د. عبد القادر جوخدار
- درجة الإجازة في الهندسة الكهربائية والإلكترونية - جامعة حلب - عام 1992.
- درجة الماجستير MPhil - التحكم والإلكترونيات الصناعية - جامعة بيرمنغهام - بريطانيا 1999.
- درجة الدكتوراه PhD أنظمة التحكم الذكية - جامعة أبردين - بريطانيا 2004.
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الاتصال
- ajoukhadar@gmail.com
الخبرات السابقة:
- مدرس في قسم هندسة الميكاترونيكس - جامعة حلب - منذ عام 2004.
- أستاذ مساعد في قسم هندسة الميكاترونيكس - جامعة حلب منذ عام 2012.
- أستاذ في قسم هندسة الميكاترونيكس - جامعة حلب منذ عام 2019.
- رئيس قسم هندسة الميكاترونيكس 2009 - 2013.
- نائب عميد كلية الهندسة الكهربائية والإلكترونية للشؤون العلمية 2015 - 2019.
- عميد كلية الهندسة الكهربائية والإلكترونية 2019 - 2020.
الابحاث:
Using the Bees Algorithm for wheeled mobile robot path planning in an indoor dynamic environment
This paper presents a solution to plan a path using a new form of the Bees Algorithm for a 2-Wheeled Differential Drive mobile robot. This robot is used in an indoor environment. The environment consists of static and dynamic obstacles which are represented by a continuous configuration space as an occupancy map-based. The proposed method is run in two respective stages. Firstly, the optimal path is obtained in the static environment using either the basic form or the new form of the Bees Algorithm. The initial population in the new form of the Bees Algorithm consists only of feasible paths. Secondly, this optimal path is updated online to avoid collision with dynamic obstacles. A modified form of the local search is used to avoid collision with dynamic obstacles and to maintain optimality of sub-paths. A set of benchmark maps were used to simulate and evaluate the proposed algorithm. The results obtained were compared with those of the other algorithms for different sets of continuous maps. - Cogent Engineering Volume 5, 2018 - Issue 1
قراءة المزيد >>Real time control of multi-agent mobile robots with intelligent collision avoidance system
This paper presents a newly developed mobile robot based multi-agent system with capabilities of robust motion control and intelligent collision avoidance. The system consists of three mobile robots, one master and two slaves. The master robot intelligently takes decisions as to which action to perform to avoid obstacles and collisions. On the other hand, the master mobile robot is capable to swerve around a static or moving object when necessary. All possible conditions have been arranged in a fuzzy knowledge base which is used to express and manipulate them in which the mobile robot may encounter them on its driving lane. The proposed research has been carried out to simulate a real car driving regime on roads where the driver may not react properly. - Science and Information Conference
قراءة المزيد >>Mechanism, Machine, Robotics and Mechatronics Sciences
Recently trajectory tracking control of a quadcopter has been paid attention by academic and industry. This paper proposes two different strategies for trajectory tracking control of a quadcopter system implementing nonlinear control theory. The first approach is based on the integral backstepping technique, the second proposed one is an LQI (Linear Quadratic Integral) optimal controller with a feedback linearization so as to deal with the nonlinearity and the coupling components of the quadcopter state variables. The control laws for trajectory tracking using the proposed two strategies were validated by simulation and experimental results obtained from a quadcopter test bench. Simulation results show a comparison between the performance of each of the two control laws depending on the nonlinear model of the quadcopter system under investigation; the trajectory tracking has been achieved properly for … - Mechanism, Machine, Robotics and Mechatronics Sciences
قراءة المزيد >>