scholarly journals On Synergistic Integration of Adaptive Dithering Based Internal Model Control for Hysteresis Compensation in Piezoactuated Nanopositioner

2015 ◽  
Vol 2015 ◽  
pp. 1-19 ◽  
Author(s):  
Saikat Kumar Shome ◽  
Mangal Prakash ◽  
Sourav Pradhan ◽  
Arpita Mukherjee
Keyword(s):  
Internal Model ◽  
Tracking Error ◽  
Integrated Approach ◽  
Adaptive Controller ◽  
Internal Model Control ◽  
Cell Manipulation ◽  
Force Microscopy ◽  
Hysteresis Compensation ◽  
Rate Dependent ◽  
Model Control

Piezoelectric-stack actuated platforms are very popular in the parlance of nanopositioning with myriad applications like micro/nanofactory, atomic force microscopy, scanning probe microscopy, wafer design, biological cell manipulation, and so forth. Motivated by the necessity to improve trajectory tracking in such applications, this paper addresses the problem of rate dependent hysteretic nonlinearity in piezoelectric actuators (PEA). The classical second order Dahl model for hysteresis encapsulation is introduced first, followed by the identification of parameters through particle swarm optimization. A novel inversion based feedforward mechanism in combination with a feedback compensator is proposed to achieve high-precision tracking wherein the paradoxical concept of noise as a performance enhancer is introduced in the realm of PZAs. Having observed that dither induced stochastic resonance in the presence of periodic forcing reduces tracking error, dither capability is further explored in conjunction with a novel output harmonics based adaptive control scheme. The proposed adaptive controller is then augmented with an internal model control based approach to impart robustness against parametric variations and external disturbances. The proposed control law has been employed to track multifrequency signals with consistent compensation of rate dependent hysteresis of the PEA. The results indicate a greatly improved positioning accuracy along with considerable robustness achieved with the proposed integrated approach even for dual axis tracking applications.

Improved IMC-filter design and IMC-PI equivalence: Application to quadrotor under gust of wind

2020 ◽  
Vol 234 (9) ◽  
pp. 1060-1072
Author(s):  
Yasser Bouzid ◽  
Houria Siguerdidjane ◽  
Elmehdi Zareb
Keyword(s):  
Internal Model ◽  
Filter Design ◽  
Autonomous Vehicle ◽  
Tracking Error ◽  
Experimental Tests ◽  
Pi Controller ◽  
Internal Model Control ◽  
Model Control ◽  
Tuning Strategy ◽  
The Mathematical Model

As known, internal model control is equivalent to a PI or a PID controller provided that the mathematical model associated to the process to be controlled is of first or second order respectively. So, to go beyond these particular cases and to make an extension in bringing more theoretical results, the article proposes a method to reach the equivalence between an internal model control and a PI controller regardless of the model order. To this end, the key idea consists of using a specific filter that exhibits superior robustness level compared to the classical filter and further leads to get a structure of a PI controller whatever the order of the model is. The developed procedure constitutes the main contribution of this article. To meet given set of specifications, the controller parameters are tuned through a straightforward analytic way using the dynamics of the tracking error. The proposed tuning strategy constitutes another contribution of the article. Furthermore, to evaluate the efficiency level of this procedure, an application to control an autonomous vehicle is described and the simulation results are shown to be satisfactory confirmed by a series of experimental tests.

Weighted Internal Model Control-Proportional Integral Derivative Control Scheme Via Fractional Gradient Descent Algorithm

2020 ◽  
Vol 142 (12) ◽  
Author(s):  
Shivam Jain ◽  
Yogesh V. Hote
Keyword(s):  
Internal Model ◽  
Gradient Descent ◽  
Controller Design ◽  
Convex Combination ◽  
Adaptive Controller ◽  
Internal Model Control ◽  
Model Control ◽  
Gradient Descent Algorithm ◽  
Individual Candidate ◽  
The Individual

Abstract An adaptive controller design technique based on internal model control (IMC) scheme is proposed in this paper. Multiple IMC controllers having different values of filter time constants and exhibiting widely different performance are combined via weight update rule. The weight update rule, formulated via convex combination of integral and fractional order gradient descent algorithms, assigns time varying weights to individual candidate controllers to obtain an enhanced performance over the individual candidate controllers. The beauty of the proposed technique is that it employs the simplicity of one degree-of-freedom (1DOF) IMC structure to achieve an improved performance over existing 2DOF control schemes. The efficacy of the proposed technique is demonstrated via three illustrative examples and via experimental validation on the hardware setup of dc servosystem. An extensive comparative analysis in terms of simulation plots and performance indices offers a testimony to the effectiveness of the proposed scheme.

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