Design and Validation of Fractional-Order Control Scheme for DC Servomotor via Internal Model Control Approach

2017 ◽  
Vol 36 (1) ◽  
pp. 49-60 ◽  
Author(s):  
Sahaj Saxena ◽  
Yogesh V. Hote
Keyword(s):  
Fractional Order ◽  
Internal Model ◽  
Internal Model Control ◽  
Fractional Order Control ◽  
Control Approach ◽  
Control Scheme ◽  
Model Control ◽  
Dc Servomotor

scholarly journals Experimental validation of fractional order internal model controller design on buck and boost converter

2020 ◽  
pp. 002029402092226
Author(s):  
Shivam Jain ◽  
Yogesh V Hote ◽  
Padmalaya Dehuri ◽  
Deeksha Mittal ◽  
Vishwanatha Siddhartha
Keyword(s):  
Fractional Order ◽  
Internal Model ◽  
Experimental Validation ◽  
Boost Converter ◽  
Internal Model Control ◽  
Control Technique ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Control Scheme ◽  
Model Control

In this paper, fractional order internal model control technique is formulated for non-ideal dc–dc buck and boost converter. The fractional order internal model control approach integrates the concept of Commande Robuste d’Ordre Non Entier principle for tuning a fractional order filter with internal model control scheme. The final controller can be expressed as a series combination of proportional integral derivative controller and a fractional order low pass filter. To assess the robustness of the proposed fractional order internal model control scheme, both the servo response and regulatory response of the dc–dc converters are investigated in the presence of disturbances. The efficacy of fractional order internal model control technique is demonstrated via comparison with 2 degrees of freedom internal model control scheme. Furthermore, an experimental validation of fractional order internal model control is conducted on laboratory setup, and a dSPACE 1104 microcontroller is used for hardware implementation. The simulation results and the hardware validation are a testimony to the effectiveness of fractional order internal model control technique.

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.

Design of a neural internal model control system for a robot

Robotica ◽  
2000 ◽  
Vol 18 (5) ◽  
pp. 505-512 ◽  
Author(s):  
D. T. Pham ◽  
Şahin Yildirim
Keyword(s):  
Internal Model ◽  
Neural Model ◽  
Internal Model Control ◽  
Bp Algorithm ◽  
Recurrent Networks ◽  
Neural Controller ◽  
Inverse Control ◽  
Control Scheme ◽  
Model Control ◽  
Two Degree Of Freedom

This paper describes the design of an Internal Model Control (IMC) system for a planar two-degree-of-freedom robot. IMC was investigated as an alternative to the basic inverse control scheme which is difficult to implement. The proposed IMC system consisted of a forward internal neural model of the robot, a neural controller and a conventional feedback controller, all of which were realised easily. Both the neural model and the neural controller were based on recurrent networks which were trained using the backpropagation (BP) algorithm. The paper presents the results obtained with two types of recurrent networks as well as a conventional PID system.

The Inverted Decoupling Based Fractional Order Two-Input-Two-Output IMC Controller

2017 ◽  
Author(s):  
Dazi Li ◽  
Xingyu He
Keyword(s):  
Frequency Domain ◽  
Fractional Order ◽  
Disturbance Rejection ◽  
Internal Model ◽  
Design Method ◽  
Internal Model Control ◽  
Order System ◽  
Single Input Single Output ◽  
Integer Order ◽  
Model Control

Many processes in the industry can be modeled as fractional order, research on the fractional order become more and more popular. Usually, controllers such as fractional order PID (FOPID) or fractional active disturbance rejection control (FADRC) are used to control single-input-single-output (SISO) fractional order system. However, when it comes to fractional order two-input-two-output (TITO) processes, few research focus on this. In this paper, a new design method for fractional order control based on multivariable non-internal model control with inverted decoupling is proposed to handle non-integer order two-input-two-output system. The controller proposed in this paper just has two parameters to tune compared with the five parameters of the FOPID controller, and the controller structure can be achieved by internal model control (IMC) method which means it is easy to implement. The parameters tuning method used in this paper is based on frequency domain strategy. Compared with integer order situation, fractional order method is more complex, because the calculation of the frequency domain characteristics is difficult. The controller proposed in this paper is robust to process gain variations, what’s more, it provides ideal performance for both set point-tracking and disturbance rejection. Numerical results are given to show the performance of the proposed controller.

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