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Download Control, Mechatronics and Automation Technology: Proceedings by Dawei Zheng PDF

By Dawei Zheng

This lawsuits quantity comprises chosen papers offered on the 2014 foreign convention on keep an eye on, Mechatronics and Automation expertise (ICCMAT 2014), held July 24-25, 2014 in Beijing, China. the target of ICCMAT 2014 is to supply a platform for researchers, engineers, academicians in addition to business pros from around the globe to offer their examine effects and improvement actions up to the mark, Mechatronics and Automation know-how.

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Extra resources for Control, Mechatronics and Automation Technology: Proceedings of the International Conference on Control, Mechatronics and Automation Technology ... 2014, Beijing, China

Example text

The basic domain of input and output is shown in Table 1. The number of the fuzzy sets is 7, and we name them as NB, NM, NS, ZO, PS, PM, PB. In this paper, we make 12573 samples to overlap this learning domain. The initial center and width settings of membership function are shown in Table 2. 2 Figure 4. Different numbers of iterations based on different η. From the simulation, we can see that the greater η is, the faster E is converging. But the study speed is still too slow, which can’t meet the requirement.

RLF and DS ranks second and third, respectively, reducing the phase lag notably. 38 Figure 9. Pilot-aircraft closed loop model. Figure 7. Open loop phase lag compensation. Figure 10. Aircraft response to Pulse Tracking Task with/without filters, Case C. Figure 8. Bias removal comparison. DASA overlaps the conventional output, showing no phase compensation. The focus of the next task is to look at the bias removal. If the input is not symmetric, a state error or a bias occurs, which degrades handling quality [4].

Open loop phase lag compensation. Figure 10. Aircraft response to Pulse Tracking Task with/without filters, Case C. Figure 8. Bias removal comparison. DASA overlaps the conventional output, showing no phase compensation. The focus of the next task is to look at the bias removal. If the input is not symmetric, a state error or a bias occurs, which degrades handling quality [4]. Figure 8 examines every filter’s ability to remove the bias after an asymmetric input. All of the filters can remove the bias successfully except DS.

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