Identification of Damavand tokamak using fractional order dynamic neural network

2018 ◽  
Vol 41 (5) ◽  
pp. 1447-1457 ◽  
Author(s):  
Zeinab Aslipour ◽  
Alireza Yazdizadeh
Keyword(s):  
Neural Network ◽  
Fractional Order ◽  
Controller Design ◽  
Learning Rule ◽  
Dynamic Neural Network ◽  
Integer Order ◽  
Optimal Value ◽  
New Learning ◽  
Damavand Tokamak ◽  
Comparison Of The Results

The Damavand tokamak is a small size research machine for fusion-related studies. This paper is motivated by the need to create an accurate nonlinear subspace model that may be used for controller design. The system is identified based on a newly introduced Fractional Order Dynamic Neural Network (FODNN) optimized by evolutionary computation. The proposed method, owing to its rich structure, is appropriate for modeling of the complicated behavior of the plasma and its instability. In the proposed method, a Lyapunov-like analysis is used to derive a stable new learning rule for updating the proposed FODNN weights. To achieve optimal value for fractional order of the proposed FODNN, a Particle Swarm Optimization (PSO) is employed. The performance of the proposed identifier is verified by using experimental data and the results are also compared with the integer order dynamic neural network identifier. The results show that there is a bound for the “identification error” that vanishes to zero as time tends to infinity. Furthermore, the comparison of the results achieved by the proposed method and those of the integer order dynamic neural network depicts higher accuracy of the proposed FODNN.

scholarly journals Fractional-order fuzzy adaptive controller design for uncertain robotic manipulators

2019 ◽  
Vol 16 (2) ◽  
pp. 172988141984022 ◽  
Author(s):  
Yanping Deng
Keyword(s):  
Fuzzy Control ◽  
Fractional Order ◽  
Controller Design ◽  
Sliding Mode ◽  
Main Idea ◽  
Robotic Manipulators ◽  
Adaptive Controller ◽  
Small Region ◽  
Trajectory Tracking Control ◽  
Integer Order

A sliding mode adaptive fractional fuzzy control is provided in this article to achieve the trajectory tracking control of uncertain robotic manipulators. By adaptive fractional fuzzy control, we mean that fuzzy parameters are updated through fractional-order adaptation laws. The main idea of this work consists in using fractional input to control complex integer-order nonlinear systems. An adaptive fractional fuzzy control that guarantees tracking errors tend to an arbitrary small region is established. To facilitate the stability analysis, fractional-order integral Lyapunov functions are proposed, and the integer-order Lyapunov stability criterion is used. Finally, simulation results are presented to show the effectiveness of the proposed method.

Improved Internal Model Control-Proportional-Integral- Derivative Fractional-Order Multiloop Controller Design for Non Integer Order Multivariable Systems

2018 ◽  
Vol 141 (1) ◽  
Author(s):  
Tassadit Chekari ◽  
Rachid Mansouri ◽  
Maamar Bettayeb
Keyword(s):  
Fractional Order ◽  
Degrees Of Freedom ◽  
Controller Design ◽  
Mimo Systems ◽  
Design Method ◽  
Internal Model Control ◽  
Tuning Parameter ◽  
Multivariable Systems ◽  
Integer Order ◽  
Model Control

This paper is aimed to propose a multiloop control scheme for fractional order multi-input multi-output (FO-MIMO) systems. It is an extension of the FO-multiloop controller design method developed for integer order multivariable systems to FO-MIMO ones. The interactions among the control loops are considered as disturbances and a two degrees-of-freedom (2DOF) paradigm is used to deal with the process outputs performance and the interactions reduction effect, separately. The proposed controller design method is simple, in relation with the desired closed-loop specifications and a tuning parameter. It presents an interest in controlling complex MIMO systems since fractional order models (FO-models) represent some real processes better than integer order ones and high order systems can be approximated by FO-models. Two examples are considered and compared with other existing methods to evaluate the proposed controller.

Modeling and Design of Fractional-Order IMC Based Controller for Power Plant Gas Turbine

2015 ◽  
Author(s):  
Sharad P. Jadhav ◽  
Rajan H. Chile ◽  
Satish T. Hamde
Keyword(s):  
Power Plant ◽  
Gas Turbine ◽  
Fractional Order ◽  
Internal Model ◽  
Controller Design ◽  
Optimization Technique ◽  
Research Area ◽  
Integer Order ◽  
Point Tracking ◽  
Internal Model Controller

Fractional-order modeling and controller design by a simplified way is the demanding research area and is gearing more and more momentum. This paper is the attempt of application of fractional-order modeling and controller design for the power plant gas turbine. The Gas Turbine is most important equipment in power, aviation and automotive industry. It converts the thermal energy of fuel into the mechanical power. Therefore, important requirement of gas turbine system is to control the flow of input fuel. The existing identified model of the gas turbine between the input fuel flow and the output speed, is of high-order and integer type, which is reduced to the simple and compact integer-order (IO) and fractional-order (FO) models using local optimization technique. The fractional-order internal model controller (FO-IMC) is designed and to show the performance efficacy it is compared with integer-order internal model controller (IO-IMC), which is also designed using the same methodology and specification. Simulation results show that FO-IMC based controller gives better performance for the set point tracking, plant uncertainty and disturbance rejection than the IO-IMC. FO-IMC controller also satisfy the robust stability condition.

scholarly journals Neural Network Backstepping Controller Design for Fractional-Order Nonlinear Systems

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Youjun Chen ◽  
Songyu Wang
Keyword(s):  
Neural Network ◽  
Fractional Order ◽  
Control Method ◽  
Controller Design ◽  
Estimation Error ◽  
Theoretical Method ◽  
Network Control ◽  
Feedback Systems ◽  
Backstepping Controller ◽  
The Stability

In this work, a backstepping controller design for fractional-order strict feedback systems is investigated and the neural network control method is used. It is noted that in the standard backstepping design, the fractional derivative of the virtual quantity needs to be calculated repeatedly, which will lead to a sharp increase in the number of controller terms with the increase of the system dimension and finally make the control system difficult to bear. To handle the estimation error, certain robust terms in the controller at the last step are designed. The stability of the controlled system is proven strictly. In addition, the proposed controller has a simple form which can be easily implemented. Finally, in order to verify our theoretical method, the control simulation based on a fractional-order chaotic system is implemented.

Fractional Order Proportional Derivative (FOPD) and FO[PD] Controller Design for Networked Position Servo Systems

2009 ◽  
Author(s):  
Yongshun Jin ◽  
YangQuan Chen ◽  
Chunyang Wang ◽  
Ying Luo
Keyword(s):  
Fractional Order ◽  
Controller Design ◽  
Phase Margin ◽  
Crossover Frequency ◽  
Pd Controller ◽  
Servo Systems ◽  
Integer Order ◽  
Simulation Results ◽  
Position Servo ◽  
The Given

This paper considers the fractional order proportional derivative (FOPD) controller and fractional order [proportional derivative] (FO[PD]) controller for networked position servo systems. The systematic design schemes of the networked position servo system with a time delay are presented. It follows from the Bode plot of the FOPD system and the FO[PD] that the given gain crossover frequency and phase margin are fulfilled. Moreover, the phase derivative w.r.t. the frequency is zero, which means that the closed-loop system is robust to gain variations at the given gain crossover frequency. However, sometimes we can not get the controller parameters to meet our robustness requirement. In this paper, we have studied on this situation and presented the requirement of the gain cross frequency, and phase margin in the designing process. For the comparison of fractional order controllers with traditional integer order controller, the integer order proportional integral differential (IOPID) was also designed by using the same proposed method. The simulation results have verified that FOPD and FO[PD] are effective for networked position servo. The simulation results also reveal that both FOPD controller and FO[PD] controller outperform IO-PID controller for this type of system.

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