Fuzzy Sliding Mode with Region Tracking Control for Autonomous Underwater Vehicle

Underwater vehicles play an important part in military, oil and gas sector nowadays. However, the environment underwater is also not very known to men, so the underwater vehicle or robot that get sent there have to be fully autonomous in order to be able to do the mission without fail. Therefore, many research in the recent years focusing on how to improve the performance of underwater vehicle especially in regulate and tracking control system. A lot of controllers have been proposed for the purpose of improving the control system of AUV such as PID, sliding mode control, adaptive, fuzzy logic, neural network and combination of these controllers. Proportional-Derivative (PD) control plus gravity compensation [1] is the simplest set-point technique for controlling an AUV. However, the weakness of PD control plus gravity compensation is that it is difficult to obtain the exact model of gravitational and buoyancy forces as the dynamic of AUV depend on the condition of the subsea. In addition, the wave current could easily sway away the AUV from its destination. The conventional set point method as this method required more energy so that the vehicle can stay on its point whilst being drag out with wave current. Another method called region tracking method is proposed by Li [2] to overcome this weakness. In this method, the target is a region instead of a point. By redefine the target as a region, the AUV can stay as long as needed without having to activate its controller as long as the wave current does not drag itself out of the region. This method also is applied to a swarm robot as proposed by Hou [3]. Zool proposed using boundary region instead of region in [4] because there are AUV missions that need boundary as objective such as monitoring the exterior pipeline underwater and etc. Sliding mode control is one of controller usually used for AUV control system as it robust against uncertainty and disturbance. However, the main weakness of sliding mode is the chattering effect. So, most of research using sliding mode control focus on eliminated the chattering effect. One of the usual methods to reduce the chattering effect is by substitute the signum function with saturation function. In [5], Santhakumar and Asokan proposed combine and using best the PID and sliding mode control. In the initial phase, SMC will be operating however when the system is in reaching phase, PID controller will be used to bring the system to steady state. Bessa [6] in the other hand, proposed an adoption of properly design boundary layer to overcome the chattering effect. Soylu [7], proposed using adaptive term instead the sign term to eliminated the chattering effect and Sun, also using the same approaches as Soylu added with backstepping technique for tracking control of an AUV in [8]. Fuzzy logic has been extensively used in the recent years compared when it was first introduced by Zadeh around forty years ago[9]. The application of fuzzy logic is range from consumer product to control application. For control purposes, fuzzy logic has been designed as a tuning gain algorithm for control method such as PID and sliding mode control. The use of fuzzy logic to tune the gains in PID controller is reported in [10, 11] and sliding mode gain in [12]. In [13], fuzzy logic is used to model the equation switching term in sliding mode controller instead using signum function. In this paper, we presented fuzzy sliding mode control with region tracking control for a single AUV. Simulation results on AUV with 6 degrees of freedom are presented to demonstrate the effectiveness of the proposed controller. The rest of the paper is organized as follow: Section 2 describes the kinematic and dynamic properties of an AUV. In Section 3, the fuzzy sliding model control with region function formulation is briefly explained. In Section 4, numerical simulation results are provided to demonstrate the performance of the proposed controllers compared with conventional sliding mode control. Finally, the paper is closed with Article history