PD control with computed feedforward of robot manipulators: a design procedure

Kelly, Rafael; Salgado, Ricardo Menezes

doi:10.1109/70.313108

Cited by 82 publications

(47 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Theorem 1 Using adaptive control algorithm (3) for the system (2), if at least one follower has access to q 0 , and there exist positive-definite matrices K 1 , …”

Section: Adaptive Tracking Control Algorithm With External Uncertain mentioning

confidence: 99%

“…Dynamics and control of Lagrange systems have been a significant topic over the past decades to both the scientific and the engineering communities. A wide variety of control strategies have been proposed and investigated for Lagrange systems which include linear and nonlinear feedback control [1], PD-type control [1,2], timedelay feedback control [3], and the open-loop optimization control [4][5][6], among many others. In recent years, coordinated control of networked Lagrange systems has attracted increasing attention from various fields of science and engineering.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Distributed adaptive tracking backstepping control in networked nonidentical Lagrange systems

Xiang

Zhou

2014

Nonlinear Dyn

View full text Add to dashboard Cite

In this paper, the problem of adaptive tracking control in networked nonidentical Lagrange systems is investigated via backstepping schemes. Two distributed tracking control algorithms are designed for directed network topology graph with a spanning tree, where both the leader's position and its velocity are assumed to be varying. Some generic criteria for adaptive tracking control algorithms with uncertain external disturbance and parametric uncertainties are presented. It is shown that the proposed algorithms only require a subset of the followers access to leader's position. Furthermore, the adaptive control algorithm for uncertain external disturbance systems is robust, and it can avoid online measurement for neighbors' velocities and efficiently eliminate the chattering during tracking. The results show that all followers can track the leader's dynamics. Two examples and their simulations show the effectiveness of the proposed algorithms.

show abstract

“…Theorem 1 Using adaptive control algorithm (3) for the system (2), if at least one follower has access to q 0 , and there exist positive-definite matrices K 1 , …”

Section: Adaptive Tracking Control Algorithm With External Uncertain mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distributed adaptive tracking backstepping control in networked nonidentical Lagrange systems

Xiang

Zhou

2014

Nonlinear Dyn

View full text Add to dashboard Cite

show abstract

“…Furthermore, this assumption is fundamental for the local stability proofs presented in refs. [3][4][5] and the global uniform asymptotic stability proof presented by Santibáñez and Kelly. 1 In this respect, it is important to say that some studies 6,7 have stressed that neglecting the actuator dynamics may result in closed-loop system performance degradation or even instability.…”

Section: Introductionmentioning

confidence: 97%

PD control with feedforward compensation for rigid robots actuated by brushless DC motors

2010

View full text Add to dashboard Cite

Link to this article: http://journals.cambridge.org/abstract_S0263574710000329 How to cite this article: R. V. Carrillo-Serrano, V. M. Hernández-Guzmán and V. Santibáñez (2011). PD control with feedforward compensation for rigid robots actuated by brushless DC motors. Robotica, 29, pp 507-514 SUMMARYThis work is concerned with trajectory tracking of robots when the electrical dynamics of the brushless DC motor actuators is considered. It is shown that proportionalderivative (PD) control with feedforward compensation, plus some additional terms to cope with the electrical dynamics, ensures state boundedness. Furthermore, tracking error converges to zero from arbitrarily large initial conditions if controller gains are correctly chosen. Under mild assumptions, this controller reduces to the well-known PD control with feedforward compensation when implemented according to torque control, a successful industrial practice. Thus, it is explained, for the first time, why this strategy works well in applications.

show abstract

“…In addition, sufficiently large gains are undesirable in practice. To deal with the latter problem, [5] develops a design procedure that sets the lower bounds on the proportional and derivative gains that guarantee stability of the closed-loop system. The procedure is carried out under the assumption that the robot dynamic model is known and the desired trajectory is properly chosen.…”

mentioning

confidence: 99%

“…The procedure is carried out under the assumption that the robot dynamic model is known and the desired trajectory is properly chosen. That is to Manuscript received September 4, 1995; revised October 1, 1996 and April 5,1997.…”

mentioning

confidence: 99%

Decentralized adaptive fuzzy control of robot manipulators

Jin

1998

IEEE Trans. Syst., Man, Cybern. B

View full text Add to dashboard Cite

Abstract-This paper develops a decentralized adaptive fuzzy control scheme for robot manipulators via a combination of genetic algorithm and gradient method. The controller for each link consists of a feedforward fuzzy torque-computing system and a feedback fuzzy PD system. The feedforward fuzzy system is trained and optimized off-line by an improved genetic algorithm, that is to say, not only the parameters but also the structure of the fuzzy system are self-organized. Because genetic algorithm can operate successfully without the system model, no exact inverse dynamics of the robot system are required. The feedback fuzzy PD system, on the other hand, is tuned on-line using gradient method. In this way, the proportional and derivative gains are adjusted properly to keep the closed-loop system stable. The proposed controller has the following merits: 1) it needs no exact dynamics of the robot systems and the computation is time-saving because of the simple structure of the fuzzy systems; and 2) the controller is insensitive to various dynamics and payload uncertainties in robot systems. These are demonstrated by analyses of the computational complexity and various computer simulations.

show abstract

PD control with computed feedforward of robot manipulators: a design procedure

Cited by 82 publications

References 10 publications

Distributed adaptive tracking backstepping control in networked nonidentical Lagrange systems

Distributed adaptive tracking backstepping control in networked nonidentical Lagrange systems

PD control with feedforward compensation for rigid robots actuated by brushless DC motors

Decentralized adaptive fuzzy control of robot manipulators

Contact Info

Product

Resources

About