Design of Intelligent Controllers for Double Inverted Pendulum

In this paper, first a fuzzy controller is proposed for systems comprising two inverted pendulums placed in the same plane, where one pendulum moves along the X-axis and the other moves along the Y-axis; rules of a Fuzzy-Mamdani controller is improved by considering the behavior of an operator and a the developed expert system and by trial and error in the observation of the system’s behavior. Simulation results obtained in MATLAB are proposed and then two other intelligent methods are presented. In the second proposed method, a TSK controller is designed with Anfis training approach and its simulation results are presented. Finally, a non-fuzzy controller (linearization feedback) is used as the supervisor fuzzy controller and the simulation results are presented. At last, performance of the three controllers is compared and the results are demonstrated

Giant Gravitons with NSNS B field

We study the motion of a D(8-p)-brane probe in the background created by a stack of non-threshold (D(p-2), Dp) bound states for $2\le p\le 6$. The brane probe and the branes of the background have two common directions. We show that for a particular value of the worldvolume gauge field there exist configurations of the probe brane which behave as massless particles and can be interpreted as gravitons blown up into a fuzzy sphere and a noncommutative plane. We check this behaviour by studying the motion and energy of the brane and by determining how supersymmetry is broken by the probe as it moves under the action of the background.Comment: 24 pages, LaTe

Cross-layer Balanced and Reliable Opportunistic Routing Algorithm for Mobile Ad Hoc Networks

For improving the efficiency and the reliability of the opportunistic routing algorithm, in this paper, we propose the cross-layer and reliable opportunistic routing algorithm (CBRT) for Mobile Ad Hoc Networks, which introduces the improved efficiency fuzzy logic and humoral regulation inspired topology control into the opportunistic routing algorithm. In CBRT, the inputs of the fuzzy logic system are the relative variance (rv) of the metrics rather than the values of the metrics, which reduces the number of fuzzy rules dramatically. Moreover, the number of fuzzy rules does not increase when the number of inputs increases. For reducing the control cost, in CBRT, the node degree in the candidate relays set is a range rather than a constant number. The nodes are divided into different categories based on their node degree in the candidate relays set. The nodes adjust their transmission range based on which categories that they belong to. Additionally, for investigating the effection of the node mobility on routing performance, we propose a link lifetime prediction algorithm which takes both the moving speed and moving direction into account. In CBRT, the source node determines the relaying priorities of the relaying nodes based on their utilities. The relaying node which the utility is large will have high priority to relay the data packet. By these innovations, the network performance in CBRT is much better than that in ExOR, however, the computation complexity is not increased in CBRT.Comment: 14 pages, 17 figures, 31 formulas, IEEE Sensors Journal, 201