scholarly journals Velocity Free Platoon Formation Control for Unmanned Surface Vehicles with Output Constraints and Model Uncertainties

2020 ◽  
Vol 10 (3) ◽  
pp. 1118 ◽  
Author(s):  
Duansong Wang ◽  
Mingyu Fu ◽  
Shuzhi Sam Ge ◽  
Dongyu Li
Keyword(s):  
Lyapunov Functions ◽  
Formation Control ◽  
Model Uncertainties ◽  
Model Based Control ◽  
Unmanned Surface Vehicles ◽  
Output Constraints ◽  
Formation Pattern ◽  
The Neural Networks ◽  
Communication Distance ◽  
Barrier Lyapunov Functions

This paper studies the velocity free platoon formation control for unmanned surface vehicles (USVs) with the model uncertainties and output constraints. Firstly, a reconstruction module is designed to estimate the velocity of the leader, which will be completed in finite time and will reduce the communication burden. Along with this, the model-based control combined with the symmetric barrier Lyapunov functions (BLF) method is designed to guarantee the output constraints. Then, the model uncertainties of the USV are approximated by the neural networks (NNs) and the NN BLF control is developed. To achieve the desired formation pattern, the constraints, including collision avoidance and communication distance, are under consideration. Finally, we proved that our system is semiglobally uniformly ultimately bounded (SGUUB) and verified the effectiveness of this approach by simulations.

scholarly journals A Staged Finite-Time Control Strategy for Formation of Underactuated Unmanned Surface Vehicles

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Hui Ye ◽  
Xiaofei Yang ◽  
Chunxiao Ge ◽  
Zhaoping Du
Keyword(s):  
Control Strategy ◽  
Finite Time ◽  
Formation Control ◽  
Initial Condition ◽  
Limited Time ◽  
Unmanned Surface Vehicles ◽  
Time Control ◽  
Starting Point ◽  
Formation Pattern ◽  
Distributed Controllers

The formation control issue for a group of underactuated unmanned surface vehicles (USVs) is discussed in the paper, and a staged finite-time control strategy for the USVs is proposed. Firstly, we try to steer each USV to its own starting point in the formation for a limited time, under the initial condition that each of these vehicles is parked at random. To deal with the nonholonomic behavior of the system, the dynamics of the USV is transformed into cascade systems. Then, the finite-time controller is designed for each vehicle based on homogeneity theory. After each USV reaches its own starting point with desired orientation, the model of the vehicle is decomposed into two subsystems under the Serret-Frenet frame. In order to maintain the formation pattern, two finite-time distributed controllers are developed for the surge subsystem and the yaw subsystem, respectively. The settling time for the staged control strategy is limited. Numerical simulations are carried out to illustrate the effectiveness of the proposed formation control strategy.

Barrier Lyapunov functions-based localized adaptive neural control for nonlinear systems with state and asymmetric control constraints

2018 ◽  
Vol 41 (6) ◽  
pp. 1656-1664 ◽  
Author(s):  
Jun Zhang ◽  
Guosheng Li ◽  
Yahui Li ◽  
Xiaokang Dai
Keyword(s):  
Nonlinear Systems ◽  
Lyapunov Functions ◽  
Neural Control ◽  
Tracking Error ◽  
Formal Proof ◽  
Reference Trajectory ◽  
Control Input ◽  
Control Constraints ◽  
Output Constraints ◽  
Barrier Lyapunov Functions

A barrier Lyapunov functions (BLFs)-based localized adaptive neural network (NN) control is proposed for a class of uncertain nonlinear systems with state and asymmetric control constraints to track the reference trajectory. To handle system constraints, BLFs are used in the backstepping procedure, and the control input is considered as an extended state variable. This extends current research on BLFs-based control for systems with state and output constraints to systems with state and asymmetric control constraints. A locally weighted learning NN with projection modification is designed to estimate and compensate for the system uncertainty. The use of projection modification ensures the NN estimator is contained in a given bounded area and prevents the absolute value of NN output from being near to or larger than the bound of the tracking error. The feasibility and effectiveness of the proposed control have been demonstrated by formal proof and simulation results.

scholarly journals Reinforcement-Learning-Based Asynchronous Formation Control Scheme for Multiple Unmanned Surface Vehicles

2021 ◽  
Vol 11 (2) ◽  
pp. 546
Author(s):  
Jiajia Xie ◽  
Rui Zhou ◽  
Yuan Liu ◽  
Jun Luo ◽  
Shaorong Xie ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Formation Control ◽  
Rapid Development ◽  
Gradient Algorithm ◽  
Robot System ◽  
Physical Relationship ◽  
Unmanned Surface Vehicles ◽  
Main Challenge ◽  
Control Scheme ◽  
Multi Robot

The high performance and efficiency of multiple unmanned surface vehicles (multi-USV) promote the further civilian and military applications of coordinated USV. As the basis of multiple USVs’ cooperative work, considerable attention has been spent on developing the decentralized formation control of the USV swarm. Formation control of multiple USV belongs to the geometric problems of a multi-robot system. The main challenge is the way to generate and maintain the formation of a multi-robot system. The rapid development of reinforcement learning provides us with a new solution to deal with these problems. In this paper, we introduce a decentralized structure of the multi-USV system and employ reinforcement learning to deal with the formation control of a multi-USV system in a leader–follower topology. Therefore, we propose an asynchronous decentralized formation control scheme based on reinforcement learning for multiple USVs. First, a simplified USV model is established. Simultaneously, the formation shape model is built to provide formation parameters and to describe the physical relationship between USVs. Second, the advantage deep deterministic policy gradient algorithm (ADDPG) is proposed. Third, formation generation policies and formation maintenance policies based on the ADDPG are proposed to form and maintain the given geometry structure of the team of USVs during movement. Moreover, three new reward functions are designed and utilized to promote policy learning. Finally, various experiments are conducted to validate the performance of the proposed formation control scheme. Simulation results and contrast experiments demonstrate the efficiency and stability of the formation control scheme.

scholarly journals Quadrotor Formation Strategies Based on Distributed Consensus and Model Predictive Controls

2018 ◽  
Vol 8 (11) ◽  
pp. 2246 ◽  
Author(s):  
Chia-Wei Chang ◽  
Jaw-Kuen Shiau
Keyword(s):  
Formation Control ◽  
Vertical Motion ◽  
Formation Flight ◽  
Horizontal Motion ◽  
Motion Simulation ◽  
Linear Quadratic ◽  
Distributed Consensus ◽  
Consensus Control ◽  
Formation Pattern ◽  
The Given

In this study, the distributed consensus control and model predictive control (MPC)-based formation strategies for quadrotors are proposed. First, the formation-control problem is decoupled into horizontal and vertical motions. The distributed consensus control and MPC-based formation strategy are implemented in the follower’s horizontal formation control. In the horizontal motion, the leader tracks the given waypoints by simply using the MPC, and generates the desired formation trajectory for each follower based on its flight information, predicted trajectory, and the given formation pattern. On the other hand, the followers carry out the formation flight based on the proposed horizontal formation strategy and the desired formation trajectories generated by the leader. In the vertical motion, formation control is carried out using only the MPC for both the leader and the follower. Likewise, the leader tracks the desired altitude/climb rate and generates the desired formation trajectories for the followers, and the followers track the desired formation trajectories generated by the leader using the MPC. The optimization problem considered in the MPC differs for the horizontal and vertical motions. The problem is formulated as a quadratic programming (QP) problem for the horizontal motion, and as a linear quadratic tracker (LQT) for the vertical motion. Simulation of a comprehensive maneuver was carried out under a Matlab/Simulink environment to examine the performance of the proposed formation strategies.

scholarly journals Distance-Based Formation Control for Quadrotors with Collision Avoidance via Lyapunov Barrier Functions

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Jawhar Ghommam ◽  
Luis F. Luque-Vega ◽  
Maarouf Saad
Keyword(s):  
Collision Avoidance ◽  
Tracking Control ◽  
Formation Control ◽  
Closed Loop ◽  
Group Formation ◽  
Closed Loop System ◽  
Relative Localization ◽  
Formation Pattern ◽  
Set Up ◽  
The Stability

In this paper, group formation control with collision avoidance is investigated for heterogeneous multiquadrotor vehicles. Specifically, the distance-based formation and tracking control problem are addressed in the framework of leader-follower architecture. In this scheme, the leader is assigned the task of intercepting a target whose velocity is unknown, while the follower quadrotors are arranged to set up a predefined rigid formation pattern, ensuring simultaneously interagent collision avoidance and relative localization. The adopted strategy for the control design consists in decoupling the quadrotor dynamics in a cascaded structure to handle its underactuated property. Furthermore, by imposing constraints on the orientation angles, the follower will never be overturned. Rigorous stability analysis is presented to prove the stability of the entire closed-loop system. Numerical simulation results are presented to validate the proposed control strategy.

Sign in / Sign up

Export Citation Format

Share Document