Wireless event-triggered controller for a 3D tower crane lab process

Altaf, Faisal; Araújo, José; Hernández, Aitor; Johansson, Karl Henrik

doi:10.1109/med.2011.5983179

Cited by 6 publications

(3 citation statements)

References 14 publications

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“…In [3], the authors present an event-triggered controller and they test their controller along with the traditional periodic controller on a physical system. They compare the performance of the two controllers with and without introducing network delay and packet loss.…”

Section: Applications Of Event-based Controlmentioning

confidence: 99%

Event-based control as a cloud service

Abdelaal

Hegazy

Hefeeda

2017

2017 American Control Conference (ACC)

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Event-based control has gained significant interest from the research community in recent years because it allows better resource utilization in networked control systems. In this thesis, we propose an architecture for offering event-based control as a service from the cloud, which not only improves resource utilization but also reduces the cost and setup time of large-scale industrial automation systems. Providing event-based control from the cloud, however, poses multiple research challenges. We address two of the main challenges, which are mitigating long and variable network delays and handling controller failures introduced because of moving the controller far away from the plant. We propose novel methods to solve the delay and failure problems and we show that these methods maintain the stability and performance of the control system. We implemented the proposed methods and deployed them on the Amazon cloud. Our results show that our delay mitigation technique can handle large communication delays up to several seconds with practically zero effect on the main performance metrics of the system. Moreover, the proposed fault tolerance approach can transparently handle controller failures even if the controlled system is thousands of miles away from its cloud controllers.

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Section: Applications Of Event-based Controlmentioning

confidence: 99%

Event-based control as a cloud service

Abdelaal

Hegazy

Hefeeda

2017

2017 American Control Conference (ACC)

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“…The crane’s parameters used in the model equations are given in Table 2. Altaf (2010) estimated the parameters using the prediction error method. Other parameters such as friction coefficients and the inertia are estimated using an offline identification parameter estimation tool in MATLAB via the sum square method based on the structure of the model.…”

Section: Resultsmentioning

confidence: 99%

Robust integral sliding mode control of tower cranes

Aboserre

El-Badawy

2020

Journal of Vibration and Control

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In this study, integral sliding mode control is proposed for tower cranes to ensure precise tracking of the desired position while reducing the oscillations of the payload. The nonlinear robust controller is designed based on high fidelity nonlinear dynamical model, unlike the decoupled or linearized models used in the literature. The advantage of this approach is reducing the model uncertainties resulting in a lower control effort demand that would be required by the sliding mode controller. Moreover, the stability of the under-actuated tower crane system is analyzed using Lyapunov theory to guarantee the practical stability of error dynamics. Experimental results of the proposed control approach are compared with conventional sliding mode control to show its effectiveness and robustness against real system uncertainties.

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“…Specifically, the architecture of ADC-TDMA is similar to C-TDMA and consists of sensing task, X-slots, d c delay, and U-slot (see Figure 4b). In a S x j slot, the node N j evaluates the threshold of Equation (13). In the case of no threshold violation, the node N j skips the communication and returns to sleep mode until S u j .…”

Section: Adc-tdma and Padetcmentioning

confidence: 99%