Responsive surging, heading and diving controls of autonomous underwater vehicle based on brute forcing and smoothing of controllers

884-889There are many types of controllers had been used to control Autonomous Underwater Vehicle (AUV) such as Proportional Integral Derivative (PID), Linear Quadratic Regulator (LQR), state feedback linearization, integrator backstepping, and Sliding-Mode Control (SMC). However, for PID and SMC in particular, it is difficult to determine the optimal control design parameters. The objective of this study is to design and develop a responsive motion control system with optimal parameters for an AUV. The contribution of this paper is in term of introducing a filter to smooth reference signal and proposing a brute forcing technique to find optimal controller parameters. The methodology starts with modeling the AUV, estimating the unknown parameters from a real AUV model, designing a control system based on PI and SMC methods, and finally optimizing the controller parameters. The controller design was onto controlling surge speed using PI, heading using SMC, and diving using SMC. Simulation-wise, the developed control system has an average value of 93.89 % of responsiveness to track desired trajectory while 82.33 % of responsiveness without using the smoothing filter. The tested input signals were unit step, ramp, parabolic, and sinusoidal

Responsive surging, heading and diving controls of autonomous underwater vehicle based on brute forcing and smoothing of controllers

There are many types of controllers had been used to control Autonomous Underwater Vehicle (AUV) such as Proportional Integral Derivative (PID), Linear Quadratic Regulator (LQR), state feedback linearization, integrator back-stepping, and Sliding-Mode Control (SMC). However, for PID and SMC in particular, it is difficult to determine the optimal control design parameters. The objective of this study is to design and develop a responsive motion control system with optimal parameters for an AUV. The contribution of this paper is in term of introducing a filter to smooth reference signal and proposing a brute forcing technique to find optimal controller parameters. The methodology starts with modeling the AUV, estimating the unknown parameters from a real AUV model, designing a control system based on PI and SMC methods, and finally optimizing the controller parameters. The controller design was onto controlling surge speed using PI, heading using SMC, and diving using SMC. Simulation-wise, the developed control system has an average value of 93.89 % of responsiveness to track desired trajectory while 82.33 % of responsiveness without using the smoothing filter. The tested input signals were unit step, ramp, parabolic, and sinusoidal

Responsive surging, heading and diving controls of autonomous underwater vehicle based on brute forcing and smoothing of controllers

There are many types of controllers had been used to control Autonomous Underwater Vehicle (AUV) such as Proportional Integral Derivative (PID), Linear Quadratic Regulator (LQR), state feedback linearization, integrator back-stepping, and Sliding-Mode Control (SMC). However, for PID and SMC in particular, it is difficult to determine the optimal control design parameters. The objective of this study is to design and develop a responsive motion control system with optimal parameters for an AUV. The contribution of this paper is in term of introducing a filter to smooth reference signal and proposing a brute forcing technique to find optimal controller parameters. The methodology starts with modeling the AUV, estimating the unknown parameters from a real AUV model, designing a control system based on PI and SMC methods, and finally optimizing the controller parameters. The controller design was onto controlling surge speed using PI, heading using SMC, and diving using SMC. Simulation-wise, the developed control system has an average value of 93.89 % of responsiveness to track desired trajectory while 82.33 % of responsiveness without using the smoothing filter. The tested input signals were unit step, ramp, parabolic, and sinusoidal

The predictive functional control and the management of constraints in GUANAY II autonomous underwater vehicle actuators

Autonomous underwater vehicle control has been a topic of research in the last decades. The challenges addressed vary depending on each research group's interests. In this paper, we focus on the predictive functional control (PFC), which is a control strategy that is easy to understand, install, tune, and optimize. PFC is being developed and applied in industrial applications, such as distillation, reactors, and furnaces. This paper presents the rst application of the PFC in autonomous underwater vehicles, as well as the simulation results of PFC, fuzzy, and gain scheduling controllers. Through simulations and navigation tests at sea, which successfully validate the performance of PFC strategy in motion control of autonomous underwater vehicles, PFC performance is compared with other control techniques such as fuzzy and gain scheduling control. The experimental tests presented here offer effective results concerning control objectives in high and intermediate levels of control. In high-level point, stabilization and path following scenarios are proven. In the intermediate levels, the results show that position and speed behaviors are improved using the PFC controller, which offers the smoothest behavior. The simulation depicting predictive functional control was the most effective regarding constraints management and control rate change in the Guanay II underwater vehicle actuator. The industry has not embraced the development of control theories for industrial systems because of the high investment in experts required to implement each technique successfully. However, this paper on the functional predictive control strategy evidences its easy implementation in several applications, making it a viable option for the industry given the short time needed to learn, implement, and operate, decreasing impact on the business and increasing immediacy.Peer ReviewedPostprint (author's final draft