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.

On Robust Control of Fractional Order Plants: Invariant Phase Margin

2015 ◽  
Vol 10 (5) ◽  
Author(s):  
Mohammad Hossein Basiri ◽  
Mohammad Saleh Tavazoei
Keyword(s):  
Robust Control ◽  
Fractional Order ◽  
Phase Margin ◽  
Crossover Frequency ◽  
Large Uncertainty ◽  
Robust Controller ◽  
Numerical Examples

Recently, a robust controller has been proposed to be used in control of plants with large uncertainty in location of one of their poles. By using this controller, not only the phase margin and gain crossover frequency are adjustable for the nominal case but also the phase margin remains constant, notwithstanding the variations in location of the uncertain pole of the plant. In this paper, the tuning rule of the aforementioned controller is extended such that it can be applied in control of plants modeled by fractional order models. Numerical examples are provided to show the effectiveness of the tuned controller.

OPCL Coupling of Mixed Integer-Fractional Order oscillators: Tree and Chain Implementation

2021 ◽  
Author(s):  
Adedayo Oke Adelakun
Keyword(s):  
Fractional Order ◽  
Mixed Integer ◽  
Complete Synchronization ◽  
Amplitude Death ◽  
Integer Order ◽  
Simulation Results ◽  
Coupled Circuits ◽  
Tree Type ◽  
Chain Type

Abstract OPCL Coupling of Integer-order and fractional-order Sprott-A systems using off-shelf components are constructed. Fractance configurations such as chain-type and tree-type were designed using a fractional-order capacitor and fractional-order resistor, respectively. The simulation results of the coupled circuits reveal the transition between complete synchronization (CS) to Anti-synchronization (AS) and vice versa via Amplitude death (AD).

scholarly journals Consensus of Fractional-Order Multiagent Systems with Nonuniform Time Delays

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Jun Liu ◽  
Kaiyu Qin ◽  
Wei Chen ◽  
Ping Li ◽  
Mengji Shi
Keyword(s):  
Multiagent Systems ◽  
Fractional Order ◽  
Time Delays ◽  
External Environment ◽  
Domain Theory ◽  
Dynamical Model ◽  
Integer Order ◽  
The Laplace Transform ◽  
Simulation Results ◽  
Theoretical Results

Due to the complex external environment, many multiagent systems cannot be precisely described or even cannot be described by an integer-order dynamical model and can only be described by a fractional-order dynamical model. In this paper, consensus problems are investigated for two types of fractional-order multiagent systems (FOMASs) with nonuniform time delays: FOMAS with symmetric time delays and undirected topology and FOMAS with asymmetric time delays and directed topology. Employing the Laplace transform and the frequency-domain theory, two delay margins are obtained to guarantee the consensus for the two types of FOMAS, respectively. These results are also suitable for the integer-order dynamical model. Finally, simulation results are provided to illustrate the effectiveness of our theoretical results.

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.

Fractional Order Controller Design for Ball and Beam System

2013 ◽  
Vol 313-314 ◽  
pp. 544-548 ◽  
Author(s):  
Mehmet Korkmaz ◽  
Omer Aydogdu
Keyword(s):  
Genetic Algorithms ◽  
Particle Swarm Optimization ◽  
Evolutionary Algorithms ◽  
Fractional Order ◽  
Controller Design ◽  
Swarm Optimization ◽  
System Parameters ◽  
Beam System ◽  
Simulation Results ◽  
Fractional Order Controller

Fractional order controllers which has mostly used recently have investigated in this paper. It is benefit from ball & beam system to show effects of controllers. Fractional order controller and its integer form are compared with simulation results for the mentioned system. Parameters of controllers have obtained by using evolutionary algorithms techniques which are particle swarm optimization (PSO) and genetic algorithms (GAs). According to results, it is confirmed the advantage of fractional controllers. Beside, PSO has a little bit superiority over GAs technique for determining optimum values of controller parameters.

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