A new predictive intelligent controller and path planning for mobile robots

Abstract

This paper studies the synchronization and control of chaotic systems, and a new chaotic-based path is designed for Mobile robots (MRs). The chaotic systems are used to design an unpredictable path for a class of patrol MRs. To enhance security, multiple chaotic systems with a chaotic switching mechanism are introduced for path planning. The main challenge is that the dynamics of MRs are entirely unknown. The physical dynamics are not reliable in practice, because many parameters in MR dynamics are changed due to unknown environmental conditions such as noisy sensors, time delays, friction, and non-ideal actuators. Also, the chaotic switching of reference signals between chaotic signals imposes a high dynamic perturbation. So, a powerful fractional-order predictive controller on the basis of type-3 (T3) fuzzy-logic systems (FLSs) is developed. The estimation and prediction errors of T3-FLSs are compensated by a designed parallel compensator. T3-FLSs are online tuned such that stability is ensured, and the defined cost function for prediction controller is minimized. The suggested scheme is implemented on a real-world MR, and the results demonstrate the febrility and the accuracy. Also, in several simulations, the efficacy of the designed controller is examined. The simulation and experimental results show that the accuracy is improved more than 70% in comparison with conventional predictive controllers under noisy signals and uncertain dynamics.