scholarly journals Enhanced trajectory tracking using optimally combined feedforward plant inversion and feedforward closed loop inversion

2021 ◽  
Author(s):  
Leopoldo Jetto ◽  
Valentina Orsini
Keyword(s):  
Trajectory Tracking ◽  
Closed Loop

scholarly journals Closed-Loop Control for Trajectory Tracking of a Microparticle Based on Input-to-State Stability Through an Electromagnetic Manipulation System

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 46537-46545
Author(s):  
Weicheng Ma ◽  
Min Xu ◽  
Zhixiong Zhong ◽  
Xiangpeng Li ◽  
Zhijie Huan
Keyword(s):  
Trajectory Tracking ◽  
Closed Loop ◽  
Closed Loop Control ◽  
Loop Control ◽  
Manipulation System

Trajectory tracking control of electric sail with input uncertainty and saturation constraint

2016 ◽  
Vol 39 (7) ◽  
pp. 1007-1016 ◽  
Author(s):  
Yu Wang ◽  
Bingxiu Bian
Keyword(s):  
Solar Wind ◽  
Trajectory Tracking ◽  
Closed Loop ◽  
Sliding Mode ◽  
Input Saturation ◽  
Asymptotically Stable ◽  
Closed Loop System ◽  
Saturation Constraints ◽  
Non Linear System ◽  
Input Saturation Constraints

The electric sail (ES) is a novel propellantless propulsion concept, which extracts the solar wind momentum by repelling the positively charged ions. Due to the difficulty of attitude adjustment by the large flexible structure and the uncertainty of ion density, velocity and electron temperature by solar wind, there exist thrust input uncertainty and saturation with time-varying bounds for ES. The trajectory tracking problem for ES in three-dimensional (3-D) space is studied, and the composite sliding mode control scheme with corresponding guidance strategy is proposed for the single-input–multiple-output (SIMO) non-linear system. The hierarchical sliding surfaces are constructed with an auxiliary design system to analyse the effect of input saturation constraints and decouple the SIMO non-linear system to reduce the control complexity. Also, the disturbance estimation based on a super-twisting algorithm is employed to decrease the switch chattering and improve the system robustness. It is proved that all the sliding mode surfaces are asymptotically stable, and all the signals of the closed-loop system are bounded with input saturation constraints. Furthermore, all the signals are converging to zero and the closed-loop system is asymptotically stable without saturation. Finally, the simulation demonstrates the proposed composite sliding mode control is fit for ES 3-D trajectory tracking.

Trajectory Tracking of Underactuated Surface Vessels Based on Hierarchical Sliding Mode

2014 ◽  
Author(s):  
Cheng Liu ◽  
Zaojian Zou ◽  
Jianchuan Yin
Keyword(s):  
Trajectory Tracking ◽  
Degrees Of Freedom ◽  
Closed Loop ◽  
Sliding Mode ◽  
Underactuated System ◽  
Sliding Mode Controller ◽  
Control Field ◽  
Surface Vessels ◽  
Underactuated Surface Vessels ◽  
Hierarchical Sliding Mode

Trajectory tracking is an importance practice in ship motion control field. It attracts more attention recently due to its difficulties. Trajectory tracking requires the ship to arrive pinpoint location at exact time. It is a underactuated system because the degrees of freedom of control inputs are fewer than the degrees of freedom that needed to be controlled. In this paper, a hierarchical sliding mode controller and a common sliding mode controller are proposed to deal with the trajectory tracking problem of underactuated surface vessels. Simulation results validate the tracking performance of the proposed controllers. The closed-loop stability is testified by the Lyapunov stability theorem.

Double Closed-Loop General Type-2 Fuzzy Sliding Model Control for Trajectory Tracking of Wheeled Mobile Robots

2019 ◽  
Vol 21 (7) ◽  
pp. 2032-2042 ◽  
Author(s):  
Songyi Dian ◽  
Jixia Han ◽  
Rui Guo ◽  
Shengchuan Li ◽  
Tao Zhao ◽  
...  
Keyword(s):  
Mobile Robots ◽  
Trajectory Tracking ◽  
General Type ◽  
Closed Loop ◽  
Wheeled Mobile Robots ◽  
Model Control ◽  
Fuzzy Sliding Model Control

A Dual-Mode Model Predictive Control Algorithm Trajectory Tracking in Discrete-Time Nonlinear Dynamic Systems

2017 ◽  
Vol 139 (4) ◽  
Author(s):  
Asad A. Ul Haq ◽  
Michael E. Cholette ◽  
Dragan Djurdjanovic
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Discrete Time ◽  
Dynamic Systems ◽  
Trajectory Tracking ◽  
Closed Loop ◽  
Linear Control ◽  
Nonlinear Dynamic Systems ◽  
Closed Loop System ◽  
Dual Mode

In this paper, a dual-mode model predictive/linear control method is presented, which extends the concept of dual-mode model predictive control (MPC) to trajectory tracking control of nonlinear dynamic systems described by discrete-time state-space models. The dual-mode controller comprises of a time-varying linear control law, implemented when the states lie within a sufficiently small neighborhood of the reference trajectory, and a model predictive control strategy driving the system toward that neighborhood. The boundary of this neighborhood is characterized so as to ensure stability of the closed-loop system and terminate the optimization procedure in a finite number of iterations, without jeopardizing the stability of the closed-loop system. The developed controller is applied to the central air handling unit (AHU) of a two-zone variable air volume (VAV) heating, ventilation, and air conditioning (HVAC) system.

Research on the Cooperative Control Method for Trajectory Tracking of Automatic Guided Vehicle Based on Dynamic Position/Force

2013 ◽  
Vol 457-458 ◽  
pp. 1298-1302 ◽  
Author(s):  
Xuan Zuo Liu ◽  
Qiao Yun Yan ◽  
Fei Yun Tang
Keyword(s):  
Trajectory Tracking ◽  
Cooperative Control ◽  
Closed Loop ◽  
Control Structure ◽  
Sliding Mode ◽  
Closed Loop Control ◽  
Control Input ◽  
External Interference ◽  
Loop Control ◽  
Automatic Guided Vehicle

AbstractConsidering the influence of the dynamic characteristic of automatic guided vehicle (AGV) on trajectory tracking controlling, double closed loop control structure is proposed to realize the position/force cooperative control. The outer loop controlling uses backstepping to design corresponding position controller for kinematics model of AGV, while the inner control uses the integral sliding mode controlling. Self-adaptive controlling law is used to estimate the uncertain external interference in the driving force controller and stability of AGV trajectories tracking proof is proposed. In order to make the system achieve better control performance and prevent the occurrence of severe wobble, the hyperbolic tangent function in the control law of sliding mode control replaces the sign function to ensure a continuously smooth control input and states of the system. In the Matlab/simulink environment, tracking a given splayed trajectory generated by the S function to verify the double closed loop control structure and the effectiveness of the control algorithm proposed in this paper.

Trajectory tracking of an omnidirectional mobile robot using Gaussian process regression

2021 ◽  
Vol 69 (8) ◽  
pp. 656-666
Author(s):  
Hannes Eschmann ◽  
Henrik Ebel ◽  
Peter Eberhard
Keyword(s):  
Mobile Robots ◽  
Gaussian Process ◽  
Trajectory Tracking ◽  
Closed Loop ◽  
Gaussian Process Regression ◽  
Industrial Applications ◽  
Loop Control ◽  
Common Control ◽  
Model Extension ◽  
Flexible Operation

Abstract Mobile robots are enjoying increasing popularity in a number of different automation tasks. Omnidirectional mobile robots especially allow for a very flexible operation. They are able to accelerate in every direction, regardless of their orientation. In this context, we developed our own robot platform for research on said types of robots. It turns out that these mobile robots show interesting behaviour, which commonly used models for omnidirectional mobile robots fail to reproduce. As the exact sources and structures of mismatches are still unknown, non-parametric Gaussian process regression is used to develop a data-based model extension of the robot. A common control task for industrial applications is trajectory tracking, where a robot needs to follow a predefined path, for example in a warehouse, as close as possible in space and time. Appropriate feed-forward solutions for the data-based model are developed and finally leveraged in closed-loop control via nonlinear model predictive control. In real-world experiments, the results are compared to commonly used proportional position-based feedback. This novel contribution builds upon the preliminary work in [7] but, for the first time, includes also closed-loop (trajectory) tracking.

scholarly journals Formation Control and Distributed Goal Assignment for Multi-Agent Non-Holonomic Systems

2019 ◽  
Vol 9 (7) ◽  
pp. 1311 ◽  
Author(s):  
Wojciech Kowalczyk
Keyword(s):  
Mobile Robots ◽  
Collision Avoidance ◽  
Trajectory Tracking ◽  
Formation Control ◽  
Closed Loop ◽  
Linear Feedback ◽  
Planning Problem ◽  
Closed Loop Control ◽  
Loop Control ◽  
Loop Control System

This paper presents control algorithms for multiple non-holonomic mobile robots moving in formation. Trajectory tracking based on linear feedback control is combined with inter-agent collision avoidance. Artificial potential functions (APF) are used to generate a repulsive component of the control. Stability analysis is based on a Lyapunov-like function. Then the presented method is extended to include a goal exchange algorithm that makes the convergence of the formation much more rapid and, in addition, reduces the number of collision avoidance interactions. The extended method is theoretically justified using a Lyapunov-like function. The controller is discontinuous but the set of discontinuity points is of zero measure. The novelty of the proposed method lies in integration of the closed-loop control for non-holonomic mobile robots with the distributed goal assignment, which is usually regarded in the literature as part of trajectory planning problem. A Lyapunov-like function joins both trajectory tracking and goal assignment analyses. It is shown that distributed goal exchange supports stability of the closed-loop control system. Moreover, robots are equipped with a reactive collision avoidance mechanism, which often does not exist in the known algorithms. The effectiveness of the presented method is illustrated by numerical simulations carried out on the large formation of robots.

Sign in / Sign up

Export Citation Format

Share Document