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The development of autonomous unmanned aerial vehicles (UAVs) is of high interest to many governmental and military organizations around the world. An essential aspect of UAV autonomy is the ability for automatic path planning. In this paper, we use the genetic algorithm (GA) and the particle swarm optimization algorithm (PSO) to cope with the complexity of(More)
– In this paper the design and development of an intelligent controller based on artificial neural networks (ANN) on a Field Programmable Gate Array (FPGA), for a four-rotor helicopter to be capable of achieving vertical take off and to be able to sustain a specified attitude, is presented. To overcome challenges due to the complexities of creating a Neural(More)
Recently, the combination of sliding mode and fuzzy logic techniques has emerged as a promising methodology for dealing with nonlinear, uncertain, dynamical systems. In this paper, a sliding mode control algorithm combined with a fuzzy control scheme is developed for the trajectory control of a command guidance system. The acceleration command input is(More)
The paper presents a new and general method for the design of an unknown input observer for single input single output time-invariant minimum phase linear systems. The proposed method is applicable to systems of any relative degree. In the case of systems with a relative degree of one, the observer reduces to those proposed in the literature. Since some(More)
This paper proposes an innovative approach for the design of a nonlinear controller to stabilize an autonomous mobile robot. The design approach combines a nonlinear control design method with a root-finding algorithm for nonlinear algebraic equations. For the design, the robot model is divided into two parts: a state space model with intermediate control(More)