This paper proposes a Hardware-in-the-Loop sim-ulation (HiLs) tested via square Helmholtz coils as a relative magnetic field generator. In technical terms, the HiLs is an indispensable tool for engineering design duri...
This paper proposes a Hardware-in-the-Loop sim-ulation (HiLs) tested via square Helmholtz coils as a relative magnetic field generator. In technical terms, the HiLs is an indispensable tool for engineering design during rapid proto-typing of attitude determination and control algorithms for the turning parameters that control the attitude of the satellite, since most of the satellite's mission relies on its attitude, making this system one of the most essential to the satellite's operation. More-over, performing controlled experiments with the parameters for developing adaptive control algorithms improves the overall efficiency of the satellite's kinematic system. The conceptual design of a proposed system architecture can be composed of the electrical currents of 2.4-meter square Helmholtz coils produced by a low-level microcontroller equipped with a DC-motor driver by a pulse-width modulation (PWM) signal through real-time connection to an orbit propagator using a high-level computer. This research focuses on the attitude dynamic of satellites through the interaction between the Earth's magnetic field (EMF) and the magnetotorque in the satellite. To apply this phenomenon, the intensity and the direction of the magnetic field must be identified through Biot-Savart's law. Along with the EMF, the reference position is calculated using the standard general perturbations satellite orbit model (SGP4), and the intensity is modeled based on coefficients from the 13 th edition of the International Geo-magnetic Reference Field (IGRF). Therefore, this paper presents a detailed development of a HiLs testbed for distributed attitude determination and controlsystems (hardware and software co-design, protocol, and control theory). Furthermore, it discusses a classic cooperative control case for the output of magnetic field intensity and direction, which was undertaken to explain the integrated simulation process and validate the effectiveness of the co-simulation tested to be
For a vehicle moving in an n-dimensional Euclidean space, we present a construction of a hybrid feedback that guarantees both global asymptotic stabilization of a reference position and avoidance of an obstacle corres...
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We consider the problem of designing robust state-feedback controllers for discrete-time linear time-invariant systems, based directly on measured data. The proposed design procedures require no model knowledge, but o...
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ISBN:
(数字)9781538682661
ISBN:
(纸本)9781538682678
We consider the problem of designing robust state-feedback controllers for discrete-time linear time-invariant systems, based directly on measured data. The proposed design procedures require no model knowledge, but only a single open-loop data trajectory, which may be affected by noise. First, a data-driven characterization of the uncertain class of closed-loop matrices under state-feedback is derived. By considering this parametrization in the robust control framework, we design data-driven state-feedback gains with guarantees on stability and performance, containing, e.g., the H_ ∞-control problem as a special case. Further, we show how the proposed framework can be extended to take partial model knowledge into account. The validity of the proposed approach is illustrated via a numerical example.
A benchmark for multi-UAV task assignment is presented in order to evaluate different algorithms. An extended Team Orienteering Problem is modeled for a kind of multi-UAV task assignment problem. Three intelligent alg...
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作者:
Grzedzinski, KacperTrodden, PaulRolls-Royce Control
Monitoring and Systems Engineering University Technology Centre Department of Automatic Control and Systems Engineering University of Sheffield United Kingdom
The dual-control problem of simultaneously regulating a plant and identifying its dynamics is addressed in a linear model predictive control (MPC) framework. We propose and study an approach where two optimal control ...
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An optimization-based method for improving the productivity of precision machine tools is proposed, where the reference path is computed in local coordinates, and information about the machine tool performance is lear...
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Individual Pitch control (IPC) is a well-known and, in normal operating conditions, effective approach to alleviate blade loads in wind turbines. However, in the case of a Pitch Actuator Stuck (PAS) type of fault, con...
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ISBN:
(数字)9781538682661
ISBN:
(纸本)9781538682678
Individual Pitch control (IPC) is a well-known and, in normal operating conditions, effective approach to alleviate blade loads in wind turbines. However, in the case of a Pitch Actuator Stuck (PAS) type of fault, conventional IPC is not beneficial since its action is disturbed by the failed pitch actuator. In this paper, a Subspace Predictive Repetitive control (SPRC)-based IPC is proposed to implement a Fault Tolerant control (FTC) strategy for Floating Offshore Wind Turbines (FOWTs) affected by PAS faults. In particular, an online subspace identification step is first carried out to obtain a linearized model of the FOWT system in faulty condition. The identified FOWT system is then used to develop a repetitive control law. Consequently, the adaptive repetitive control solution is implemented on the remaining healthy pitch actuators, in order to accommodate the PAS fault. Results show the developed SPRC approach allows to accommodate the PAS faults, achieving a considerable reduction of the blade loads in combination with lower pitch activities for the healthy actuators. This allows to continue power production and postpone maintenance operations, thus reducing the O&M costs.
automatic Guided Vehicle (AGV) semantic attack is now becoming an important research topic in digital workshops. Unfortunately, the conventional attack detections could trigger the wrong attack detection alarms, becau...
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ISBN:
(纸本)9781728119496
automatic Guided Vehicle (AGV) semantic attack is now becoming an important research topic in digital workshops. Unfortunately, the conventional attack detections could trigger the wrong attack detection alarms, because of the unexpected wireless radio frequency interference. This paper investigates a new method for AGV semantic attack detection based on Hidden Markov Model (HMM). Our method is able to discriminate the typical wireless retransmission in presence of environment interference or in the context of AGV semantic attack by comparing the hidden state transition probability with the predefined threshold. Our model has been evaluated on our developed platform. The extensive experimental results and analysis prove the effectiveness of our method.
In threshold-based anomaly detection, we want to tune the threshold of a detector to achieve an acceptable false alarm rate. However, tuning the threshold is often a non-trivial task due to unknown detector output dis...
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An ancient and counterintuitive phenomenon known as the Mpemba effect showcases the critical role of initial conditions in relaxation processes. How to realize and utilize this effect for speeding up relaxation is an ...
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