Stabilization and tracking control of an x-z type inverted pendulum system using Lightning Search Algorithm tuned nonlinear PID controller

GÜRSEL ÖZMEN N., Marul M.

ROBOTICA, cilt.40, sa.7, ss.2428-2448, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 40 Sayı: 7
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1017/s0263574721001727
  • Dergi Adı: ROBOTICA
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Applied Science & Technology Source, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, DIALNET, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.2428-2448
  • Anahtar Kelimeler: inverted pendulum, nonlinear PID control, lightning search algorithm (LSA), particle swarm optimization (PSO), stabilization, tracking control, SLIDING-MODE CONTROL, PARTICLE SWARM OPTIMIZATION, FUZZY CONTROL, SWINGING-UP, DESIGN, SPEED
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

Inverted pendulum systems (IPSs) are mostly used to demonstrate the control rules for keeping the pendulum at a balanced upright position due to a slight force applied to the cart system. This paper presents an application for nonlinear control of an x-z type IPS by using a proportional-integral-derivative (PID) controller with newly established evolutionary tuning method Lightning Search Algorithm (LSA). A single, double and triple PID controller system is tested with the conventional and the self-tuning controllers to get a better understanding of the performance of the given system. The mathematical modelling of the x-z type IPS, the theoretical explanation of the LSA and the simulation analysis of the x-z type IPS is put forward entirely. The LSA algorithm solves the optimization problem of PID controller in an evolutionary way. The most effective way of making comparisons is evaluating the performance results with a well-known optimization technique or with the previous accepted results. We have compared the system's performance with particle swarm optimization and with a classical control study in the literature. According to the simulation results, LSA-tuned PID controller has the ability to decrease the overshoot better than the conventional-tuned controllers. Finally, it can be concluded that the LSA-supported PID can better stabilize the pendulum angle and track the reference better for non-disturbed and the slightly disturbed systems.