Composite controller design for a 6DOF Stewart nanoscale platform

Ting, Yung; Li, Chun-Chung; Nguyen, Tho Van

doi:10.1016/j.precisioneng.2013.01.012

Cited by 17 publications

(7 citation statements)

References 7 publications

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“…Ting et al relied on Lyapunov theory to prove the stability of a PID controller optimally tuned by genetic algorithm (GA). 22 Experimental results done in the presence of external load conditions showed that a satisfactory level of accuracy was maintained. Omran and Kassem proposed a similar optimization method to tune the parameters of a PD controller applied on a 6-DOF Stewart platform.…”

Section: Introductionmentioning

confidence: 91%

Emulation of pilot control behavior across a Stewart platform simulator

Eftekhari

Karimpour

2018

Robotica

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SUMMARYThis paper presents a model-based controller consisting of a feedback linearization scheme and a state-dependent proportional derivative (PD) controller adapted to a parallel flight simulator Stewart mechanism. This parallel robot is considered to emulate motions of highly maneuverable aircrafts, which require well-trained pilots. The simulations are based upon a reduced-model prototype built in order to verify kinematic design aspects and control laws. Indeterminacies in the mass distribution of the system will generally affect model-based controllers, necessitating compensation or the employment of robust control methods. Through introducing the pilot's sensorial feedback of acceleration, the pilot's behavior in giving commands is emulated via an optimization process, which tunes the controller coefficients accordingly. Stability of the designed control system is guaranteed via the Lyapunov approach. To further explore the system through perilous flight scenarios, three pre-designed maneuvers are selected as test cases. It is expected that closed-loop control tasks in which a pilot tracks a target, while at the same time the controller rejects disturbances and adapts itself to the pilot's progressive skills, are ameliorated through this arrangement. Numerical results show that the proposed method is found robust in the training process in conditions of parameters indeterminacy.

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Section: Introductionmentioning

confidence: 91%

Emulation of pilot control behavior across a Stewart platform simulator

Eftekhari

Karimpour

2018

Robotica

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“…According to the output torque of the motor and the manipulator, the motor-mechanism model is formulated from Eqs. (23) and (19) as follows:…”

Section: Actuator Dynamicsmentioning

confidence: 99%

“…In practice, manipulators are controlled to track a desired trajectory that is planned in their workspace. In recent years, various advanced control techniques have been performed and successfully implemented to control 6-DOF SPS Stewart parallel manipulators accurately, such as proportional integral derivative PID control, 23,24 linear quadratic regulator (LQR) control, 25 model-based control, 26−29 H∞ adaptive control, 30−31 computed torque control, 32 fuzzy control 33 and sliding mode control (SMC). 34−37 Among these control techniques, SMC is a variable structure and also an efficient robust control method for nonlinear systems with unknown loads and un-modelled dynamics.…”

Section: Introductionmentioning

confidence: 99%

A comparative study of two model-based control techniques for the industrial manipulator

Dumlu¹,

Erenturk²,

Kaleli³

et al. 2016

Robotica

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SUMMARYIn this paper, design, analysis and real-time trajectory tracking control of a 6-degree of freedom revolute spherical-spherical type parallel manipulator, actuated by six hybrid stepper motors, has been studied. Two different control approaches have been used to improve the trajectory tracking performance of the designed manipulator. The first approach considered a single input-single output (SISO) linear quadratic regulator (LQR) for trajectory tracking control of the manipulator. Another controller type based on a nonlinear sliding mode controller method has been utilized to take decoupled dynamic approximation model of the manipulator into account and to improve tracking performance of the manipulator. Real-time experimental results for the two different control techniques have been verified. Finally, according to the results, the nonlinear sliding mode controller method has improved the tracking performance of the designed manipulator.

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“…There are interactions in evolution among the components in (2); therefore, the information of the system is implied in the process of the development of each component; thus a certain change rule can be found and extracted from the system. As long as delay time and the embedding dimension are known, phase space can be reconstructed from (2).…”

Section: Phase Space Reconstructionmentioning

confidence: 99%

“…There are a lot of uncertainty factors and nonlinear mechanisms in the process of actual control application of sixdegree-of-freedom parallel Stewart platform [1][2][3]. It is very obvious that vibration characteristics of the new type of passive super static vibratory platform [4] are of prodigious complexity.…”

Section: Introductionmentioning

confidence: 99%

Chaos Analysis on the Acceleration Control Signals of the Piezoelectric Actuators in the Stewart Platform

Jiaqiang

Qian

et al. 2016

Shock and Vibration

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In order to solve the nonlinear mechanism in the process of actual control application of six-degree-of-freedom parallel Stewart platform, the chaos theory was applied in the paper to analyze the acceleration control signal. The research included correlation dimension calculation by use of the G-P method, the maximum Lyapunov coefficient of the acceleration control signal, and Kolmogorov entropies of the acceleration control signal. The results show that the acceleration signals are of chaos characteristics, and there are lots of influencing factors to the acceleration variables.

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Composite controller design for a 6DOF Stewart nanoscale platform

Cited by 17 publications

References 7 publications

Emulation of pilot control behavior across a Stewart platform simulator

Emulation of pilot control behavior across a Stewart platform simulator

A comparative study of two model-based control techniques for the industrial manipulator

Chaos Analysis on the Acceleration Control Signals of the Piezoelectric Actuators in the Stewart Platform

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