A non-linear control to regulate the speed and the supply of air flow in an internal combustion Diesel engine with exhaust gas recirculation system is proposed. The control scheme uses a static feedback of the states ...
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A non-linear control to regulate the speed and the supply of air flow in an internal combustion Diesel engine with exhaust gas recirculation system is proposed. The control scheme uses a static feedback of the states to linearize the motor-turbocharger system avoiding linearization by dynamic state feedback. The control scheme used is complemented by an estimator for the load torque of the engine based on the Immersion and Invariance technique. The stability analysis allows to conclude asymptotic stability when the control scheme uses the estimated load torque. Through a series of numerical simulations the properties of the proposed control scheme are evaluated.
In this paper, the design of an output predictor for systems with scarce irregular measurements with time varying delays is addressed. A model based predictor that takes into account the past measured outputs is used....
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In this paper, the design of an output predictor for systems with scarce irregular measurements with time varying delays is addressed. A model based predictor that takes into account the past measured outputs is used. Robustness of the predictor to the time varying delays and data availability as well as disturbance attenuation is dealt with via H-infinity performance. A design strategy is proposed based on the available disturbances information. (C) 2006 Elsevier Ltd. All rights reserved.
This paper presents a self-sensory robot arm to two basic sensing problems in control of flexible manipulators: detection of the position and orientation variations due to structural deformation and detection of the c...
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This paper presents a self-sensory robot arm to two basic sensing problems in control of flexible manipulators: detection of the position and orientation variations due to structural deformation and detection of the contact force of end-effector when manipulator interacts with its environment. Taking advantage of structural flexibility, a flexible robot arm with strain gauges distributed on it acts as a sensing unit. The position and orientation of flexible arm are expressed as a function of curvature of the arm. An interpolation technique gives this continuous curvature function from a finite set of measurements made with strain gauges. A relation between strain measurements and endpoint force of flexible arm is developed and the contact force of end-effector is then determined using a force propagation algorithm. The proposed technique and algorithm were implemented and evaluated in a laboratorial flexible arm. Experimental validations using a vision system and two force sensors have shown that the self-sensory flexible arm can provide accurate endpoint position and force in both static and dynamic loading situations. (C) 2003 Elsevier Science Ltd. All rights reserved.
This paper presents an adaptive regulation scheme for a class of ordinary nonlinear nonautonomous second-order differential equations which includes as particular cases a number of particular differential equations wh...
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This paper presents an adaptive regulation scheme for a class of ordinary nonlinear nonautonomous second-order differential equations which includes as particular cases a number of particular differential equations which occur in applications. The unforced reference model is proposed to be a stable differential parametrization within the general class dealt with. Therefore, some sufficient Lyapunov's stability conditions for such a class are previously investigated which can be used, in particular, to set an appropriate reference model. The resulting closed-loop adaptive scheme is proved to be stable and it involves a parameter estimation scheme of least-squares type which is proved to possess all suitable properties in terms of estimates boundedness and asymptotic convergence of the estimates to finite limits as well as time-integrability of the squared adaptation error.
The model of estimation algorithms designed for pattern recognition is considered. A partial order for a class of systems of support sets that admit an efficient implementation is defined and investigated. It is prove...
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The model of estimation algorithms designed for pattern recognition is considered. A partial order for a class of systems of support sets that admit an efficient implementation is defined and investigated. It is proved that the problem of finding a counterexample for the efficiency property with additional constraints is NP-complete.
Uncertainty and bias of RMS measurement of digitally non-coherent sampled signal is dependent on the algorithm used. This paper presents the new Averaging two subsets method for RMS value bias correction of non-cohere...
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Uncertainty and bias of RMS measurement of digitally non-coherent sampled signal is dependent on the algorithm used. This paper presents the new Averaging two subsets method for RMS value bias correction of non-coherent sampled signal. Methods for estimating RMS values in the time domain are also compared.
This paper studies stiffness and stability properties of Extended Cubature and Unscented Kalman Filters applied to continuous-discrete stochastic systems with stiff dynamic behavior. The main part of these methods rel...
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This paper studies stiffness and stability properties of Extended Cubature and Unscented Kalman Filters applied to continuous-discrete stochastic systems with stiff dynamic behavior. The main part of these methods relies on numerical integration of Moment Differential Equations (MDEs). Our focus is to understand how the stiffness of MDEs influences performance of the filters. The proposed linear stability analysis shows that the MDEs that have arisen within these methods can enlarge the stiffness of continuous-time stochastic model and, hence, require solvers with advanced stability properties for their effective and accurate treatment. Besides, the proposed nonlinear stability analysis proves that such MDEs may become extremely unstable in simulation intervals. The latter raises the uncertainty of state estimation and results in two interesting implications: (i) the lower-order Extended Kalman Filter outperforms the higher-order Cubature and Unscented Kalman Filters in the accuracy of state estimation of stochastic systems with unstable MDE behavior;(ii) the methods under exploration fail when the stiffness is large enough. Our theoretical consideration is supported by numerical tests with filters based on the MATLAB code ode15s, which is a benchmark solver for stiff ODEs. These are examined on linear and nonlinear stiff continuous-time stochastic models. (C) 2018 Elsevier Ltd. All rights reserved.
Maximum likelihood algorithms for estimating parameters of a correlation matrix of clutter for adaptive allocation of signals of moving targets in multifrequency coherent pulse radar-tracking systems are synthesized. ...
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Maximum likelihood algorithms for estimating parameters of a correlation matrix of clutter for adaptive allocation of signals of moving targets in multifrequency coherent pulse radar-tracking systems are synthesized. Schematic diagrams of the corresponding measuring instruments are provided.
We develop novel algorithms based on interval analysis with theoretical guarantees, to augment the accuracy of cell phone geolocation by taking advantage of local variations of magnetic intensity. Thus, the sources of...
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We develop novel algorithms based on interval analysis with theoretical guarantees, to augment the accuracy of cell phone geolocation by taking advantage of local variations of magnetic intensity. Thus, the sources of disturbances to magnetometer readings caused indoors are effectively used as beacons for localization. We construct a magnetic intensity map for an indoor environment by collecting magnetic field data over each floor tile. We then test the algorithms without position initialization and obtain indoor geolocation to within 2 m while slowly walking over a complex path of 80 m. The geolocation errors are smaller in the vicinity of large magnetic disturbances. Finally, we fuse the magnetometer measurement with inertial measurements on the cell phone to yield even smaller geolocation errors of under 50 cm for a moving user. Our theoretical results connect geolocation accuracy to combinations of sensor and map properties. (C) 2014 Elsevier Ltd. All rights reserved.
Simulation of complex (bio)chemical reactions plays an important role in a process kinetics characterisation. However, detailed kinetic modelling is a difficult task because the model has to reflect the process comple...
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Simulation of complex (bio)chemical reactions plays an important role in a process kinetics characterisation. However, detailed kinetic modelling is a difficult task because the model has to reflect the process complexity under variate operating conditions, starting from a limited number of observed variables, (non-)conventional data recorded with a limited sampling frequency, and often with a low reproducibility. Extensive investigations can lead to structured models of complexity depending on the utilisation scope. To overcome weak results, the identification problem must be well formulated, data consistent, numerical estimation appropriate and effective, and the estimate quality analysis adequate. While statistical estimation theory has been extensively developed in terms of objective function choice and solution analysis, numerical algorithm application to (bio)chemical kinetic systems presents particularities and difficulties. The present paper aims to review the main steps and trends in solving the kinetic model identification problem. Rules for a suitable problem formulation vs. modelling objectives, advanced numerical algorithms for obtaining a reliable solution, and an estimate of suitable analysis are shortly summarised.
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