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RISS 인기검색어
- 검색키워드
- 저자 : Auday Al‑Mayyahi (검색결과 3 건)
- 무료
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Design of a Stable an Intelligent Controller for a Quadruped Robot
Ammar A. Aldair,Auday Al‑Mayyahi,Weiji Wang 대한전기학회 2020 Journal of Electrical Engineering & Technology Vol.15 No.2
Quadruped robots have increasingly been used in complex terrains where barriers and gaps exist. In this paper, a four-legged robot with intelligent controllers is designed and simulated. The designed architecture comprises 12 servo motors, three per leg, to provide considerable fexibility in movement and turning. Proportional Integral Derivative (PID) controllers and Fuzzy controllers are proposed to control and stabilize the motion of the quadruped robot. An ant colony optimization algorithm has been utilized to tune the parameters of the PID controller and the Fuzzy controller. After obtaining the optimal values of both controllers, the entire architecture is implemented using the Multibody Simscape package in MATLAB which models multidomain physical systems. The simulation results are conducted in a 3-dimensional environment and they are demonstrated in three case studies; frstly, when the system is simulated without using a controller which leads to a collapse of the quadruped robot. Secondly, when the PID controller is combined with the system, better movement is obtained. However, the quadruped is unable to complete its path and collapses after a few meters. Thirdly, when the Fuzzy controller is integrated into the designed architecture, a signifcant improvement is observed in terms of minimizing elapsed time and improving the overall performance of the motion. The stability of the Fuzzy controller has been examined using Lyapunov criteria to validate its overall performance. Comparisons are conducted based on control eforts and travelled distances to demonstrate the suitability and efectiveness of Fuzzy controllers over PID controllers.
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Ammar A. Aldair,Auday Al‑Mayyahi,Abdulmuttalib T. Rashid 대한전기학회 2020 Journal of Electrical Engineering & Technology Vol.15 No.4
This article introduces a new control methodology to intelligently drive the motion of a mobile robot via given waypoints. A nonlinear model predictive controller (NMPC) is utilized to track the waypoints that are placed randomly at diferent positions in a given environment. Hence, various tracking paths can be generated based on locations of waypoints. Additionally, a Quadratic Bezier Curves algorithm has been applied for obstacle avoidance. It is combined with the NMPC via a switching mechanism. Hence, the transportation of the mobile robot will take the priority of avoiding obstructing obstacles if exist before moving forward to the next target waypoint. Single and multiple mobile robots have been simulated into several scenarios to investigate the performance of the developed control scheme.
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Baqir Nasser AbdulSamed,Ammar A. Aldair,Auday Al‑Mayyahi 대한전기학회 2020 Journal of Electrical Engineering & Technology Vol.15 No.2
This paper addresses the designing of a robust controller for an automatic landing, trajectory tracking and take-of missions of quadrotor unmanned aerial vehicle (QUAV). This has been investigated where the QUAV’s dynamic model involves nonlinearity, uncertainties, and coupling which makes the QUAV has a very complex system. The proposed controller can control both the position and orientation in addition to control the driving motors. For controlling the position, an appropriate control signal is generated for adjusting the altitude of the QUAV in a working space. To achieve this, three adaptive fuzzy controllers have been designed for three-dimensional coordinates i.e. x, y and z axes. For orientation control, three proportional derivative integral controllers (PIDCs) are introduced to control pitch, roll and yaw angles and make them reaching the desired values. Moreover, PID controllers are proposed for controlling the four driving motors. The parameters of both fuzzy and PID controllers are tuned by using particle swarm optimization (PSO) algorithm which enables the selection of the optimal values for each controller. For comparison purposes, the adaptive fuzzy controllers in the frst layer of the proposed control system are replaced with PIDCs to prove the efectiveness of the proposed control system. Furthermore, a Lyaounov theory is utilized for studying the stability of fuzzy controllers. The proposed control system is capable of guiding the QUAV to track the previously defned reference trajectories. For obstacle avoidance, a vector feld histogram algorithm is used to avoid collision of the QUAV with obstructing obstacles that block the QUAV’s path.
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