A feedback based CRI approach to fuzzy reasoning

This paper aims at developing a voltage-based impedance model-reference controller using fuzzy uncertainty estimator for the robust control of electrically driven robot manipulators. The proposed control scheme not only utilizes a desired impedance as a reference model, but also provides the integrated control of position and force in the closed loop system. The robotic system receives the output of model-reference as a desired trajectory and thus the aim of the controller is to reduce the difference between the task-space desired trajectory and the desired impedance model. Furthermore, two control terms namely a robustifying term and a fuzzy uncertainty estimator are added in the structure of control design in order to improve the performance of the control system as well as to tackle uncertainty including un-modelled dynamics and external disturbances. Using stability analysis, we derive the adaptive mechanisms and also prove the boundedness of all system states. Finally, simulation results are included to verify the proposed control method.

Section: Impedance Designmentioning

confidence: 99%

mentioning

confidence: 99%

A model-reference impedance control of robot manipulators using an adaptive fuzzy uncertainty estimator

Nazmara¹,

Fateh²,

Ahmadi³

2018

“…As such, mission planning is one key to UAV swarm operation. Current mission planning methods for UAV swarms mainly focus on solutions to path planning problems [2][3][4] or reconnaissance mission planning problems [5][6][7] . These methods solve mission planning problems for UAV swarms effectively in some aspects but notably do not apply to combat mission planning problems, for two reasons.…”

Section: Introductionmentioning

confidence: 99%

Solving A Multi-objective Mission Planning Problem for UAV Swarms with An Improved NSGA-III Algorithm

Liu¹,

Wang²,

Li³

et al. 2018

Restricted communication in unmanned aerial vehicle (UAV) swarms means that configuration needs to vary dynamically with changing tasks. We propose a mission planning model that uses a motif, a grouping of related functions, as the basic task unit. The planning model automatically generates a mission planning scheme from a task priority execution order given as an input. The selection of the best scheme from among possible solutions is a multiobjective optimization problem with calculation complexity rapidly increasing with the number of tasks. To address this difficulty, we enhance the NSGA-III algorithm by adding adaptive genetic operators when generating the offspring population. We apply the improved NSGA-III algorithm to optimize mission planning schemes with changing task priority execution orders. We validated the feasibility and effectiveness of the improved algorithm via a case study.

“…These factors include the remaining energy of a node, network density and bandwidth available. This paper proposes a new algorithm for broadcasting strategy in which fuzzy logic concept [16][17][18][19][20][21] is used with node density, i.e. Number of neighbors, available bandwidth and remaining energy of node as input and broadcasting probability P of RREQ packets is calculated as an output.…”

Section: Co-published By Atlantis Press and Taylor And Francismentioning

confidence: 99%

Efficient Fuzzy Logic Based Probabilistic Broadcasting for Mobile Ad hoc Network

Kumar¹,

Mehfuz²

2016

In Mobile Ad hoc networks broadcasting is the one of the most important and crucial phenomenon. Broadcasting can be taken up in many ways and the simplest method of broadcasting is simple flooding which can significantly increase the overheads and can result in redundant messages which can further cause the Broadcasting Strom problem. In this paper, we propose an efficient fuzzy logic based probabilistic broadcasting for AODV protocol in order to reduce overheads. The fuzzy based logic criteria make decisions which are based on some of the important parameters affecting broadcasting like number of neighbors, bandwidth available and remaining energy. The simulation result shows that the proposed algorithm is efficient and reliable with respect to the consumed power, throughput, overhead, collision rate and it also maintains low normalized routing load as compared to AODV and other routing protocols proposed in the literature in which simple flooding or fixed probability broadcasting is used.