scholarly journals Revisiting the simplified internal model control tuning rules for low-order controllers: feedforward controller

2020 ◽  
Vol 14 (12) ◽  
pp. 1612-1618
Author(s):  
Carlos Rodríguez ◽  
Ernesto Aranda-Escolástico ◽  
José Luis Guzmán ◽  
Manuel Berenguel ◽  
Tore Hägglund
Keyword(s):  
Internal Model ◽  
Internal Model Control ◽  
Model Control ◽  
Feedforward Controller ◽  
Tuning Rules ◽  
Low Order

Internal Model Control Using EWMA for a Wedge-Type Piezoelectric Motor

2007 ◽  
Author(s):  
Yung Ting ◽  
Hui-Yi Feng ◽  
Han-Chih Hsieh ◽  
Li-Yen Wang ◽  
Chun-Chung Li ◽  
...  
Keyword(s):  
Internal Model ◽  
Dead Zone ◽  
Friction Model ◽  
Internal Model Control ◽  
Nonlinear Phenomenon ◽  
Piezoelectric Motor ◽  
Time Operation ◽  
Control Command ◽  
Model Control ◽  
Feedforward Controller

Wedge-type piezoelectric motor is easily subject to disturbance such as friction, preload and temperature change, which influences the performance significantly and reduces the positioning accuracy and reliability. In this study, Exponentially Weighted Moving Average (EWMA) method is considered to use for the velocity-feedback loop, which is included in an Internal Model Control (IMC) to achieve a Run-to-Run IMC (RtR-IMC) control structure. Such control scheme is able to adapt the control command following a changing system dynamics so that it can improve the tracking accuracy and robustness. Friction is also a problem of generating dead-zone area and causes serious nonlinear phenomenon especially while moving direction is changed. A feedforward controller is designed based on the friction model. Moreover, temperature increase appears in long-time operation, which is another factor influential to piezoelectric motor’ performance. Instead of using the Single EWMA method, which cannot efficiently deal with such environmental drift problem, a Double EWMA algorithm is developed. Practical experiment is carried out to verify the performance by using these proposed methods. It concludes that the Double EWMA associated with the friction-model-based feedforward controller is superior to the other methods.

Optimality of Internal Model Control Tuning Rules

2004 ◽  
Vol 43 (24) ◽  
pp. 7951-7958 ◽  
Author(s):  
Jose Alvarez-Ramirez ◽  
Rosendo Monroy-Loperena ◽  
Alejandra Velasco ◽  
Rafael Urrea
Keyword(s):  
Internal Model ◽  
Internal Model Control ◽  
Model Control ◽  
Tuning Rules

scholarly journals Data-driven Control of the Activated Sludge Process: IMC plus Feedforward Approach

2016 ◽  
Vol 11 (4) ◽  
pp. 522 ◽  
Author(s):  
Jose David Rojas ◽  
Orlando Arrieta ◽  
Montse Meneses ◽  
Ramon Vilanova
Keyword(s):  
Activated Sludge ◽  
Substrate Concentration ◽  
Internal Model ◽  
Internal Model Control ◽  
Data Driven ◽  
Activated Sludge Process ◽  
Virtual Reference ◽  
Model Free ◽  
Model Control ◽  
Feedforward Controller

<p>In the work presented in this paper, data-driven control is used to tune an Internal Model Control. Despite the fact that it may be contradictory to apply a model-free method to a model-based controller, this methodology has been successfully applied to a Activated Sludge Process (ASP) based wastewater treatment. In addition a feedforward controller over the influent substrate concentration was also computed using the virtual reference feedback tuning and applied to the same wastewater process to see the effect over the dissolved oxygen and the substrate concentration at the effluent.</p>

Disturbance Rejection of Nanopositioner Using Internal Model Control

2012 ◽  
Vol 2 (4) ◽  
pp. 1-7
Author(s):  
Sheilza Aggarwal ◽  
Maneesha Garg ◽  
Akhilesh Swarup
Keyword(s):  
Disturbance Rejection ◽  
Internal Model ◽  
Internal Model Control ◽  
Model Control

A novel IMC-FOF design for four wheel steering systems of distributed drive electric vehicles

2021 ◽  
pp. 095440702110314
Author(s):  
Yan Ti ◽  
Kangcheng Zheng ◽  
Wanzhong Zhao ◽  
Tinglun Song
Keyword(s):  
Fractional Order ◽  
Electric Vehicles ◽  
Internal Model ◽  
Rear Wheel ◽  
Internal Model Control ◽  
Steering Angle ◽  
Comparison Results ◽  
Model Control ◽  
Tracking Ability ◽  
Internal Model Controller

To improve handling and stability for distributed drive electric vehicles (DDEV), the study on four wheel steering (4WS) systems can improve the vehicle driving performance through enhancing the tracking capability to desired vehicle state. Most previous controllers are either a large amount of calculation, or requires a lot of experimental data, these are relatively time-consuming and laborious. According to the front and rear wheel steering angle of DDEV can be distributed independently, a novel controller named internal model controller with fractional-order filter (IMC-FOF) for 4WS systems is proposed and studied in this paper. The IMC-FOF is designed using the internal model control theory and compared with IMC and PID controller. The influence of time constant and fractional-order parameters which is optimized using quantum genetic algorithms (QGA) on tracking ability of vehicle state are also analyzed. Using a production vehicle as an example, the simulation is performed combining Matlab/Simulink and CarSim. The comparison results indicated that the proposed controller presents performance to distribute the front and rear wheel steering angle for ensuring better tracking capability to desired vehicle state, meanwhile it possesses strong robustness.

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