Asymptotic tracking control scheme for mechanical systems with external disturbances and friction

2010 ◽  
Vol 73 (7-9) ◽  
pp. 1293-1302 ◽  
Author(s):  
Lili Cui ◽  
Huaguang Zhang ◽  
Bing Chen ◽  
Qingling Zhang
Keyword(s):  
Tracking Control ◽  
Mechanical Systems ◽  
External Disturbances ◽  
Control Scheme ◽  
Asymptotic Tracking

Nonlinear Perfect Tracking Control for a Robot Arm with Uncertainties Using Operator-Based Robust Right Coprime Factorization Approach

2015 ◽  
Vol 27 (1) ◽  
pp. 49-56 ◽  
Author(s):  
Aihui Wang ◽  
◽  
Dongyun Wang ◽  
Haiquan Wang ◽  
Shengjun Wen ◽  
...  
Keyword(s):  
Tracking Control ◽  
Structural Parameters ◽  
Control System Design ◽  
Robot Arm ◽  
External Disturbances ◽  
Factorization Approach ◽  
Coprime Factorization ◽  
Tracking Condition ◽  
Control Scheme ◽  
Universal Stability

<div class=""abs_img""><img src=""[disp_template_path]/JRM/abst-image/00270001/06.jpg"" width=""300"" />Plant uncertainties compensation</div> In this paper, a robust nonlinear perfect tracking control for a robot arm with uncertainties is proposed by using operator-based robust right coprime factorization approach. In general, there exist unknown modelling errors in measuring structural parameters of the robot arm and external disturbances in real situations. In the present control system design, the effect of the modelling errors and disturbances on the system performance is considered to be uncertainties of the robot arm dynamics. Considering the uncertainties, a robust nonlinear perfect tracking control using operator-based robust right coprime factorization is investigated. That is, first, considering the unknown uncertain plant generates limitations in obtaining the so-called universal stability and tracking conditions, the effect of uncertain plant is compensated by designed operator-based feedback control scheme. Second, a new perfect tracking condition is proposed for improving the trajectory of the robot arm. Finally, the effectiveness of the designed system is confirmed by simulation results. </span>

scholarly journals Fixed-Time Trajectory Tracking Control of Autonomous Surface Vehicle with Model Uncertainties and Disturbances

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Jiawen Cui ◽  
Haibin Sun
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Sliding Mode ◽  
Fixed Time ◽  
Convergence Time ◽  
Model Uncertainties ◽  
External Disturbances ◽  
Trajectory Tracking Control ◽  
Integral Sliding Mode ◽  
Control Scheme

The issue of fixed-time trajectory tracking control for the autonomous surface vehicles (ASVs) system with model uncertainties and external disturbances is investigated in this paper. Particularly, convergence time does not depend on initial conditions. The major contributions include the following: (1) An integral sliding mode controller (ISMC) via integral sliding mode surface is first proposed, which can ensure that the system states can follow the desired trajectory within a fixed time. (2) Unknown external disturbances are absolutely estimated by means of designing a fixed-time disturbance observer (FTDO). By combining the FTDO and ISMC techniques, a new control scheme (FTDO-ISMC) is developed, which can achieve both disturbance compensation and chattering-free condition. (3) Aiming at reconstructing the unknown nonlinear dynamics and external disturbances, a fixed-time unknown observer (FTUO) is proposed, thus providing the FTUO-ISMC scheme that finally achieves trajectory tracking of ASVs with unknown parameters. Finally, simulation tests and detailed comparisons indicate the effectiveness of the proposed control scheme.

Robust Anti-Swing Adaptive Fuzzy Tracking Control for Tower Crane Systems With Both Dead-Zone Band and Time-Delays Uncertainties

2015 ◽  
Author(s):  
Tzu Sung Wu ◽  
Mansour Karkoub
Keyword(s):  
Time Delays ◽  
Closed Loop ◽  
Dead Zone ◽  
Mechanical Systems ◽  
Control Technique ◽  
External Disturbances ◽  
Adaptive Fuzzy ◽  
Tower Crane ◽  
Control Scheme ◽  
Actuator Nonlinearities

Complex mechanical systems, such as tower cranes, are known to be highly nonlinear, under-actuated, and non-colocated, which makes their closed-loop control very challenging. The interconnected components of these systems undergo complex dynamic phenomena, such as friction, which lead to energy or momentum transmission delays. The complexity of such systems is further complicated by external disturbances and nonlinearities resulting from using hydraulic and/or electrical actuators, mechanical joints, gears, etc., which result in the formation of dead-zones, backlash, and hysteresis. A dead-zone, which constitutes a significant non-smooth nonlinearity, severely limits the performance of many mechanical systems such as the tower crane. Previous works on the control of tower cranes were based on accurate determination of their actuated states. In this work, a robust control technique based on adaptive fuzzy theory is investigated for anti-swing and trajectory tracking of tower crane systems. The system is subject to uncertainties in parameter parameters, time delays, external disturbances, and unknown actuator nonlinearities. The unknown actuator nonlinearities, from the jib and tower motors, are characterized by dead-zone bands (as opposed to the typical crisp dead-zone functions). First, fuzzy logic systems with on-line adaptations are utilized to evaluate the unknown nonlinear functions. The proposed control scheme uses the H∞ control technique to develop compensators to overcome the effects of parameter variations, time delays, external disturbances, and unknown actuator dead-zone band nonlinearities. The proposed control scheme ensures the stability of the closed-loop system and achieves desired tracking precision such that the states of the tower crane system are ultimately uniformly bounded (UUB) and guarantees an H∞ norm bound constraint on disturbance attenuation for all admissible uncertainties based on the Lyapunov criterion. Simulation results show the validity of this approach for the tower crane system.

scholarly journals Robust Tracking Control for Robotic Manipulator via Fuzzy Logic System andH∞Approaches

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Kun Mu ◽  
Cong Liu ◽  
Jinzhu Peng
Keyword(s):  
Fuzzy Logic ◽  
Tracking Control ◽  
Robotic Manipulator ◽  
Fuzzy Logic System ◽  
Torque Control ◽  
Robust Tracking ◽  
Robust Tracking Control ◽  
External Disturbances ◽  
Control Scheme ◽  
Logic System

Based on fuzzy logic system (FLS) andH∞control methodologies, a robust tracking control scheme is proposed for robotic system with uncertainties and external disturbances. FLS is employed to implement the framework of computed torque control (CTC) method via its approximate capability which is used to attenuate the nonlinearity of robotic manipulator. The robustH∞control can guarantee robustness to parametric and dynamics uncertainties and also attenuate the effect of immeasurable external disturbances entering the system. Moreover, a quadratic stability approach is used to reduce the conservatism of the conventional robust control approach. It can be guaranteed that all signals in the closed-loop are bounded by employing the proposed robust tracking control. The validity of the proposed control scheme is shown by simulation of a two-link robotic manipulator.

scholarly journals Fault-Tolerant Tracking Control for a Descriptor System under an Unknown Input Disturbances

Electronics ◽  
2021 ◽  
Vol 10 (18) ◽  
pp. 2247
Author(s):  
Norbert Kukurowski ◽  
Marcin Pazera ◽  
Marcin Witczak
Keyword(s):  
Tracking Control ◽  
Fault Tolerant ◽  
Control Process ◽  
Descriptor System ◽  
Unknown Input ◽  
Laboratory System ◽  
External Disturbances ◽  
Input Disturbance ◽  
Control Scheme ◽  
Estimation Scheme

The paper proposes a fault-tolerant tracking control scheme based on a robust observer for a descriptor system. Thus, it is assumed that the described system can be simultaneously occupied by an unknown input disturbance, along with an actuator and sensor faults. Additionally, it is natural to assume that the unknown input disturbance cannot be estimated, which makes the control process more difficult. Moreover, the proposed descriptor system is also occupied by external disturbances. Thus, the robust stability of the proposed control and estimation scheme was guaranteed by using H∞ performance. Consequently, the DC servo-motor laboratory system was used to confirm the correctness and effectiveness of the proposed fault-tolerant tracking control scheme.

Robust neural network control of MEMS gyroscope using adaptive sliding mode compensator

Robotica ◽  
2014 ◽  
Vol 34 (3) ◽  
pp. 497-512 ◽  
Author(s):  
Juntao Fei ◽  
Yuzheng Yang
Keyword(s):  
Neural Network ◽  
Upper Bound ◽  
Tracking Control ◽  
Sliding Mode ◽  
Tracking Error ◽  
Modeling Error ◽  
External Disturbances ◽  
Mems Gyroscope ◽  
Control Scheme ◽  
The Impact

SUMMARYA new robust neural sliding mode (RNSM) tracking control scheme using radial basis function (RBF) neural network (NN) is presented for MEMS z-axis gyroscope to achieve robustness and asymptotic tracking error convergence. An adaptive RBF NN controller is developed to approximate and compensate the large uncertain system dynamics, and a robust compensator is designed to eliminate the impact of NN modeling error and external disturbances for guaranteeing the asymptotic stability property. Moreover, another RBF NN is employed to learn the upper bound of NN modeling error and external disturbances, so the prior knowledge of the upper bound of system uncertainties is not required. All the adaptive laws in the RNSM control system are derived in the same Lyapunov framework, which can guarantee the stability of the closed loop system. Comparative numerical simulations for an MEMS gyroscope are investigated to verify the effectiveness of the proposed RNSM tracking control scheme.

Asymptotic Tracking Control of Freeway Traffic Density via Ramp Metering

2012 ◽  
Vol 253-255 ◽  
pp. 1686-1690
Author(s):  
Xiao Hong Fan ◽  
Yong Feng Ju
Keyword(s):  
Tracking Control ◽  
Flow System ◽  
Ramp Metering ◽  
Traffic Density ◽  
Unknown Parameters ◽  
External Disturbances ◽  
Freeway Traffic ◽  
Control Gain ◽  
Asymptotic Tracking ◽  
Ramp Signal

The method of the robust integral of the sign of the error was used to design the ramp signal for traffic flow system of freeway with uncertaines . Uncertain terms are allowed to be modelled or unmodelled.The unmodelled terms in the model were estimated by there bounded differential . Compared with other ramp metering method, this controller is designed without approximately linearizing the complicated nonlinear model and requiring the upper bound of unmodelled terms known .The control gain is reduced .The method is verified to be robust subject to both external disturbances and unmodelled dynamics ,and to be adaptive to unknown parameters . The numerical example shows good tracking performance .

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