scholarly journals Grey Wolf Optimizer-Based Approaches to Path Planning and Fuzzy Logic-based Tracking Control for Mobile Robots

2020 ◽  
Vol 15 (3) ◽  
Author(s):  
Radu-Emil Precup ◽  
Emil-Ioan Voisan ◽  
Emil M. Petriu ◽  
Marius L. Tomescu ◽  
Radu-Codrut David ◽  
...  
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Tracking Control ◽  
Fuzzy Controller ◽  
Optimization Problems ◽  
Cost Effective ◽  
Grey Wolf Optimizer ◽  
Reference Trajectory ◽  
Grey Wolf ◽  
Wheeled Mobile Robots

This paper proposes two applications of Grey Wolf Optimizer (GWO) algorithms to a path planning (PaPl) problem and a Proportional-Integral (PI)-fuzzy controller tuning problem. Both optimization problems solved by GWO algorithms are explained in detail. An off-line GWO-based PaPl approach for Nonholonomic Wheeled Mobile Robots (NWMRs) in static environments is proposed. Once the PaPl problem is solved resulting in the reference trajectory of the robots, the paper also suggests a GWO-based approach to tune cost-effective PI-fuzzy controllers in tracking control problem for NWMRs. The experimental results are demonstrated through simple multiagent settings conducted on the nRobotic platform developed at the Politehnica University of Timisoara, Romania, and they prove both the effectiveness of the two GWO-based approaches and major performance improvement.

A new meta-heuristic optimization algorithm based on a paradigm from physics: string theory

2021 ◽  
Vol 41 (1) ◽  
pp. 1657-1675
Author(s):  
Luis Rodriguez ◽  
Oscar Castillo ◽  
Mario Garcia ◽  
Jose Soria
Keyword(s):  
String Theory ◽  
Optimization Algorithm ◽  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Optimization Problems ◽  
Flower Pollination Algorithm ◽  
Grey Wolf Optimizer ◽  
Mathematical Functions ◽  
Inference System ◽  
First Case

The main goal of this paper is to outline a new optimization algorithm based on String Theory, which is a relative new area of physics. The String Theory Algorithm (STA) is a nature-inspired meta-heuristic, which is based on studies about a theory stating that all the elemental particles that exist in the universe are strings, and the vibrations of these strings create all particles existing today. The newly proposed algorithm uses equations based on the laws of physics that are stated in String Theory. The main contribution in this proposed method is the new techniques that are devised in order to generate potential solutions in optimization problems, and we are presenting a detailed explanation and the equations involved in the new algorithm in order to solve optimization problems. In this case, we evaluate this new proposed meta-heuristic with three cases. The first case is of 13 traditional benchmark mathematical functions and a comparison with three different meta-heuristics is presented. The three algorithms are: Flower Pollination Algorithm (FPA), Firefly Algorithm (FA) and Grey Wolf Optimizer (GWO). The second case is the optimization of benchmark functions of the CEC 2015 Competition and we are also presenting a statistical comparison of these results with respect to FA and GWO. In addition, we are presenting a third case, which is the optimization of a fuzzy inference system (FIS), specifically finding the optimal design of a fuzzy controller, where the main goal is to optimize the membership functions of the FIS. It is important to mention that we used these study cases in order to analyze the proposed meta-heuristic with: basic problems, complex problems and control problems. Finally, we present the performance, results and conclusions of the new proposed meta-heuristic.

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