Modified Linear Active Disturbance Rejection Control for Uncertain Robot Manipulator Trajectory Tracking
TL;DR: The MLADRC is significantly characterized by the addition of feedforward control of reference angular acceleration, which helps robot manipulators keep up with target trajectories more accurately.
Abstract: To solve the problems of model uncertainties, dynamic coupling, and external disturbances, a modified linear active disturbance rejection controller (MLADRC) is proposed for the trajectory tracking control of robot manipulators. In the computer simulation, MLADRC is compared to the proportional-derivative (PD) controller and the regular linear active disturbance rejection controller (LADRC) for performance tests. Multiple uncertain factors such as friction, parameter perturbation, and external disturbance are sequentially added to the system to simulate an actual robot manipulator system. Besides, a two-degree-of-freedom (2-DOF) manipulator is constructed to verify the control performance of the MLADRC. Compared with the regular LADRC, MLADRC is significantly characterized by the addition of feedforward control of reference angular acceleration, which helps robot manipulators keep up with target trajectories more accurately. The simulation and experimental results demonstrate the superiority of the MLADRC over the regular LADRC for the trajectory tracking control.
Citations
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Journal Article•
TL;DR: In this article, the estimation ability of linear extended state observer (ESO) and the stability of the closed-loop system under the linear active disturbance rejection control (LADRC) were investigated.
42 citations
TL;DR: In this article , a robust control method based on adaptive neural network is proposed to improve the control accuracy and robustness of free-floating space robot, considering the uncertain factors such as load variation, external interference and joint flexibility in engineering practice.
8 citations
17 Jul 2022
TL;DR: In this paper , a real deep Lagrangian network (Real-DeLaN) is proposed to improve the performance of the manipulator by calculating the contact force on the end effector of a manipulator based on virtual displacement work.
Abstract: To meet the practical operation requirements of manipulators in industry, service and collaboration scenarios, trajectory tracking accuracy and system stability of manipulators are usually regarded as critical control objectives. This paper proposes a novel manipulator control method with three-level constraints, called the real deep Lagrangian network (Real-DeLaN). In this method, real data (also called physical data) are collected from the physical manipulator and utilized to train the Lagrangian dynamics network model to improve the migration ability from simulation to reality. The torque output of the dynamic model is corrected by the real-time calculation of friction in the network. The contact force on the end effector of the manipulator is compensated based on the principle of virtual displacement work. The experimental results show that Real-DeLaN can better control the joints to perform trajectory tracking, reduce the friction error of the manipulator, and show better anti-interference ability.
DOI•
01 Feb 2022
TL;DR: In this article , the stability and smoothness of trajectory planning and attitude control of the manipulator are studied, and different attitude interpolation methods are compared and analyzed, and spherical linear interpolation method is used to solve the problem of uneven velocity of the linear interpolations method.
Abstract: In this paper, the stability and smoothness of trajectory planning and attitude control of the manipulator are studied. The DH motion model of Kinova Jaco Gen-2 manipulator was established to solve the forward and inverse kinematics equations. Firstly, the third-order Bezier curve is designed to plan the trajectory of manipulator, which has good continuity and smoothness, and can control the workspace. Secondly, an attitude interpolation method based on quaternion is proposed. And different attitude interpolation methods are compared and analyzed, and spherical linear interpolation method is used to solve the problem of uneven velocity of the linear interpolation method. Finally, MATLAB robot toolbox is used to simulate and verify that the angle of each joint changes smoothly, and the trajectory of manipulator has good smoothness and stability based on Bezier curve and quaternion interpolation. According to the experimental results, the path planning based on the third order Bezier curve and spherical linear interpolation has a continuous smooth joint trajectory curve and a continuous joint angular velocity curve. The manipulator can move smoothly to the target point under the constraint of the end posture. Therefore, the trajectory planning method can be used as an ideal planning method for manipulator.
References
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04 Jun 2003
TL;DR: A new set of tools, including controller scaling, controller parameterization and practical optimization, is presented to standardize controller tuning, which moves controller tuning in the direction of science.
Abstract: A new set of tools, including controller scaling, controller parameterization and practical optimization, is presented to standardize controller tuning. Controller scaling is used to frequency-scale an existing controller for a large class of plants, eliminating the repetitive controller tuning process for plants that differ mainly in gain and bandwidth. Controller parameterization makes the controller parameters a function of a single variable, the loop-gain bandwidth, and greatly simplifies the tuning process. Practical optimization is defined by maximizing the bandwidth subject to the physical constraints, which determine the limiting factors in performance. Collectively, these new tools move controller tuning in the direction of science.
1,790 citations
"Modified Linear Active Disturbance ..." refers methods in this paper
...To simplify the tuning process, Gao [20] proposed a linear ADRC, i....
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...To simplify the tuning process, Gao [20] proposed a linear ADRC, i.e., LADRC, and replaced nonlinear ESO with a linear ESO (LESO)....
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...[20] Z. Gao, “Scaling and bandwidth-parameterization based controller tuning,” in Proceedings of the American Control Conference, pp. 4989–4996, Denver, CO, USA, June 2003....
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...According to the method of parameter bandwidthization proposed in [20], the MLADRC parameters are configured as...
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TL;DR: The adaptive backstepping control method and Lyapunov stability theory are used to prove the proposed controller can ensure all the signals in the systems are semiglobally uniformly ultimately bounded, and the output of the systems can track the reference signal closely.
Abstract: In this paper, the adaptive neural network (NN) tracking control problem is addressed for robot manipulators subject to dead-zone input. The control objective is to design an adaptive NN controller to guarantee the stability of the systems and obtain good performance. Different from the existing results, which used NN to approximate the nonlinearities directly, NNs are employed to identify the originally designed virtual control signals with unknown nonlinear items in this paper. Moreover, a sequence of virtual control signals and real controller are designed. The adaptive backstepping control method and Lyapunov stability theory are used to prove the proposed controller can ensure all the signals in the systems are semiglobally uniformly ultimately bounded, and the output of the systems can track the reference signal closely. Finally, the proposed adaptive control strategy is applied to the Puma 560 robot manipulator to demonstrate its effectiveness.
276 citations
TL;DR: The proposed ESO-based adaptive controller theoretically achieves an excellent asymptotic tracking performance when time-invariant modeling uncertainties exist and preserves the performance results of both control methods while overcoming their practical performance limitations.
Abstract: Velocity signal is difficult to obtain in practical electrohydraulic servomechanisms Even though it can be approximately derived via numerical differentiation on position measurement, the strong noise effect will greatly deteriorate the achievable control performance Hence, how to design a high-performance tracking controller without velocity measurement is of practical significance In this paper, a practical adaptive tracking controller without velocity measurement is proposed for electrohydraulic servomechanisms To estimate the unmeasurable velocity signal, an extended state observer (ESO) that also provides an estimate of the mismatched disturbance is constructed The ESO uses the unknown parameter estimates updated by a novel adaptive law, which only depends on the actual position and desired trajectory Moreover, the matched parametric uncertainty is also handled by online parameter adaptation and the matched disturbance is suppressed via a robust control law The proposed ESO-based adaptive controller theoretically achieves an excellent asymptotic tracking performance when time-invariant modeling uncertainties exist In the presence of time-variant modeling uncertainties, guaranteed transient performance and prescribed final tracking accuracy can also be achieved The proposed control strategy bridges the gap between the adaptive control and disturbance observer-based control without using the velocity signal and preserves the performance results of both control methods while overcoming their practical performance limitations Comparative experiments are performed on an actual servovalve-controlled double-rod hydraulic actuator to verify the superiority of the proposed control strategy
162 citations
118 citations
"Modified Linear Active Disturbance ..." refers background in this paper
...*e dynamic control is designed according to the dynamic characteristics of robot manipulators, so it can make the control quality of the system better [1, 2]....
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TL;DR: A new robust controller is developed for robot manipulator based on an integrating between a novel self-tuning fuzzy proportional-integral-derivative (PID)-nonsingular fast terminal sliding mode control (STF-PID-NFTSM) and a time delay estimation (TDE).
Abstract: In this work, a new robust controller is developed for robot manipulator based on an integrating between a novel self-tuning fuzzy proportional-integral-derivative (PID)-nonsingular fast terminal sliding mode control (STF-PID-NFTSM) and a time delay estimation (TDE). A sliding surface based on the PID-NFTSM is designed for robot manipulators to get multiple excited features such as faster transient response with finite time convergence, lower error at steady-state and chattering elimination. However, the system characteristics are hugely affected by the selection of the PID gains of the controller. In addition, the design of the controller requires an exact dynamics model of the robot manipulators. In order to obtain effective gains for the PID sliding surface, a fuzzy logic system is employed and in order to get an estimation of the unknown dynamics model, a TDE algorithm is developed. The innovative features of the proposed approach, i.e., STF-PID-NFTSM, is verified when comparing with other up-to-date advanced control techniques on a PUMA560 robot.
89 citations