Design and Application of Self-Adaptive Controller Based on Q Series PLC

2013 ◽  
Vol 694-697 ◽  
pp. 2134-2138
Author(s):  
Ying Hao ◽  
Hao Yuan ◽  
Feng Dong
Keyword(s):  
Control Strategy ◽  
Control Algorithm ◽  
Adaptive Controller ◽  
Performance Comparison ◽  
The Self ◽  
Controller Performance ◽  
Adaptive Control Strategy ◽  
Beer Production ◽  
Adaptive Pid Control ◽  
Self Adaptive

The control of simulated beer production line is implemented based on a Q series PLC controller of Mitsubishi company. The mathematical modeling method and the self-adaptive control strategy are introduced. The Mitsubishi PX-Developer software is adopted to design, run and debug online the PID and self-adaptive PID controller. Performance comparison between the two kinds of control strategy is made. It is shown that the self-adaptive PID control algorithm has the superiority.

scholarly journals FRACTIONAL-ORDER PASSIVITY-BASED ADAPTIVE CONTROLLER FOR A ROBOT MANIPULATOR TYPE SCARA

Fractals ◽  
2020 ◽  
Vol 28 (08) ◽  
pp. 2040008
Author(s):  
J. E. LAVÍN-DELGADO ◽  
S. CHÁVEZ-VÁZQUEZ ◽  
J. F. GÓMEZ-AGUILAR ◽  
G. DELGADO-REYES ◽  
M. A. RUÍZ-JAIMES
Keyword(s):  
Fractional Order ◽  
Control Strategy ◽  
Control Method ◽  
Robot Manipulator ◽  
Adaptive Controller ◽  
Performance Comparison ◽  
External Disturbances ◽  
Scara Robot ◽  
Comparison Results ◽  
Lagrange Formalism

In this paper, a novel fractional-order control strategy for the SCARA robot is developed. The proposed control is composed of [Formula: see text] and a fractional-order passivity-based adaptive controller, based on the Caputo–Fabrizio and Atangana–Baleanu derivatives, respectively; both controls are robust to external disturbances and change in the desired trajectory and effectively enhance the performance of robot manipulator. The fractional-order dynamic model of the robot manipulator is obtained by using the Euler–Lagrange formalism, as well as the model of the induction motors which are the actuators that drive their joints. Through simulations results, the effectiveness and robustness of the proposed control strategy have been demonstrated. The performance of the fractional-order proposed control method is compared with its integer-order counterpart, composed of the PI controller and the conventional passivity-based adaptive controller, reported in the literature. The performance comparison results demonstrate the superiority and effectiveness of the fractional-order proposed control strategy for a SCARA robot manipulator.

scholarly journals Application of Nonlinear Adaptive Control in Temperature of Chinese Solar Greenhouses

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1582
Author(s):  
Yonggang Wang ◽  
Yujin Lu ◽  
Ruimin Xiao
Keyword(s):  
Neural Network ◽  
Adaptive Control ◽  
Radial Basis Function ◽  
Control Strategy ◽  
Basis Function ◽  
Adaptive Controller ◽  
Strong Nonlinearity ◽  
Nonlinear Adaptive Control ◽  
Radial Basis ◽  
Adaptive Control Strategy

The system of a greenhouse is required to ensure a suitable environment for crops growth. In China, the Chinese solar greenhouse plays a crucial role in maintaining a proper microclimate environment. However, the greenhouse system is described with complex dynamic characteristics, such as multi-disturbance, parameter uncertainty, and strong nonlinearity. It is difficult for the conventional control method to deal with the above problems. To address these problems, a dynamic model of Chinese solar greenhouses was developed based on energy conservation laws, and a nonlinear adaptive control strategy combined with a Radial Basis Function neural network was presented to deal with temperature control. In this approach, nonlinear adaptive controller parameters were determined through the generalized minimum variance laws, while unmodeled dynamics were estimated by a Radial Basis Function neural network. The control strategy consisted of a linear adaptive controller, a neural network nonlinear adaptive controller, and a switching mechanism. The research results show that the mean errors were 0.8460 and 0.2967, corresponding to a conventional PID method and the presented nonlinear adaptive scheme, respectively. The standard errors of the conventional PID method and the nonlinear adaptive control strategy were 1.8480 and 1.3342, respectively. The experimental results fully prove that the presented control scheme achieves better control performance, which meets the actual requirements.

Distributed adaptive control strategy for flexible link manipulators

Robotica ◽  
2016 ◽  
Vol 35 (7) ◽  
pp. 1562-1584 ◽  
Author(s):  
Fareh Raouf ◽  
Saad Mohamad ◽  
Saad Maarouf ◽  
Bettayeb Maamar
Keyword(s):  
Control Strategy ◽  
Adaptive Controller ◽  
Joint Space ◽  
Flexible Link ◽  
Estimated Parameters ◽  
Distributed Adaptive Control ◽  
Gradient Based ◽  
Upper Level ◽  
Adaptive Control Strategy ◽  
Error Dynamics

SUMMARYThis paper presents an adaptive distributed control strategy for n-serial-flexible-link manipulators. The proposed adaptive controller is used for flexible-link-manipulators: (1) to solve the tracking control problem in the joint space, and (2) to reduce vibrations of the links. The dynamical model of flexible link manipulators is reorganized to take the form of n interconnected subsystems. Each subsystem has a one-joint and one-link pair. The system parameters are deemed to be unknown. The adaptive distributed strategy controls one subsystem in each step, starting from the last one. The nth subsystem is controlled by assuming that the remaining subsystems are stable. Then, proceeding backward to the (n-1)th system, the same strategy is applied, and so on, until the first subsystem is reached. The gradient-based estimator is used to estimate the parameters of each subsystem. The control law of the ith subsystem uses its own estimated parameters and the estimated parameters of all upper level subsystems. The global stability of the error dynamics is proved using Lyapunov approach. This algorithm was implemented in real time on a two-flexible-link manipulator, and a comparison with the non-adaptive version shows the effectiveness of this approach.

scholarly journals A Reactive Power Based Reference Model for Adaptive Control Strategy in a SEIG

2018 ◽  
Vol 8 (1) ◽  
pp. 2477-2484
Author(s):  
M. A. Taghikhani ◽  
A. D. Farahani
Keyword(s):  
Vector Control ◽  
Control Strategy ◽  
Reactive Power ◽  
Reference Model ◽  
Dynamic Performance ◽  
Adaptive Controller ◽  
Control Mode ◽  
Rotor Flux ◽  
Adaptive Control Strategy ◽  
Model Reference Adaptive

In this paper, a new control strategy is proposed for a three-phase squirrel-cage self-excited induction generator (SEIG) connected to a variable speed wind turbine in autonomous mode. In order to improve the dynamic performance of the mentioned vector control system, a model reference adaptive controller is used for online rotor time constant estimation. Thus, the main drawbacks of this method, which include the effects of the changes in machine parameters on rotor flux estimation, slip speed, the creation of instability problems and the system leaving vector control mode, are resolved. In this control strategy, a PI controller is used to control the dc voltage and three similar hysteresis current controllers (HCC) are used to control the switching of IGBTs. The results of the dynamic simulation indicate the desirable performance of the proposed system.

Sign in / Sign up

Export Citation Format

Share Document