Searching and containing dynamic target like oil spillage in the ocean is a challenging task due to the natural time variance of the spread of the oil. The use of cooperative multi-marine vehicle systems in a cluttered environment for this purpose poses difficulties in sustaining formation pattern to pursue and contain the leakage. In this article, in order to provide realistic setup for the industrial applications of multi-marine vehicles systems, we present a novel approach for collision-free distributed formation control for a network of underactuated surface vessels (USVs). The proposed approach comprises two layers: A distributed coordination layer and a local fixed-time neural network control layer. In the first layer, formation leaders accomplish a specified formation configuration while tracking a desired trajectory from a tracking leader. The second control layer is to robustly drive the real USVs with parametric and nonparametric uncertainties to track their corresponding formation leaders. Because only parts of the formation leaders can acquire the states of the tracking leader, a distributed fixed-time estimator is proposed to obtain accurate estimations of the desired information for each USV in the network. Next, in order to effectively maneuver in cluttered environment, local path replanning-based repulsive potential function technique is proposed for each USV in the group formation to act on the formation leaders trajectories. Further, redesigned adaptive neural networks are integrated to compensate the model uncertainties. The stability of the proposed controller is verified by the Lyapunov direct method. Simulation studies of a hexagon formation are presented to illustrate the effectiveness of the proposed approach.

In this paper, first-order and second-order sliding mode controllers for underactuated manipulators are proposed. Sliding mode control (SMC) is considered as an effective tool in different studies for control systems. However, the associated chattering phenomenon degrades the system performance. To overcome this phenomenon and track a desired trajectory, a twisting, a super-twisting and a modified super-twisting algorithms are presented respectively. The stability analysis is performed using a Lyapunov function for the proposed controllers. Further, the four different controllers are compared with each other. As an illustration, an example of an inverted pendulum is considered. Simulation results are given to demonstrate the effectiveness of the proposed approaches.

This research is aimed to the development of a dynamic control to enhance the performance of the existing dynamic controllers for mobile robots. System dynamics of the car-like robot with nonholonomic constraints were employed. A Backstepping approach for the design of discontinuous state feedback controller is used for the design of the controller. It is shown that the origin of the closed loop system can be made stable in the sense of Lyapunov. The control design is made on the basis of a suitable Lyapunov function candidate. The effectiveness of the proposed approach is tested through simulation on a car-like vehicle mobile robot.