An Explosion Based Algorithm to Solve the Optimization Problem in Quadcopter Control

摘要: This paper presents an optimization algorithm named Random Explosion Algorithm (REA). The fundamental idea of this is based on a simple concept the explosion object. object commonly known as particle: when exploded, it will randomly disperse fragments around particle within radius. fragment that be considered search agent fill local space and particular region for best fitness solution. proposed was tested 23 benchmark test functions, results are validated by comparative study with eight well-known algorithms, which Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Genetic (GA), Differential Evolution (DE), Multi-Verse Optimizer (MVO), Moth Flame (MFO), Firefly (FA), Sooty Tern (STOA). After that, implemented analyzed quadrotor control application. Similarly, other algorithms stated done. findings reveal REA can yield very competitive results. It also shows convergence analysis has proved converge more quickly toward global optimum than metaheuristic algorithms. For application result, controller better track desired reference input shorter rise time settling time, lower percentage overshoot, minimal steady-state error root mean square (RMSE).