Research and Design of Fractional-Order PID Controller for Inertial Stabilized Platform via Internal Model Control

2021 ◽  
Author(s):  
Yaqiong Zhang ◽  
Jiandu Guo ◽  
Yi Liu ◽  
Jing Zhou ◽  
Yu Sun
Keyword(s):  
Fractional Order ◽  
Pid Controller ◽  
Internal Model ◽  
Internal Model Control ◽  
Model Control ◽  
Stabilized Platform ◽  
Fractional Order Pid ◽  
Research And Design ◽  
Fractional Order Pid Controller

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.

scholarly journals Kalman Filter and Variants for Estimation in 2DOF Serial Flexible Link and Joint Using Fractional Order PID Controller

2021 ◽  
Vol 11 (15) ◽  
pp. 6693
Author(s):  
Sagar Gupta ◽  
Abhaya Pal Singh ◽  
Dipankar Deb ◽  
Stepan Ozana
Keyword(s):  
Kalman Filter ◽  
Fractional Order ◽  
Pid Controller ◽  
Degree Of Freedom ◽  
Flexible Link ◽  
System Properties ◽  
Tool Position ◽  
Fractional Order Pid ◽  
Two Degree Of Freedom ◽  
Fractional Order Pid Controller

Robotic manipulators have been widely used in industries, mainly to move tools into different specific positions. Thus, it has become necessary to have accurate knowledge about the tool position using forward kinematics after accessing the angular locations of limbs. This paper presents a simulation study in which an encoder attached to the limbs gathers information about the angular positions. The measured angles are applied to the Kalman Filter (KF) and its variants for state estimation. This work focuses on the use of fractional order controllers with a Two Degree of Freedom Serial Flexible Links (2DSFL) and Two Degree of Freedom Serial Flexible Joint (2DSFJ) and undertakes simulations with noise and a square wave as input. The fractional order controllers fit better with the system properties than integer order controllers. The KF and its variants use an unknown and assumed process and measurement noise matrices to predict the actual data. An optimisation problem is proposed to achieve reasonable estimations with the updated covariance matrices.

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