as on an ordinary wavelet structure. The proposed model lies on a tree structure consists of several sets of data coefficients as a result of multiwavelet transformation. Each data sets is linked only through initial data set at root node and conditionally independent given this initial state. Multiwavelet possesses several interesting properties like simultaneously short support, symmetry and orthogonality. The effect of these properties on the proposed model is shown through simulation of smoothing process of a certain fractal signal. It will be demonstrated that several improvements over previously announced results are obtained.
This paper discusses the applicability of monitoring systems for improving ship control. After introducing some critical issues in the area of ship motion control an analysis is presented concerning the choice of diff...
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This paper discusses the applicability of monitoring systems for improving ship control. After introducing some critical issues in the area of ship motion control an analysis is presented concerning the choice of different architecture and algorithms with particular reference to the applicability of new methods capable to implement robustness and adaptivity features and to the software requirements for building up advanced ship monitoring and control systems. An examples of ship monitoring and control system actually under development at the Department of Information and Systems of the University of Pavia are presented
Dynamic traffic flow development on a road section without off- and on-ramps is determined by time dependent boundary conditions and initial density and velocity distributions. In cases of application, usually, these ...
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Dynamic traffic flow development on a road section without off- and on-ramps is determined by time dependent boundary conditions and initial density and velocity distributions. In cases of application, usually, these initial distributions are not known. Based on the works by Kerner et al . (1993a, b, 1994), a measurement-based traffic flow simulation for the determination of section related traffic data was developed (Kronjäger et al. 1995). Starting with initial conditions obtained by interpolating the measured traffic data, using finite difference methods and a tailored least-square method, the model allows the calculation of the density and velocity profiles as a function of time and space. The study of this approach in different field tests has shown, that after a certain time the simulated traffic flow quantities comply well with experimental data.
Teleoperation and intervention robotics involve more and more mobile or movable robots which must get new references to be at work. Two cases are presented, in which references are measured by contact, either with the...
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Teleoperation and intervention robotics involve more and more mobile or movable robots which must get new references to be at work. Two cases are presented, in which references are measured by contact, either with the environment (medical robot working at a fixed place with tactile references recording), or with other robots (cooperation with contacts like a “handshaking”), and information is processed in order to obtain transformation matrix between robots and/or environment coordinates for either work in a new place, or move an object with several robots together or one after another.
This paper presents a constructive solution to the design problem of observers to estimate both system state and unknown inputs. We propose an equivalent system, which is free of unknown inputs to derive the observer....
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This paper presents a constructive solution to the design problem of observers to estimate both system state and unknown inputs. We propose an equivalent system, which is free of unknown inputs to derive the observer. Based on the equivalent system description, one can design an observer to estimate both the system state and the unknown inputs simultaneously. Experimental results for a tank system demonstrate the applicability of the proposed methodologies.
This report deals with the detection and diagnosis of faults (FDD) when they develop in different parts of a wastewater treatment plant, situated in Manresa, Spain. When a fault occurs estimates of parameters in a non...
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This report deals with the detection and diagnosis of faults (FDD) when they develop in different parts of a wastewater treatment plant, situated in Manresa, Spain. When a fault occurs estimates of parameters in a non-linear mathematical model of the plant change. Some methods for detection and tracking the values of different parameters are proposed, where only large parameter changes are considered in this work. The methods have a common structure with three basic elements: a basic identification algorithm, a detector of the parameter changes and an adaptive procedure for improving the tracking capability of the identifier. A set of simulation experiments are presented in order to compare them.
This paper presents an indirect adaptive control scheme for nominally stabilizable, but possible non-controllable, continuous and time-varying systems with unmodelled dynamics. The control objective is the adaptive st...
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This paper presents an indirect adaptive control scheme for nominally stabilizable, but possible non-controllable, continuous and time-varying systems with unmodelled dynamics. The control objective is the adaptive stabilization of the system. The scheme includes several estimation algorithms and a supervisor which selects the appropriate estimator keeping it in operation during at least a minimum residence time.
A key bottleneck in the production of pharmaceuticals is in the formation of crystals from solution. The control of the crystal size distribution can be critically important for efficient downstream operations such as...
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A key bottleneck in the production of pharmaceuticals is in the formation of crystals from solution. The control of the crystal size distribution can be critically important for efficient downstream operations such as filtration and drying, and product effectiveness (e.g., bioavailability, tablet stability). This paper provides an overview of recent developments in the identification of pharmaceutical crystallization processes. This includes descriptions of recent activities in sensor technologies, model identification, experimental design, and robustness analysis of pharmaceutical crystallization processes.
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