Controller Design based on Fractional Calculus for AUV Yaw Control

Abstract

This research presents a fractional order integral controller strategy, which improves the steering angle for Autonomous Underwater Vehicles (AUVs). The AUV mathematical modeling is presented. A Fractional Order Proportional Integral (FOPI) control scheme is implemented to ensure the yaw angle stability of the AUV steering under system uncertainty. The FOPI controller is validated with MATLAB/Simulink and is compared to the conventional Integer Order PI (IOPI) controller to track the yaw angle of the structure. The simulation results show that the proposed FOPI controller outperforms the IOPI controller and improves the AUV system steering and the overall transient response while ensuring the system's stability with and without external disturbances such as underwater current and different loading conditions.

Fractional Order Modeling and Control of an Articulated Robotic Arm

“…For the robotic arm structure, it is crucial for the controller to track the desired position accurately in order to attain a stable operation. Noninteger calculus is a generalized concept to fractional order differential and integral basic operator ^# _ ` as defined in [17]:…”

Performance Comparison of Different Fuzzy Logic Controllers on Vehicle-Caravan Systems

“…Active control techniques are used in VC systems against instability modes [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24]. Active control techniques can be used in both the towing vehicle and the caravan system.…”

“…Model-based and model-independent methods are used in active control techniques developed using ADB in VC systems. The Model Predictive Control (MPC) controller was developed to increase the lateral stability of the trailer system and prevent the occurrence of unstable situations [7,[21][22]. Examining the performance of the braking controller using the Linear Quadratic Regulator (LQR) technique showed that stable responses were produced [4,6,22].…”

“…The Model Predictive Control (MPC) controller was developed to increase the lateral stability of the trailer system and prevent the occurrence of unstable situations [7,[21][22]. Examining the performance of the braking controller using the Linear Quadratic Regulator (LQR) technique showed that stable responses were produced [4,6,22]. Model-based controllers have the disadvantage that the system model can be used after modeling with different degrees of freedom according to the application area.…”

“…This study used the fuzzy logic method as a modelindependent control technique, as there is no need for a system model if it is used as an active control technique in the VC system. Several studies used the FLC technique in VC systems, showing that unstable states were prevented [9,[21][22][23][24]. Such studies usually compare the proposed controller with other control techniques or when the controller is turned off.…”