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Big cities and growing industrial areas bring high risk of different kinds of pollutions which would implicate to the quality of life of the society. Discovering and monitoring of polluted areas using autonomous mobile robots is nowadays a frequently considered solution concerning both environmental and human safety problems. Being part of a distributed control system, such robots can help to improve...
A new approach using gestures and visual computing techniques to control unmanned aerial vehicles is presented. The goal is to control automatically and in semi-autonomous mode the flight of a quad-rotor rotorcraft in indoor environments characterized with the absence of possibility to receive GPS data. Human operator can control the implementation of various maneuvers during the flight of the rotorcraft...
A novel variable-structure-systems-based approach to neuro-adaptive feedback control of systems with uncertain dynamics is proposed. An inner sliding motion is established in terms of the controller parameters. The outer sliding motion is set up on the system under control, the state tracking error vector being driven towards the origin of the phase space. The equivalence between the two sliding motions...
The interest into the unmanned aerial vehicles (UAVs) has largely increased recently. With the advances in technologies it has become possible to test efficiently and cost-effectively different autonomous flight control concepts using small-scale aircrafts. In this paper the stabilizing control problem of quad-rotor rotorcraft using multiple sliding surface (MSS) controllers has been investigated...
Cerebellar model articulation controller (CMAC) networks have been widely applied to problems involving modeling and control of complex dynamical systems because of their computational simplicity, fast learning and good generalization capability. The integration of fuzzy logic systems and CMAC networks into fuzzy CMAC structures can help to improve their function approximation accuracy in terms of...
An incrementally tuned interval type-2 Takagi-Sugeno-Kang (TSK) fuzzy neural network implementing fuzzy if-then rule base with first order output functions is proposed for compensation of friction and disturbance effects during the trajectory tracking control of rigid robot manipulators. Friction and disturbances have an important influence on the robot manipulator dynamics. They are highly nonlinear...
A neuro-fuzzy adaptive control approach for nonlinear dynamical systems, coupled with unknown dynamics, modeling errors, and various sorts of disturbances, is proposed and used to design a wheel slip regulating controller. The implemented control structure consists of a conventional controller and a neuro-fuzzy network-based feedback controller. The former is provided both to guarantee global asymptotic...
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