Virtual Decomposition Based Modeling for Multi-DOF Manipulator With Flexible Joint

Xia, Kerui; Xing, Hongjun; Ding, Liang; Gao, Haibo; Liu, Guangjun; Deng, Zongquan

doi:10.1109/access.2019.2919749

Cited by 8 publications

(4 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In all cases the overshoot was negligible. In Figures 4,6,8,10,12,14,16,18 the variations of the control inputs are moderate.…”

Section: Simulation Testsmentioning

confidence: 93%

“…So far, several control approaches have been applied to robots with flexible joints and to robots with compliant actuators. One can note for instance sliding‐mode control, backstepping control, or model predictive control 11‐16 . Often, nonlinear state‐observers are used in such a type of robotic manipulators, so as to either estimate nonlinear state vector elements or to estimate disturbance forces and torques 17‐20 .…”

Section: Introductionmentioning

confidence: 99%

“…One can note for instance sliding-mode control, backstepping control, or model predictive control. [11][12][13][14][15][16] Often, nonlinear state-observers are used in such a type of robotic manipulators, so as to either estimate nonlinear state vector elements or to estimate disturbance forces and torques. [17][18][19][20] On the other side, due to strong nonlinearities in the dynamic model of these robots and due to their multivariable state-space structure, little has been done towards the solution of the related nonlinear optimal control problem.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Nonlinear optimal control for multi‐DOF robotic manipulators with flexible joints

Rigatos

Abbaszadeh

2021

Optim Control Appl Methods

View full text Add to dashboard Cite

A main problem in the control of flexible-joint robots and in the precise positioning of their end-effector, is synchronization between the turn angles of the robots' joints and the turn angles of the motors that provide actuation to these joints. In this article, a nonlinear optimal (H-infinity) control method is proposed for multi-DOF robotic manipulators with flexible joints. The dynamic model of these robotic manipulators is shown to be underactuated and to satisfy differential flatness properties. The state-space description of these robots undergoes approximate linearization around a temporary operating point which is recomputed at each iteration of the control method. The linearization procedure makes use of first-order Taylor-series expansion and relies on the computation of Jacobian matrices. For the approximately linearized model of these multi-DOF robotic systems an H-infinity feedback controller is designed. This controller stands for the solution of the robots' optimal control problem under model uncertainty and external disturbances. The computation of the controller's feedback gain requires the solution of an algebraic Riccati equation, which is performed again at each time-step of the control algorithm. The stability properties of the control scheme are proven trough Lyapunov analysis. First, it is confirmed that the controller satisfies the H-infinity tracking performance criterion which ascertains its robustness. Moreover, it is proven that the control loop is globally asymptotically stable. Finally, to implement sensorless control for such robotic systems the H-infinity Kalman Filter is used as a robust state estimator. The proposed control method for multi-DOF robotic manipulators with flexible joints retains the advantages of linear optimal control, that is fast and accurate tracking of its reference setpoints under moderate variations of the control inputs.

show abstract

“…In all cases the overshoot was negligible. In Figures 4,6,8,10,12,14,16,18 the variations of the control inputs are moderate.…”

Section: Simulation Testsmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Nonlinear optimal control for multi‐DOF robotic manipulators with flexible joints

Rigatos

Abbaszadeh

2021

Optim Control Appl Methods

View full text Add to dashboard Cite

show abstract

“…11,12 The virtual decomposition control uses the dynamics of subsystems (rigid links and joints) to conduct control design, while maintaining the L 2 stability of each subsystems and convergence of the entire robotic system. [13][14][15] Usually, high-order derivatives of joint moments are required in this method.…”

Section: Introductionmentioning

confidence: 99%

A model-based PID-like motion control method for flexible-joint manipulator with harmonic drives

Yang

Liu

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part C:

View full text Add to dashboard Cite

A novel control method is proposed to achieve high trajectory tracking precision, for flexible-joint manipulators. The method consists of three major parts: joint torque generator, joint torque tracker and motor position controller. The expected torque is generated by a PID controller based on the manipulator’s rigid dynamics model. In the torque tracker, motor position is corrected in both feedback and feedforward ways. Finally, the motor position controller is responsible to track the corrected motor trajectory to achieve the torque and position control. To suppress nonlinear friction, a disturbance observer is also implemented. The method is verified with a seven-DOFs manipulator. Simulation and experimental results show that, the proposed method is efficient and practical to suppress vibration caused by flexible transmission and disturbance due to friction. As result, high positioning accuracy is achieved in a certain wide working speed range. The no-load motion accuracy is better than 0.6 mm with a manipulator whose length is 1.8 meter, and the motion error is less than 3 mm with loading of four kilograms.

show abstract

Flatness‐based control in successive loops for mechatronic motion transmission systems

Rigatos,

Pomares,

Siano

et al. 2024

Asian Journal of Control

View full text Add to dashboard Cite

Mechatronic systems with nonlinear dynamics are met in motion transmission applications for vehicles and robots. In this article, the control problem for the nonlinear dynamics of mechatronic motion transmission systems is solved with the use of a flatness‐based control approach which is implemented in successive loops. The state‐space model of these systems is separated into a series of subsystems, which are connected between them in cascading loops. Each one of these subsystems can be viewed independently as a differentially flat system, and control about it can be performed with inversion of its dynamics as in the case of input–output linearized flat systems. In this chain of subsystems, the state variables of the subsequent ( )‐th subsystem become virtual control inputs for the preceding ‐th subsystem and so on. In turn, exogenous control inputs are applied to the last subsystem and are computed by tracing backwards the virtual control inputs of the preceding subsystems. The whole control method is implemented in successive loops, and its global stability properties are also proven through Lyapunov stability analysis. The validity of the control method is confirmed in the following two case studies: (a) control of a permanent magnet linear synchronous motor (PMLSM)‐actuated vehicle's clutch and (ii) control of a multi‐Degrees of Freedom (multi‐DOF) flexible joint robot.

show abstract

Virtual Decomposition Based Modeling for Multi-DOF Manipulator With Flexible Joint

Cited by 8 publications

References 29 publications

Nonlinear optimal control for multi‐DOF robotic manipulators with flexible joints

Nonlinear optimal control for multi‐DOF robotic manipulators with flexible joints

A model-based PID-like motion control method for flexible-joint manipulator with harmonic drives

Flatness‐based control in successive loops for mechatronic motion transmission systems

Contact Info

Product

Resources

About