Robot based on task-space dynamical model

Yime, Eugenio; Saltarén, Roque; García, Cecilia; Sabater, J. M.

doi:10.1049/iet-cta.2010.0622

Cited by 7 publications

(6 citation statements)

References 18 publications

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“…To demonstrate the performance of the proposed control scheme, the adaptive fuzzy sliding-mode controller is first implemented on integrated simulation environment based on platform and eight upper and lower limbs of the parallel manipulator [44], i.e., erefore, the dynamic Equation ( 6) can be written in a linear regression matrix form as Similarly, the following dynamic control equation can be written as where Θ is the estimate value of the uncertainty dynamics parameter Θ.…”

Section: Simulation and Discussionmentioning

confidence: 99%

Adaptive Fuzzy Sliding Mode Control for a 3-DOF Parallel Manipulator with Parameters Uncertainties

et al. 2020

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Parallel manipulators possess the advantages of being compact structure, high stiffness, stability and high accuracy, so such parallel manipulators have been widely employed in application fields as diverse as parallel kinematic machine, motion simulator platform, medical rehabilitation device, and so on. Due to the complexity of the closed-loop structural system, an accurate dynamic model is very difficult to be derived in the absence of some uncertainties parameters and external disturbances. In order to improve the trajectory tracking accuracy with time-varying and nonlinear parameters, this paper addresses the design and implement of adaptive fuzzy sliding mode control (AFSMC) for a three-degree-of-freedom (DOF) parallel manipulator, where internal force term can be linearly separated into a regression matrix and a parameter vector that contains the estimated errors. Furthermore, fuzzy inference unit is utilized to modify the gain parameters in real-time by using the state feedback from the task space and the adaptive law is performed to update uncertainties in dynamic parameters. The proposed controller is deduced in the sense of Lyapunov theory to guarantee the stability while improving the trajectory tracking performance. Finally, simulation experiment results demonstrate that the proposed control method is insensitive to uncertainties and disturbances and permits to decrease the requirement for the bound of these uncertainties, which validate the effectiveness of the developed control method and exhibit good trajectory tracking performance compared with sliding mode control (SMC) and fuzzy sliding model control (FSMC).

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Section: Simulation and Discussionmentioning

confidence: 99%

Adaptive Fuzzy Sliding Mode Control for a 3-DOF Parallel Manipulator with Parameters Uncertainties

et al. 2020

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“…The experimental platform is shown in Figure 2. The virtual work equation, according to the authors of [27], is:…”

Section: Dynamic Model Of Stewart-gough Flight Simulation Platformmentioning

confidence: 99%

Performance Evaluation of Stewart-Gough Flight Simulator Based on L1 Adaptive Control

Zhao

2021

Applied Sciences

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In the design of the six degrees of freedom (6-DOF) flight simulation system, the unmodeled dynamic, transient performance and steady-state performance of the system are generally concerned. Considering that the model of flight simulation system is highly nonlinear and requires high response speed and high stability, this paper applies L1 adaptive controller to the control of flight simulation platform. The controller has a low-pass filter in feedback loop to avoid high frequencies in the control signals, and the required transient performance can be enhanced by increasing the adaptive gain, which can improve the transient, stability, and smoothness of the flight simulator platform. The performance of the L1 adaptive controller is obtained by comparison with the traditional model reference adaptive controller (MRAC). In addition to maintaining the good transient response of MRAC, the L1 adaptive controller improves the stability of the system. The output amplitude of the actuator is reduced by 39.95%, which effectively reduces the performance requirements of the actuator. Some additional experimental evaluations are carried out to show the performance of the controller.

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“…El análisis dinámico del robot paralelo plano de cinco barras se realizó utilizando la misma metodología aplicada para un robot paralelo espacial StewartGough en los trabajos [26,27] en el espacio de la tarea; mientras que en el presente trabajo el modelo dinámico se calcula en el espacio articular o de las juntas. La ecuación dinámica se expresa mediante el modelo: (44) donde M, C y g son la matriz de masa generalizada, la matriz de Coriollis y el vector gravitacional en el espacio articular, respectivamente, y es el vector de fuerza (y/o momento) generalizada o externa.…”

Section: Análisis Dinámicounclassified

“…La primera sección explica el diseño realizado y el prototipo construido. Posteriormente, se introducen los modelos cinemático y dinámico, este último se realiza con el enfoque empleado en [26,27] para un robot espacial Stewart-Gough en el espacio de la tarea, pero en este trabajo se desarrolla en el espacio articular. Se continúa con simulaciones de control por par calculado y experimentos de control dinámico por par calculado.…”

Section: Introductionunclassified

Computed torque control of a 2-RR planar parallel robot // Control por par calculado de un robot paralelo planar 2-RR

2017

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RESUMENSe presentan el diseño, la construcción y el control de un mecanismo planar de cinco eslabones con cinco juntas de revoluta y dos grados de libertad. Se implementó el control por par calculado en el espacio articular para lograr una trayectoria deseada. Se desarrolló la cinemática de posición y de velocidad, tanto directa como inversa, y únicamente la cinemática inversa de aceleración como parámetro requerido en la ley de control. El enfoque escogido para este robot paralelo es ventajoso puesto que permite obtener una ecuación dinámica similar al modelamiento convencional de robots seriales, lo cual facilita la implementación de técnicas de control no lineal. La validez del enfoque planteado y la funcionalidad del controlador se verifican experimentalmente mediante la generación de una trayectoria circular por el efector. A pesar de la concordancia entre la simulación y los resultados experimentales, se sugiere como futuro trabajo el cambio en la estrategia de control para compensar efectos no modelados del sistema.Palabras clave: CTC; Dinámica paralela; Control de robots; Mecanismo 5 barras; Robot planar 2-RR. ABSTRACTThe design, construction and control of a two degree-of-freedom planar mechanism with five bar and five joints are presented. Computed control torque strategy in the joint space was implemented in order to fulfill a kinematic task by the end effector. It was required the position and velocity kinematic full analysis of the robot, both direct and reverse. The control law needed only the acceleration reverse kinematic formulation. The dynamic model of this parallel robot was obtained using an advantageous approach that is typical of serial robots, making easier the non-linear control techniques implementation. The validity of the dynamic model approach and the functionality of the controller are experimentally verified in the generation of a circular path by the end effector. Although there is accordance between the simulation and the experimental results, future work to implement other non-linear control strategies are suggested given the no modeled effects present in the system.

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Robot based on task-space dynamical model

Cited by 7 publications

References 18 publications

Adaptive Fuzzy Sliding Mode Control for a 3-DOF Parallel Manipulator with Parameters Uncertainties

Adaptive Fuzzy Sliding Mode Control for a 3-DOF Parallel Manipulator with Parameters Uncertainties

Performance Evaluation of Stewart-Gough Flight Simulator Based on L1 Adaptive Control

Computed torque control of a 2-RR planar parallel robot // Control por par calculado de un robot paralelo planar 2-RR

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