scholarly journals Design of an Error-Based Adaptive Controller for a Flexible Robot Arm Using Dynamic Pole Motion Approach

2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
Ki-Young Song ◽  
Madan M. Gupta ◽  
Noriyasu Homma

Design of an adaptive controller for complex dynamic systems is a big challenge faced by the researchers. In this paper, we introduce a novel concept ofdynamic pole motion(DPM) for the design of an error-based adaptive controller (E-BAC). The purpose of this novel design approach is to make the system response reasonably fast with no overshoot, where the system may be time varying and nonlinear with only partially known dynamics. The E-BAC is implanted in a system as a nonlinear controller with two dominant dynamic parameters: the dynamic position feedback and the dynamic velocity feedback. For illustrating the strength of this new approach, in this paper we give an example of a flexible robot with nonlinear dynamics. In the design of this feedback adaptive controller, parameters of the controller are designed as a function of the system error. The position feedbackKp(e,t)and the velocity feedbackKv(e,t)are continuously varying and formulated as a function of the system errore(t). This approach for formulating the adaptive controller yields a very fast response with no overshoot.

1990 ◽  
Vol 2 (2) ◽  
pp. 91-96
Author(s):  
Yasuo Yoshida ◽  
◽  
Masato Tanaka

The reduction gear's friction strongly affects the dynamic characteristics of a one-link flexible robot arm. Experiments of open loop response by motor torque were performed in two cases of large and small values of the reduction gear's friction, and compared with simulation. The reduction gear's friction has both viscous and Coulomb aspects and can be approximately treated as an equivalent viscous friction. However, tip position control was very difficult in the case of large friction with an equivalent viscous friction. Experiments indicated that tip position feedback control was possible by using a dither signal and linearizing the non-linear friction.


1992 ◽  
Vol 114 (3) ◽  
pp. 428-435 ◽  
Author(s):  
Sabri Cetinkunt ◽  
Sijun Wu

A predictive adaptive control algorithm is developed for tip position control based on the zero-order-hold equivalence of the nondimensionalized dynamic model of a flexible robot arm. A lattice filter is utilized for the purpose of parameter identification. The proposed control scheme provides an optimal output feedback control and, together with the lattice filter parameter identifier, it forms a special self-tuning regulator. It is then compared with other methods, such as linear quadratic Gaussian and stable factorization. A stability criterion for this control algorithm is also presented. The effects of the actuator dynamics on the overall system response and stability are investigated. Actuator dynamics model parameters are chosen from the actual specifications provided by manufacturers.


1996 ◽  
Vol 118 (1) ◽  
pp. 167-172 ◽  
Author(s):  
P. Lucibello ◽  
F. Bellezza

A self-tuned version of a controller for asymptotic trajectory tracking of the end point of a two-link flexible robot arm is presented. The bounded solution to the inverse system, which is used in the control law, is tuned by the estimates of the unknown robot parameters, generated by a least square identification scheme. Soundness of the state of the adaptive controller is achieved by a stabilizing linear feedback from the output error, with fixed gains and robust with respect to variations of the parameters. This guarantees the total stability of the system, which is the main ingredient used in the proof of the controller properties, through a Lyapunov-like approach. The controller performance is finally illustrated by numerically simulating the tracking of an end point ramp under payload mass variations.


2011 ◽  
Vol 403-408 ◽  
pp. 5068-5075
Author(s):  
Fatma Zada ◽  
Shawket K. Guirguis ◽  
Walied M. Sead

In this study, a design methodology is introduced that blends the neural and fuzzy logic controllers in an intelligent way developing a new intelligent hybrid controller. In this design methodology, the fuzzy logic controller works in parallel with the neural controller and adjusting the output of the neural controller. The performance of our proposed controller is demonstrated on a motorized robot arm with disturbances. The simulation results shows that the new hybrid neural -fuzzy controller provides better system response in terms of transient and steady-state performance when compared to neural or fuzzy logic controller applications. The development and implementation of the proposed controller is done using the MATLAB/Simulink toolbox to illustrate the efficiency of the proposed method.


1988 ◽  
Vol 29 (3) ◽  
pp. 459-467 ◽  
Author(s):  
James D. Lee ◽  
Ben-Li Wang

Author(s):  
Peng Qi ◽  
Hongbin Liu ◽  
Lakmal Seneviratne ◽  
Kaspar Althoefer

Flexible robot arms have been developed for various medical and industrial applications because of their compliant structures enabling safe environmental interactions. This paper introduces a novel flexible robot arm comprising a number of elastically deformable planar spring elements arranged in series. The effects of flexure design variations on their layer compliance properties are investigated. Numerical studies of the different layer configurations are presented and finite Element Analysis (FEA) simulation is conducted. Based on the suspended platform’s motion of each planar spring, this paper then provides a new method for kinematic modeling of the proposed robot arm. The approach is based on the concept of simultaneous rotation and the use of Rodrigues’ rotation formula and is applicable to a wide class of continuum-style robot arms. At last, the flexible robot arms respectively integrated with two different types of compliance layers are prototyped. Preliminary test results are reported.


2018 ◽  
pp. 267-294
Author(s):  
Hongxing Li ◽  
C.L. Philip Chen ◽  
Han-Pang Huang

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