Path Tracking of a Two-Wheeled Self-Balancing Robot Based on Multi-objective Optimization with Artificial Immune Algorithm

Nonlinear Model Predictive Control for a Self-Balancing Wheelchair

“…PID parameters must be adjusted through trial and error, which can be subjective and lack a systematic approach. Therefore, subsequent researchers have explored optimization algorithms such as artificial bee colony optimization, particle swarm optimization, grey wolf optimization, and cuckoo search algorithm [4], [5] to optimize the parameters of PID controllers. PID controllers with constant PID gains are not the best choice for a strong nonlinear system.…”