A variable-order adaptive controller for a manipulator with a sliding flexible link

1991 ◽  
Vol 7 (6) ◽  
pp. 818-827 ◽  
Author(s):  
Y.-K. Kim ◽  
J.S. Gibson
Author(s):  
Pawel Konrad Orzechowski ◽  
Tsu-Chin Tsao ◽  
James Steve Gibson

In many adaptive control applications, especially where the recursive-least-squares (RLS) algorithms are used, the real-time implementation of high order adaptive filters for estimating the disturbance dynamics is computationally intensive. The delay associated with the computational burden is usually either underestimated as no delay or overestimated as one sample delay in the control system design and analysis. For a stochastic disturbance dynamics, the H2 optimal control performance for the case of one-step delay is worse than that of no delay due to the nonminimum phase plant zero introduced by the delay. The optimal performance for a fractional delay is bounded between these two extremes. The paper investigates the effect of the fractional computational delay on a variable order adaptive controller based on a recursive least-squares adaptive lattice filter. The trade-off between the adaptive filter order and the computational delay is analyzed and evaluated by an example.


Robotica ◽  
2016 ◽  
Vol 35 (7) ◽  
pp. 1562-1584 ◽  
Author(s):  
Fareh Raouf ◽  
Saad Mohamad ◽  
Saad Maarouf ◽  
Bettayeb Maamar

SUMMARYThis paper presents an adaptive distributed control strategy for n-serial-flexible-link manipulators. The proposed adaptive controller is used for flexible-link-manipulators: (1) to solve the tracking control problem in the joint space, and (2) to reduce vibrations of the links. The dynamical model of flexible link manipulators is reorganized to take the form of n interconnected subsystems. Each subsystem has a one-joint and one-link pair. The system parameters are deemed to be unknown. The adaptive distributed strategy controls one subsystem in each step, starting from the last one. The nth subsystem is controlled by assuming that the remaining subsystems are stable. Then, proceeding backward to the (n-1)th system, the same strategy is applied, and so on, until the first subsystem is reached. The gradient-based estimator is used to estimate the parameters of each subsystem. The control law of the ith subsystem uses its own estimated parameters and the estimated parameters of all upper level subsystems. The global stability of the error dynamics is proved using Lyapunov approach. This algorithm was implemented in real time on a two-flexible-link manipulator, and a comparison with the non-adaptive version shows the effectiveness of this approach.


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