Optimisation of fuzzy logic quadrotor attitude controller – particle swarm, cuckoo search and BAT algorithms

Abstract

Bio-inspired optimisation algorithms have recently attracted much attention in the control community. Most of these algorithms mimic particular behaviours of some animal species in such a way that allows solving optimisation problems. The present paper aims at applying three metaheuristic methods for optimising fuzzy logic controllers used for quadrotor attitude stabilisation. The investigated methods are particle swarm optimisation (PSO), BAT algorithm and cuckoo search (CS). These methods are applied to find the best output distribution of singleton membership functions of the fuzzy controllers. The quadrotor control requires measured responses, therefore, three objective functions are considered: integral squared error, integral time-weighted absolute error and integral time-squared error. These metrics allow performance comparison of the controllers in terms of tracking errors and speed of convergence. The simulation results indicate that BAT algorithm demonstrated higher performance than both PSO and CS. Furthermore, BAT algorithm is capable of offering 50% less computation time than CS and 10% less time than PSO. In terms of fitness, BAT algorithm achieved an average of 5% better fitness than PSO and 15% better than CS. According to these results, the BAT-based fuzzy controller exhibits superior performance compared with other algorithms to stabilise the quadrotor.

Keywords:

• Metaheuristic
• fuzzy logic quadrotor attitude controller
• particle swarm optimisation
• cuckoo search
• BAT algorithm

Data availability statement

The authors confirm that the data supporting the findings of this study are available within the article.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Mohamed Siddiq Zatout

Mohamed seddiq Zatout received his Master Degree in Automatic of manufacturing systems from department of technology, faculty of science of technology of the University of Khemis Miliana, Algeria in 2016. Currently he is interested in the manufacturing industry. His research fields include fuzzy control, vision, UAV and meta-heuristic optimisation.

Amar Rezoug

Amar Rezoug received his Engineering, Master and Ph.D. Degrees in Automatic Control respectively from the University of Boumerdes, Polytechnic Military School (EMP) and National Polytechnic School of Algiers (ENP), (Algeria 2005, 2008 and 2013). He is currently working as an Assistant Professor in National Superior School of Technology of Algiers (ENST), Algeria. He has more than 40 journal and proceeding papers. His research includes nonlinear and intelligent control, robotics, UAV and meta-heuristic optimisation.

Abdellah Rezoug

Abdellah Rezoug is a Lecturer in the Department of Computer Science at the University Mhamed Bougara of Boumerdes, Algeria. He is also a member of the Research Laboratory in Artificial Intelligence at the University of Science and Technology Houari Boumediene (USTHB), Algiers. He received a Ph.D. degree in Computer Science in 2017 from the USTHB. His main research interests are machine learning, evolutionary computation and combinatorial optimisation.

Khalifa Baizid

Khelifa Baizid, holds a B.Sc. and Engineering degrees in Mechanical Engineering and a Master degree from the Polytechnic Military School (Algeria 2007). He got his Ph.D. degree in Robotics from the Italian Institute of Technology in 2011. He conducted research on aerial manipulation at the University of Cassino and Southern Lazio, Italy 2013-2014. During 2015-2016 He worked as a postdoctoral researcher about multiple robots at the Institut Mines-Télécom, Douai France. Then he worked as a postdoctoral in robotics and industrial automation field at the Italian Institute of Technology from 2018 to 2020. From July 2020 he is a robotics consultant of Logic Robotics Limited in HongKong.

Jamshed Iqbal

Jamshed Iqbal holds a Ph.D. in Robotics from Italian Institute of Technology (IIT) and three Master degrees in various fields of Engineering from Finland, Sweden and Pakistan. He is currently working as a Lecturer (Assistant Professor) - Robotics in the University of Hull, UK. With more than 20 years of multi-disciplinary experience in industry & academia, his research interests include robot analysis and design. He has more than 80 reputed journal papers on his credit with an H-index of 32. He has been a senior member of IEEE since 2016.