Typical autonomous driving systems are a combination of machine learning algorithms (often involving neural networks) and classical feedback controllers. Whilst significant progress has been made in recent years on th...
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Fault monitoring and diagnostics are important to ensure reliability of electric motors. Efficient algorithms for fault detection improve reliability, yet development of cost-effective and reliable classifiers for dia...
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ISBN:
(数字)9781665464543
ISBN:
(纸本)9781665464550
Fault monitoring and diagnostics are important to ensure reliability of electric motors. Efficient algorithms for fault detection improve reliability, yet development of cost-effective and reliable classifiers for diagnostics of equipment is challenging, in particular due to unavailability of well-balanced datasets, with signals from properly functioning equipment and those from faulty equipment. Thus, we propose to use a Bayesian neural network to detect and classify faults in electric motors, given its efficacy with imbalanced training data. The performance of the proposed network is demonstrated on real life signals, and a robustness analysis of the proposed solution is provided.
Fault monitoring and diagnostics are important to ensure reliability of electric motors. Efficient algorithms for fault detection improve reliability, yet development of cost-effective and reliable classifiers for dia...
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This paper addresses model predictive control of a class of linear systems subject to additive stochastic disturbances and constraints. The underlying stochastic optimal control problem combines inverse cumulative dis...
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This paper addresses model predictive control of a class of linear systems subject to additive stochastic disturbances and constraints. The underlying stochastic optimal control problem combines inverse cumulative distribution functions with ellipsoid-in-polyhedron formulations to reduce the conservatism induced by constraint satisfaction. By use of terminal constraints and time-varying weights within the cost functional, the presented control scheme satisfies criteria for mean-square stability and can be adapted to reference-tracking problems for arbitrary reference signals.
The present paper introduces a comparative analysis of the management of a stochastic optimization problem using both a risk deterministic approach and a support vector machine strategy. This optimization problem is f...
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Robotics and haptic systems have allowed new and diverse applications in the field of medicine, such as assisted surgery and teleoperation which have increasingly stringent requirements for accuracy, convergence, and ...
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ISBN:
(数字)9798350393965
ISBN:
(纸本)9798350393972
Robotics and haptic systems have allowed new and diverse applications in the field of medicine, such as assisted surgery and teleoperation which have increasingly stringent requirements for accuracy, convergence, and low computational consumption. In this paper an adaptive PID control law (Proportional Integral Derivative controller, PID), of indirect architecture is presented for movement paths in a haptic system of open chain, where the identification of the plant is through a quaternionic wavelet neural network (Quaternion Wavelet Neural Network, QWNN) for tune the PID values, this allows the optimal movement into the regions of the workspace.
In this work, we present the modeling of the dynamics of a robot manipulator using the Newton-Euler algorithm in the conformal algebra framework. The modeling of the dynamics of robot manipulators is currently done us...
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ISBN:
(数字)9798350362343
ISBN:
(纸本)9798350362350
In this work, we present the modeling of the dynamics of a robot manipulator using the Newton-Euler algorithm in the conformal algebra framework. The modeling of the dynamics of robot manipulators is currently done using the Euler-Lagrange formulation which is a batch type of computation. In contrast, in this paper, we propose a recursive algorithm for the modeling of the dynamics of robot manipulators using the Newton-Euler algorithm in the conformal geometric algebra framework.
The protection and controlsystem in substations has undergone significant evolution since the era of hardwired systems. In recent years, the increasing trend of digital transformation (DX) across various fields, incl...
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This paper presents the design of a Proportional-Integral Passivity-based controller (PI-PBC) for a current source inverter feeding a resistive load. Thanks to the definition of a new passive output, the closed-loop s...
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This paper presents the design of a Proportional-Integral Passivity-based controller (PI-PBC) for a current source inverter feeding a resistive load. Thanks to the definition of a new passive output, the closed-loop system is shown to be globally asymptotically stable. This result solves the internal stability problem reported for these power converters. To robustify the control algorithm, the paper also includes the design of a parameter estimation scheme for the parasitic resistances and the load conductance. Numerical simulations are carried out to validate the control algorithm. The simulation stage compares the behaviour using the averaged model of the power converter and a more realistic switching model, including the three-phase implementation.
A two-channel Sallen-Key low-pass filter on three non-inverting amplifiers is studied, which has the property of unrelated digital set of the upper cut-off frequency at constant index of the transmission coefficient i...
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