scholarly journals High-Gain Extended State Observer Based Adaptive Sliding Mode Path Following Control for An Underactuated Vessel Sailing in Restricted Waters

2019 ◽  
Vol 9 (6) ◽  
pp. 1102 ◽  
Author(s):  
Jianqin Wang ◽  
Zaojian Zou ◽  
Tao Wang

This paper studied the path following problem for an underactuated vessel sailing in restricted waters with varying water depths. A novel high-gain extended state observer based adaptive sliding mode path following control scheme was proposed. The high-gain extended state observer based line-of-sight guidance law was designed according to vessel kinematics in the horizontal plane, which achieved accurate guidance in spite of time-varying sideslip angles. In the guidance system, a guidance angle was calculated to serve as a reference input for the yaw tracking control system. The sliding mode yaw tracking control system was designed, which can deal with model uncertainties and external disturbances. Since it is hard to obtain the exact model parameters in advance, an adaptive technique was adopted to estimate the unknown parameters, and an adaptive sliding mode control was designed to make the yaw tracking errors globally and asymptotically converge to zero in spite of unknown model parameters, model uncertainties, and external disturbances. Furthermore, the global uniformly asymptotically stability of the closed-loop system was proven based on the cascade system theory. Lastly, simulation experiments were conducted to validate the analysis results and to demonstrate the superiority of the proposed scheme.

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Peng Gao ◽  
Guangming Zhang ◽  
Huimin Ouyang ◽  
Lei Mei

A novel sliding mode controller (SMC) with nonlinear fractional order PID sliding surface based on a novel extended state observer for the speed operation of a surface-mounted permanent magnet synchronous motor (SPMSM) is proposed in this paper. First, a new smooth and derivable nonlinear function with improved continuity and derivative is designed to replace the traditional nonderivable nonlinear function of the nonlinear state error feedback control law. Then, a nonlinear fractional order PID sliding mode controller is proposed on the basis of the fractional order PID sliding surface with the combination of the novel nonlinear state error feedback control law to improve dynamic performance, static performance, and robustness of the system. Furthermore, a novel extended state observer is designed based on the new nonlinear function to achieve dynamic feedback compensation for external disturbances. Stability of the system is proved based on the Lyapunov stability theorem. The corresponding comparative simulation results demonstrate that the proposed composite control algorithm displays good stability, dynamic properties, and strong robustness against external disturbances.


Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3305 ◽  
Author(s):  
Gang Wang ◽  
Chenghui Zhou ◽  
Yu Yu ◽  
Xiaoping Liu

When the wheeled mobile robot (WMR) is required to perform specific tasks in complex environment, i.e., on the forestry, wet, icy ground or on the sharp corner, wheel skidding and slipping inevitably occur during trajectory tracking. To improve the trajectory tracking performance of WMR under unknown skidding and slipping condition, an adaptive sliding mode controller (ASMC) design approach based on the extended state observer (ESO) is presented. The skidding and slipping is regarded as external disturbance. In this paper, the ESO is introduced to estimate the lumped disturbance containing the unknown skidding and slipping, parameter variation, parameter uncertainties, etc. By designing a sliding surface based on the disturbance estimation, an adaptive sliding mode tracking control strategy is developed to attenuate the lumped disturbance. Simulation results show that higher precision tracking and better disturbance rejection of ESO-ASMC is realized for linear and circular trajectory than the ASMC scheme. Besides, experimental results indicate the ESO-ASMC scheme is feasible and effective. Therefore, ESO-ASMC scheme can enhance the energy efficiency for the differentially driven WMR under unknown skidding and slipping condition.


Author(s):  
Yi Zhang ◽  
Wenchao Xue ◽  
Li Sun ◽  
Jiong Shen

Path following control of underactuated autonomous vessels remains a challenging issue in recent years due to its inherent underactuation and nonlinearities as well as the widely existing disturbances in the marine environment. In order to accommodate all the difficulties simultaneously, a novel extended state Kalman filter, which adopts the idea of extended state observer in estimating and compensating system lumped disturbance and optimizes the filter gain in a real-time fashion using Kalman filter technique, is constructed to estimate system states and disturbances in the presence of model uncertainties and measurement noise. Based on the estimated states and disturbances, an enhanced model predictive controller is proposed to steer the underactuated autonomous vessels along a predefined path at a desired speed after considering system state and input constraints. Simulation results have proved the superiority of extended state Kalman filter over traditional extended state observer and extended Kalman filter under various disturbance and noise scenarios. Moreover, the comparison results with conventional proportion-integration-differentiation controller have demonstrated the feasibility and efficacy of the proposed extended state Kalman filter-based model predictive controller in both set-point tracking and disturbance rejection.


2021 ◽  
Vol 18 (3) ◽  
pp. 172988142110110
Author(s):  
Mingcong Li ◽  
Chen Guo ◽  
Haomiao Yu

This article focuses on the problem of path following for underactuated unmanned surface vehicles (USVs) considering model uncertainties and time-varying ocean currents. An extended state observer (ESO)-based integral line-of-sight (ILOS) with an integral sliding mode adaptive fuzzy control scheme is proposed as the main control framework. First, a novel ESO is employed to estimate the surge and sway velocities based on the kinetic model, which are difficult to measure directly. Then, the adaptive ILOS guidance law is proposed, in which the integral vector is incorporated into the adaptive method to estimate the current velocities. Meanwhile, an improved fuzzy algorithm is introduced to optimize the look-ahead distance. Second, the controller is extended to deal with the USV yaw and surge velocity signal tracking using the integral sliding mode technique. The uncertainties of the USV are approximated via the adaptive fuzzy method, and an auxiliary dynamic system is presented to solve the problem of actuator saturation. Then, it is proved that all of the error signals in the closed-loop control system are uniformly ultimately bounded. Finally, a comparative simulation substantiates the availability and superiority of the proposed method for ESO-based ILOS path following of USV.


2021 ◽  
Vol 28 (2) ◽  
pp. 18-26
Author(s):  
Ligang Li ◽  
Zhiyuan Pei ◽  
Jiucai Jin ◽  
Yongshou Dai

Abstract In order to improve the accuracy and robustness of path following control for an Unmanned Surface Vehicle (USV) suffering from unknown and complex disturbances, a variable speed curve path following a control method based on an extended state observer was proposed. Firstly, the effect of the environmental disturbances on the USV is equivalent to an unknown and time-varying sideslip angle, and the sideslip angle is estimated by using the extended state observer (ESO) and compensated in the Line of Sight (LOS) guidance law. Secondly, based on the traditional LOS guidance law, the design of the surge velocity guidance law is added to enable the USV to self-adjust the surge velocity according to the curvature of the curve path, thus further improving the tracking accuracy. Finally, the heading and speed controller of the USV is designed by using a sliding mode control to track the desired heading and speed accurately, and then the path following control of the USV’s curve path is realised. Simulation results verify the effectiveness of the proposed method.


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