Predictive functional control for a parallel robot

Albán, Óscar Andrés Vivas; Poignet, P.; Pierrot-Deseilligny, Marc

doi:10.1109/iros.2003.1249292

Cited by 25 publications

(13 citation statements)

References 20 publications

(2 reference statements)

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“…The dynamic model equation (12) in the task space also satisfies the similar structural properties with the dynamic model of the open-chain system or a 2-DOF serial manipulator as follows [8]:…”

Section: Dynamic Modelingmentioning

confidence: 98%

“…When the system parameters are separated from the dynamic model equation (12), we get a linear parameterization expression of the system parameters of the dynamic model equation (12), as follows:…”

Section: Linear Parameterization Expression Of the Dynamic Modelmentioning

confidence: 99%

“…In this section, we will design the NA controller based on the dynamic model equation (12) in the task space for the parallel manipulator. The system parameters can be estimated by using the gradient descent algorithm based on the linear parameterization expression in (13).…”

Section: Nonlinear Adaptive Controllermentioning

confidence: 99%

“…Kim et al [11] presented a robust nonlinear controller for the Stewart platform. Vivas and Poignet [12] designed a predictive controller for a H4 parallel manipulator, and Shang et al [13] developed an optimal controller for a 2-DOF redundantly actuated parallel manipulator. These dynamic controllers can improve the performance of the traditional dynamic controllers, but also require higher accuracy of the dynamic models.…”

Section: Introductionmentioning

confidence: 99%

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Nonlinear adaptive task space control for a 2-DOF redundantly actuated parallel manipulator

Shang

Cong

2009

Nonlinear Dyn

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A nonlinear adaptive (NA) controller in the task space is developed for the trajectory tracking of a 2-DOF redundantly actuated parallel manipulator. The dynamic model with nonlinear friction is established in the task space for the parallel manipulator, and the linear parameterization expression of the dynamic model is formulated. Based on the dynamic model, a new control law including adaptive dynamics compensation, adaptive friction compensation and error elimination items is designed. After defining a quadratic performance index, the parameter update law is derived with the gradient descent algorithm. The stability of the parallel manipulator system is proved by the Lyapunov theorem, and the convergence of the tracking error and the error rate is proved by the Barbalat's lemma. The NA controller is implemented in the trajectory tracking experiments of an actual 2-DOF redundantly actuated parallel manipulator, and the experiment results are compared with the APD controller.

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Section: Dynamic Modelingmentioning

confidence: 98%

Section: Linear Parameterization Expression Of the Dynamic Modelmentioning

confidence: 99%

Section: Nonlinear Adaptive Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Nonlinear adaptive task space control for a 2-DOF redundantly actuated parallel manipulator

Shang

Cong

2009

Nonlinear Dyn

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“…The traditional dynamic controllers include the augmented PD (APD) controller [10,11], and the computed-torque (CT) controller [12,13]. Recently, some advanced controllers with performance indicators were presented for parallel manipulators, such as the predictive controller [14,15], the adaptive controller [16,17], and the synchronization controller [18]. These controllers can improve the performances of the trajectory tracking further.…”

Section: Introductionmentioning

confidence: 99%

Dynamic model based nonlinear tracking control of a planar parallel manipulator

Shang

Cong²,

Jiang³

2009

Nonlinear Dyn

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Based on the dynamic model, a novel nonlinear tracking controller is developed to overcome the nonlinear dynamics and friction of a planar parallel manipulator. The dynamic model is formulated in the active joint space, and the active joint friction is described with the Coulomb + viscous friction model. A nonlinear tracking controller is designed to eliminate the tracking error by using the power function. The nonlinear tracking controller is proven to guarantee asymptotic convergence to zero of both the tracking error and error rate with the Barbalat's lemma. The trajectory tracking experiment of the proposed controller is implemented on an actual five-bar planar parallel manipulator both at the lowspeed and high-speed motion. Moreover, the control performances of the proposed controller are compared with the results of the augmented PD (APD) controller.

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Adaptive predictive functional control for networked control systems with random delays

Wang

Fei

Han

2011

Int. J. Autom. Comput.

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Nowadays, more and more field devices are connected to the central controller through a serial communication network such as fieldbus or industrial Ethernet. Some of these serial communication networks like controller area network (CAN) or industrial Ethernet will introduce random transfer delays into the networked control systems (NCS), which causes control performance degradation and even system instability. To address this problem, the adaptive predictive functional control algorithm is derived by applying the concept of predictive functional control to a discrete state space model with variable delay. The method of estimating the networkinduced delay is also proposed to facilitate the control algorithm implementing. Then, an NCS simulation research based on TrueTime simulator is carried out to validate the proposed control algorithm. The numerical simulations show that the proposed adaptive predictive functional control algorithm is effective for NCS with random delays.

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Predictive functional control for a parallel robot

Cited by 25 publications

References 20 publications

Nonlinear adaptive task space control for a 2-DOF redundantly actuated parallel manipulator

Nonlinear adaptive task space control for a 2-DOF redundantly actuated parallel manipulator

Dynamic model based nonlinear tracking control of a planar parallel manipulator

Adaptive predictive functional control for networked control systems with random delays

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