Stabilization for a class of delayed switched inertial neural networks via non-reduced order method

This paper tackles the issue of global stabilization for a class of delayed switched inertial neural networks (SINN). Distinct from the frequently employed reduced-order technique, this paper studies SINN directly through non-reduced order method. By constructing a novel Lyapunov functional and using Barbalat Lemma, sufficient conditions for the global asymptotic stabilization issue and global exponential stabilization issue of the considered SINN are established. Numerical simulations further confirm the feasibility of the main results. The comparative research shows that global stabilization results of this paper complement and improve some existing work.

Consensus of Second-Order Multiagent Systems with Directed Signed Networks and Communication Delays

This paper is concerned with the consensus problem for second-order multiagent systems (MASs) with directed signed networks and local communication delays. First, under a strongly connected directed graph, some properties for signed digraph and the model of second-order MASs are provided. A distributed nonlinear consensus control protocol is proposed for implementing consensus of second-order MASs with signed digraph and communication delay. Then, for structurally balanced and unbalanced networks, the consensus of second-order MASs with directed signed networks and local delays is proved via the Lyapunov method and Barbalat lemma. Simulation examples are given to demonstrate the effectiveness of our results.

Neural network-based distributed adaptive configuration containment control for satellite formations

Considering unknown perturbations and model uncertainties, this paper investigates the configuration containment control for satellite formations based on directed communication topologies. We consider that there are multiple leader satellites with constant relative velocities, while only a subset of follower satellites have access to the leaders. First, a distributed velocity observer is proposed for each follower to obtain velocity information of the leaders. Then, a distributed adaptive configuration containment control algorithm is proposed in which the model nonlinear uncertainties are approximated and compensated through neural networks, while the perturbations and approximation errors are compensated by adaptive gain technique. Furthermore, subject to the chattering caused by sign functions, an improved continuous containment strategy is developed. We use graph theory, Lyapunov theory, and Barbalat lemma to demonstrate that both proposed methods can make all the follower satellites converge to the convex hull spanned by the leader satellites. Numerical examples and comparisons are provided to show the effectiveness and performances of the proposed control strategies.

Adaptive Output Tracking Control for a Class of MIMO Nonlinear Systems with Time-Delay

For a class of multi-input multi-output (MIMO) nonlinear system with time-delay, a problem of adaptive output tracking is investigated. Through applying the back-stepping recursive method, an adaptive output tracking controller is designed to achieve robust control. According to Lyapunov stability theory, Barbalat lemma, and Gronwall inequality, the designed state feedback controller not only guarantees the system states are uniformly bounded, but also ensures the system tracking error converges to a small neighborhood.

Localization and tracking control for mobile welding robot

Purpose – The purpose of this paper is to design the localization and tracking algorithms for our mobile welding robot to carry out the large steel structure welding operations in industrial environment. Design/methodology/approach – Extended Kalman filter, considering the bicycle-modeled robot, is adopted in the localization algorithm. The position and orientation of our mobile welding robot is estimated using the feedback of the laser sensor and the robot motion commands history. A backstepping variable is involved in the tracking algorithm. By introducing a specifically selected Lyapunov function, we proved the tracking algorithm using Barbalat Lemma, which leads the errors of estimated robot states to converge to zero. Findings – The experiments show that the proposed localization method is fast and accurate and the tracking algorithm is robust to track straight lines, circles and other typical industrial curve shapes. The proposed localization and tracking algorithm could be used, but not limited to the mobile welding. Originality/value – Localization problem which is neglected in previous research is very important in mobile welding. The proposed localization algorithm could estimate the robot states timely and accurately, and no additional sensors are needed. Furthermore, using the estimated robot states, we proposed and proved a tracking algorithm for bicycle-modeled mobile robots which could be used in welding as well as other industrial operation scenarios.

A Developed Adaptive Tracking Control Technique for a Four-Rotor Helicopter with External Disturbance

This paper deals with the tracking control problem of attitude angles for a four-rotor helicopter with external disturbance. A new direct adaptive compensation controller and its parameter adaptive laws are designed based on the Lyapunov stability theory, and the designed contorller can not only compensate the disturbance efficiently, but also can make the attitude angles of the four-rotor helicopter track a given reference output. By using the Barbalat lemma, the systems state tracking performance is proofed. Finally, the proposed adaptive technique is evaluated by a simulation example.