A non-overshooting controller for vehicle path following

2021 ◽  
pp. 014233122199438
Author(s):  
Tong Xu ◽  
Dong Wang ◽  
Weigong Zhang
Keyword(s):  
Field Experiments ◽  
Fitness Function ◽  
Path Following ◽  
Settling Time ◽  
Distribution Model ◽  
Positioning Errors ◽  
Guidance Law ◽  
Initial Control ◽  
Vehicle Path ◽  
Pavement Construction

Unmanned pavement construction is of great significance in China, and one of the most important issues is how to follow the designed path near the boundary of the pavement construction area to avoid curbs or railings. In this paper, we raise a simple yet effective controller, named the proportional-integral-radius and improved particle swarm optimization (PIR-IPSO) controller, for fast non-overshooting path-following control of an unmanned articulated vehicle (UAV). Firstly, UAV kinematics model is introduced and segmented UAV steering dynamics model is built through field experiments; then, the raw data collected by differential global positioning system (DGPS) is used to build the measurement error distribution model that simulates positioning errors. Next, line of sight (LOS) guidance law is introduced and the LOS initial parameter is assigned based on human driving behavior. Besides, the initial control parameters tuned by the Ziegler-Nichols (ZN) method are used as the initial iterative parameters of the PSO controller. An improved PSO fitness function is also designed to achieve fast non-overshoot control performance. Experiments show that compared with the PSO, ZN and ZN-PSO controller, the PIR-PSO-based controller has significantly less settling time and almost no overshoot in various UAV initial states. Furthermore, compared with other controllers, the proposed PIR-IPSO-based controller achieves precise non-overshoot control, relatively less settling time and centimeter-level positioning error in various initial deviations.

scholarly journals Optimal Path-Following Guidance with Generalized Weighting Functions Based on Indirect Gauss Pseudospectral Method

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Qi Chen ◽  
Xugang Wang ◽  
Jing Yang
Keyword(s):  
Degrees Of Freedom ◽  
Optimal Path ◽  
Pseudospectral Method ◽  
Path Following ◽  
Control Cost ◽  
Weighting Functions ◽  
Guidance Law ◽  
Computational Performance ◽  
Gauss Pseudospectral Method ◽  
Virtual Target

An indirect Gauss pseudospectral method based path-following guidance law is presented in this paper. A virtual target moving along the desired path with explicitly specified speed is introduced to formulate the guidance problem. By establishing a virtual target-fixed coordinate system, the path-following guidance is transformed into a terminal guidance with impact angle constraints, which is then solved by using indirect Gauss pseudospectral method. Meanwhile, the acceleration dynamics are modeled as the first-order lag to the command. Using the receding horizon technique a closed-loop guidance law, which considers generalized weighting functions (even discontinuous) of both the states and the control cost, is derived. The accuracy and effectiveness of the proposed guidance law are validated by numerical comparisons. A STM32 Nucleo board based on the ARM Cortex-M7 processor is used to evaluate the real-time computational performance of the proposed indirect Gauss pseudospectral method. Simulations for various types of desired paths are presented to show that the proposed guidance law has better performance when compared with the existing results for pure pursuit, a nonlinear guidance law, and trajectory shaping path-following guidance and provides more degrees of freedom in path-following guidance design applications.

scholarly journals Design of Three-Dimensional Path Following Guidance Logic

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Sungsu Park
Keyword(s):  
Numerical Simulations ◽  
Three Dimensional ◽  
Path Following ◽  
Guidance Law ◽  
Virtual Target ◽  
Projection Point ◽  
Motion Strategy

This paper presents a three-dimensional path following guidance logic. The proposed guidance logic is composed of the guidance law and the motion strategy of virtual target along the desired path. The guidance law makes a vehicle purse the virtual target, and the motion strategy explicitly specifies the motion of virtual target by introducing the concept of the projection point and the tangentially receding distance. The proposed logic is simple and efficient and yet provides precise path following. Numerical simulations are performed to demonstrate the effectiveness of the proposed guidance logic.

Improved Integral LOS Guidance and Path-Following Control for an Unmanned Robot Sailboat via the Robust Neural Damping Technique

2019 ◽  
Vol 72 (06) ◽  
pp. 1378-1398 ◽  
Author(s):  
Guoqing Zhang ◽  
Jiqiang Li ◽  
Bo Li ◽  
Xianku Zhang
Keyword(s):  
External Disturbance ◽  
Path Following ◽  
Basic Function ◽  
Lyapunov Theory ◽  
Neural Controller ◽  
Adaptive Parameter ◽  
Guidance Law ◽  
Path Following Control ◽  
Adaptive Neural Controller ◽  
Robust Adaptive

This paper introduces a scheme for waypoint-based path-following control for an Unmanned Robot Sailboat (URS) in the presence of actuator gain uncertainty and unknown environment disturbances. The proposed scheme has two components: intelligent guidance and an adaptive neural controller. Considering upwind and downwind navigation, an improved version of the integral Line-Of-Sight (LOS) guidance principle is developed to generate the appropriate heading reference for a URS. Associated with the integral LOS guidance law, a robust adaptive algorithm is proposed for a URS using Radial Basic Function Neural Networks (RBF-NNs) and a robust neural damping technique. In order to achieve a robust neural damping technique, one single adaptive parameter must be updated online to stabilise the effect of the gain uncertainty and the external disturbance. To ensure Semi-Global Uniform Ultimate Bounded (SGUUB) stability, the Lyapunov theory has been employed. Two simulated experiments have been conducted to illustrate that the control effects can achieve a satisfactory performance.

scholarly journals 3DOF Adaptive Line-Of-Sight Based Proportional Guidance Law for Path Following of AUV in the Presence of Ocean Currents

2019 ◽  
Vol 9 (17) ◽  
pp. 3518 ◽  
Author(s):  
Fengxu Liu ◽  
Yue Shen ◽  
Bo He ◽  
Junhe Wan ◽  
Dianrui Wang ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Path Following ◽  
Lyapunov Theory ◽  
Line Of Sight ◽  
Average Error ◽  
Drift Angle ◽  
Reference Path ◽  
Guidance Law ◽  
Look Ahead ◽  
Three Degrees Of Freedom

In order to achieve high-precision path following of autonomous underwater vehicle (AUV) in the horizontal plane, a three degrees-of-freedom adaptive line-of-sight based proportional (3DOFAPLOS) guidance law is proposed. Firstly, the path point coordinate system is introduced, which is suitable for the conversion of an arbitrary path. Then, the appropriate look-ahead distance is obtained by an improved adaptive line-of-sight (ALOS) according to three degrees-of-freedom (3DOF), including the cross-track error, the curvature of reference path, and the forward speed. Moreover, combining three degrees-of-freedom ALOS (3DOFALOS) with proportional guidance law, the desired heading is calculated considering the drift angle. 3DOFAPLOS has two functions: in the convergence stage, 3DOFALOS plays a leading role, making AUV converge to the path more quickly and smoothly. In the guidance stage, proportional guidance law plays a major role in effectively resisting the influence of drift angle and making AUV sail along the reference path. If the path is curved, 3DOFALOS makes contributions in both stages, adjusting look-ahead distance in real time with respect to curvature. The stability of the designed closed system is proved by Lyapunov theory. Both simulation and experiment results have verified that 3DOFAPLOS has a satisfactory result, which improves tracking performance more than 50% compared with the traditional line-of-sight (LOS). Specifically, the mean average error (MAE) of path following under 3DOFAPLOS can be reduced by about 60%, and the root mean square error (RMSE) can be reduced by about 50% compared with LOS.

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