Fuzzy control of industrial systems: theory and applications
Fuzzy control of industrial systems: theory and applications
Design of fuzzy PID controllers using modified triangular membership functions
Information Sciences: an International Journal
Decoupled adaptive neuro-fuzzy (DANF) sliding mode control system for a Lorenz chaotic problem
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Nonlinear controller design of a ship autopilot
International Journal of Applied Mathematics and Computer Science
Expert Systems with Applications: An International Journal
Adaptive fuzzy sliding mode control for electro-hydraulic servo mechanism
Expert Systems with Applications: An International Journal
Adaptive cruise control of a HEV using sliding mode control
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Hi-index | 12.06 |
This study presents an adaptive neuro-fuzzy sliding-mode-based genetic algorithm (ANFSGA) control system for a remotely operated vehicle (ROV) with four degrees of freedom (DOF)s. In many applications, ROVs will need to be capable of maneuvering to any given point, following object, and to be controllable from the surface. Therefore, an ANFSGA control system is introduced for tracking control of the ROV to achieve a high precision position control. Since the dynamic of ROVs are highly nonlinear and time varying, an ANFSGA control system is investigated according to direction-based genetic algorithm (GA) with the spirit of sliding mode control and adaptive neuro-fuzzy sliding mode (ANFS) based evolutionary procedure. In this way, on-line learning ability is employed to deal with the parametric uncertainty and disturbance by adjusting the ANFS inference parameters. In this proposed controller a GA control system is utilized to be the major controller, and stability can be indirectly insured by the concept of sliding mode control system without strict constraints and detailed system knowledge.