Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : ant colony optimization

Development of Path Planning Algorithm Using Probabilistic Roadmap Based on Ant Colony Optimization

Mohammed I. Abdulakareem; Firas A. Raheem

Engineering and Technology Journal, 2020, Volume 38, Issue 3A, Pages 343-351
DOI: 10.30684/etj.v38i3A.389

In this paper, a unique combination among probabilistic roadmap, ant colony optimization, and third order B-spline curve has been proposed to solve path-planning problem in complex and very complex environments. This proposed method can be divided into three stages. First stage is to construct a random map depending on the environment complexity using probabilistic roadmap algorithm. This could be done by sampling N nodes randomly in complex and very complex static environments, then connecting these nodes together according to some criteria or conditions. The constructed roadmap contains huge number of possible random paths that may connect the start and the goal points together. Second stage includes finding path within the pre-constructed roadmap. Ant colony optimization is selected to find or to search the best path between start and goal points. Finally, the third stage uses B-spline curve to smooth and reduce total length of the found path in the previous stage where path’s length has been reduced by 1% in first environment and by 15% in second environment. The results of the proposed approach ensure feasible path between start and goal points in complex and very complex environment. In addition, the path is guaranteed to be shortest, smooth, continues and safe.

Design and Implementation of a Fuzzy Logic Controller for Inverted Pendulum System Based on Evolutionary Optimization Algorithms

Ahmed F. Ghaliba; Ahmed A. Oglah

Engineering and Technology Journal, 2020, Volume 38, Issue 3A, Pages 361-374
DOI: 10.30684/etj.v38i3A.400

The inverted pendulum is a standard classical problem in the branch of
control and systems. If a cart is bushed by force then its position and angle
of the pendulum will be changed. Several controllers may employed,
keeping the pendulum arm upright by controlling at the cart location. In
this search paper, the fuzzy-like PID (FPID) controller has been used to
control the inverted pendulum, and the parameters of the controller are
tuned with several evolutionary optimization algorithms like a genetic
algorithm (GA), ant colony optimization (ACO), and social spider
optimization (SSO.) The result of tuned FPID with evolutionary
optimization is compared with conventional PID, and it shows that FPID
with SSO has been given the best result.