فهرست مطالب h. kharrati

This article addresses the problem of sliding mode control (SMC) for discrete-time delayed singular Markovian jump systems (MJSs) subject to parameter uncertainties and both of matched/mismatched disturbances. The transition probabilities of the Markov chain are considered to have partially unknown entries. Firstly, a sliding surface is proposed by taking the singular matrix into account, and hence the resultant dynamics of the sliding mode system becomes a full order delayed singular MJS. Secondly, the problem of bounded real lemma for the dynamics of the sliding mode system is investigated using the Lyapunov–Krasovskii functional. A delay-dependent solvability condition for the desired sliding surface is derived as linear matrix inequalities (LMIs), which guarantees that the dynamics of the sliding mode system to be robust stochastically admissible and satisfies the  performance. The slack matrix technique is utilized together with the delay partitioning approach to diminish the conservatism of the obtained condition. Thirdly, a sliding mode controller is synthesized to ensure that the sliding surface is reachable. Finally, two numerical examples are given to show the improved conservatism and the adequacy of the proposed design method.

In this paper guidance and control of UAVs has been discussed using autonomous path planning system to operate different missions under various conditions and with minimum human intervention. An autonomous system can be divided into path planning system and path following system. The path planning system is responsible for producing a flight path while the path following system generates proper commands to control and guide plane through the path. In this paper some waypoints has been considered in a hypothetical environment with obstacles and no fly zone regions and the optimal path is generated using genetic algorithm. First, the path will be refined to prevent from collusion, then in order to be a flyable path, we will smooth the path considering UAV’s dynamic constraints and finally the generated path is used as an input for UAV. Using BTT guidance method with nonlinear controllers have caused UAV to follow the reference path faster with lower deviation error from the path and all simulation results are shown.