Top PDF Design Templates for Some Fractional Order Control Systems

Design Templates for Some Fractional Order Control Systems

Design Templates for Some Fractional Order Control Systems

area mutually connected thermal power plant with generation rate constraint; group hunting search algorithm is adopted to explore the gain parameters of the controllers [13]. In [14], PI controller design is performed by using optimization for FOSs; first, controller parameters for a stable control are calculated by using the stability boundary locus method and then optimization is used to provide the best control. In [15], a new robust FOPID controller to stabilize a perturbed nonlinear chaotic system on one of its unstable fixed points is proposed based on the PID actions using the bifurcation diagram. In [16], fractional-order discrete synchronization of a new fourth -order memristor chaotic oscillator and the dynamic properties of the fractional-order discrete system are investigated; a new method for synchronizing is proposed and validated. In spite of the existence of a great deal of publications about FOSs some of which have just been mentioned above, most of the present analysis and design techniques deal with sophisticated and rather special applications [17-24]. Although the step response characteristics such as rise time, settling time, delay time, overshoot and some others are well known by explicit formulas for simple integer order systems [25], such formulas are not available for FOSs. And a compact publication yielding the relations between the design parameters and the step response characteristics of even simple FOSs are not yet present. The purpose of this paper is to fulfill this vacancy and to supply some design tools for simple order FOSs.
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Stability of closed-loop fractional-order systems and definition of damping contours for the design of controllers

Stability of closed-loop fractional-order systems and definition of damping contours for the design of controllers

The CRONE control methodology has been extended to MIMO systems [Nelson-Gruel et al., 2009]. Its main principle is to optimize the param- eters of a nominal and diagonal open loop trans- fer function matrix whose diagonal elements are defined by (11). It can be used to control a beam and tank system (Fig. 14) that models an aircraft wing. This system exhibits extremely low-damped vibrations that depend on the level of filling of the tank (Fig. 15). About 200 sec was required to obtain damped vibrations. These vibrations are measured by two piezoelectric ceramics ( y l and y h ). Two other
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Design of a Fractional Order CRONE and PID Controllers for Nonlinear Systems using Multimodel Approach

Design of a Fractional Order CRONE and PID Controllers for Nonlinear Systems using Multimodel Approach

This paper deals with the output regulation of nonlinear control systems in order to guarantee desired performances in the presence of plant parameters variations. The proposed control law structures are based on the fractional order PI (FOPI) and the CRONE control schemes. By introducing the multimodel approach in the closed-loop system, the presented design methodology of fractional PID control and the CRONE control guarantees desired transients. Then, the multimodel approach is used to analyze the closed-loop system properties and to get explicit expressions for evaluation of the controller parameters. The tuning of the controller parameters is based on a constrained optimization algorithm. Simulation examples are presented to show the effectiveness of the proposed method.
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Fractional-Order Filter Design for Set-point Weighted PID Controlled Unstable Systems

Fractional-Order Filter Design for Set-point Weighted PID Controlled Unstable Systems

Abstract— Control of unstable systems with conventional PID controllers gives poor set-point tracking and disturbance rejection performance. The use of set-point weighted PID controllers (SWPID) to improve the control performance with respect to set-point tracking and disturbance rejection have been attempted. This is due to the fact that, SWPID will reduce proportional and derivative kicks in the control action. However, the control signal of SWPID controller is still inheriting the PID’s undesired oscillations in the control signal. This leads to faster degradation of actuators. In this work, a fractional-order low- pass filter is designed alongside SWPID controller for unstable systems. Incorporating such filter will help to reduce undesired oscillations. The result’s comparison shows that the performance of SWPID with fractional-order filter is better compared to its performance with an integer-order filter. This is true for all the three unstable systems considered.
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Synchronization Method for a Class of Fractional order and Integer order Chaotic Systems

Synchronization Method for a Class of Fractional order and Integer order Chaotic Systems

Abstract. This paper focuses on the synchronization issues between a class of fractional-order and integer-order chaotic systems. A closed-loop control system is introduced following the linear feedback control and fractional-order stability theories to address the synchronization issues. Appropriate coefficients in this paper mentioned synchronization are adopted to guarantee the finite time asymptotical stability of resulting synchronization error due to the disturbances. The proposed control scheme is validated using simulations, and the results illustrate that the proposed controller can implement the synchronization between a class of fractional-order chaotic systems and integer-order chaotic systems, two variable structure fractional-order chaotic systems or two mismatched fractional-order chaotic systems.
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Output feedback consensus control for fractional-order nonlinear multi-agent systems with directed topologies

Output feedback consensus control for fractional-order nonlinear multi-agent systems with directed topologies

In reality, the agents might be affected by the interaction among neighboring agents, but also by its own intrinsic nonlinear dynamic. So the MASs with intrinsic nonlinear dynamics are considered recently in [2,3,5,14,18] . Since the limited view field or nonuniform sensing ranges of sensors, one agent may be able sense another agent, but not vice versa. The com- munication topology among the agents, in general is directed. Taking into consideration these practical cases, in this paper, we consider the consensus problem of fractional-order double integrator MASs with intrinsic nonlinear dynamics and general directed topologies using only relative output information. Due to the well-known Leibniz rule for fractional derivatives is invalid [28] , how to construct a suitable Lyapunov function for analysing the stability of nonlinear fractional-order MASs is very challenging. The output feedback based consensus control of double integrator MASs in the presence of nonlinear fractional-order dynamics is even more challenging as the communication topology among the agents is not only directed but also local.
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Predictive Functional Control for Fractional Order System

Predictive Functional Control for Fractional Order System

Abstract – The fractional calculus is the area of mathematics that handles derivatives and integrals of any arbitrary order (fractional or integer, real or complex order). Predictive Functional Control (PFC) is one of the most popular methods of model predictive control. The implementation of the predictive functional controller (PFC) on the fractional order systems has been presented in this paper. The effect of various approximations, sensitivity analysis, tuning of predictive functional controller parameters, the effect of delay and noise analysis of the fractional-order system has been considered. It has been shown that, in fractional order system,predictive functional control gives acceptable results.
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Synchronization of Economic Systems with Fractional Order Dynamics Using Active Sliding Mode Control

Synchronization of Economic Systems with Fractional Order Dynamics Using Active Sliding Mode Control

Synchronization of chaos has widely spread as an important issue in nonlinear systems and is one of the most important branches on the problem of controlling of chaos. In this paper, among different chaotic systems the economy chaotic system has been selected. The main aim of this paper is the designing based on the active sliding mode control for the synchronization of fractional- order chaotic systems. The chaos in the economic series could have serious and very different consequences in common macro-economy models. In this paper, this article expressed the various positions of synchronization in economic system that include of changes in the coefficients of the system ,changes in the initial conditions of the system and different fractional-order synchronization on the economic system. . in which Synchronization is shown in some examples.
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Robust Stabilization of Fractional Order Systems with Interval Uncertainties via Fractional Order Controllers

Robust Stabilization of Fractional Order Systems with Interval Uncertainties via Fractional Order Controllers

We propose a fractional-order controller to stabilize unstable fractional-order open-loop systems with interval uncertainty whereas one does not need to change the poles of the closed-loop system in the proposed method. For this, we will use the robust stability theory of Fractional-Order Linear Time Invariant FO-LTI systems. To determine the control parameters, one needs only a little knowledge about the plant and therefore, the proposed controller is a suitable choice in the control of interval nonlinear systems and especially in fractional-order chaotic systems. Finally numerical simulations are presented to show the effectiveness of the proposed controller.
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Robust adaptive control for fractional order chaotic systems with system uncertainties and external disturbances

Robust adaptive control for fractional order chaotic systems with system uncertainties and external disturbances

fractional-order adaptation laws are designed to update the controller parameters. By employing the fractional-order expansion of classical Lyapunov stability method, a robust controller is designed for fractional-order chaotic systems. The system states asymptotically converge to the origin and all signals in the closed-loop system remain bounded. A counterexample is constructed to show that the fractional-order

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Some results on the fractional order Sturm Liouville problems

Some results on the fractional order Sturm Liouville problems

On the one hand, since a Lyapunov-type inequality has found many applications in the study of various properties of solutions of differential equations, such as oscillation the- ory, disconjugacy and eigenvalues problems, there have been many extensions and gener- alizations as well as improvements in this field, e.g., to nonlinear second order equations, to delay differential equations, to higher order differential equations, to difference equa- tions and to differential and difference systems. We refer the readers to [–] (integer or- der). Fractional differential equations have gained considerable popularity and importance due to their numerous applications in many fields of science and engineering including physics, population dynamics, chemical technology, biotechnology, aerodynamics, elec- trodynamics of complex medium, polymer rheology, control of dynamical systems. With the rapid development of the theory of fractional differential equation, there are many
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Power Optimization and Control in Wind Energy Conversion Systems using Fractional Order Extremum Seeking

Power Optimization and Control in Wind Energy Conversion Systems using Fractional Order Extremum Seeking

The turbine power is measured from the equation(2) is given to the outer loop controller that is FOESC which gives an approximated value of the optimal turbine speed with respect to Fig.2.It is then given to the inner loop nonlinear control. The non linear control used here is feedback linearization which performs FOC and avoids magnetic saturation of the IG. It is a closed loop drives the turbine speed to the optimal value found by the MPPT and drives the rotor flux to the reference flux value given manually. The conventional FOC control method with P&O method is shown in [5] and [6].The PI controller used causes high response time and high overshooting if error is unexpectedly very high. It is also difficult to design PI since unpredictable variations in the machine parameters, external load disturbance and non linear dynamics. The other methods used for FOC concept are Fuzzy logic, gain scheduled PI and relative gain array. The feedback linearization gives a faster response and desired response can be obtained by adjusting the feedback gains. The controller gives stator frequency and stator voltage given to modulation, the modulation and pulse generation for MC can be referred from [4],[7] and [8] .The MC regulates the stator electrical frequency to control the turbine speed. The stator voltage amplitude can be maintained to regulate the rotor flux. The turbine speed variation does not affect rotor flux. Similarly the rotor flux reference can be varied even independently of reference optimal speed found by the MPPT. This is an improvement over FOC.
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Control and Synchronization of a Fractional-order Chaotic Financial System

Control and Synchronization of a Fractional-order Chaotic Financial System

stability theory is crucial, and it is an important basis for judging whether a system can operate normally. It is also an important basis to prove chaotic synchronization. At present, the main chaotic synchronization criterion is based on the synchronization criterion of Lyapunov exponent and the synchronization criterion based on Lyapunov function. The literature [5-7] is based on the synchronization criterion of the Lyapunov function. However, in the fractional order system, due to the more complicated system, there are of course some methods that are different from the integer order stability judgment. The literature [8,9] separately calculates the range of the value of the coefficient matrix of the analysis system, and then judges the stability criterion of the fractional-order linear system; Hu Jianbing [10-12] is a long-term commitment to fractional nonlinear stability. Research; literature [13] and literature [14] judge the stability of the system according to the Lyapunov equation; recently, Huang et al. [15] proposed a new method for judging the stability of fractional-order systems, that is, constructing a suitable function first. Then analyze the positive and negative of its eigenvalues to determine whether the system is stable. The hybrid synchronization problem of chaotic systems has only appeared in recent years. Hybrid synchronization, that is, synchronization and anti-synchronization coexist, is actually a generalization of synchronization and projection synchronization. In the literature [16] and [17], the definition of hybrid synchronization is given respectively. Further, the literature [18] designed a simple linear hybrid synchronous controller, and proposed a synchronization criterion, but the conditions of the criterion is related to the state variables of the drive system.
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Fractional order control of a DC motor with load changes

Fractional order control of a DC motor with load changes

In this paper a fractional calculus based control strategy for speed control of a DC motor with load changes is presented. The relevance of the paper to the research field consists in the simplicity of the approach, yet yielding a robust controller that can meet the performance specifications for significant load changes. The robustness of the fractional-order PI controller and its performances are compared against an integer-order PI controller. In order to evaluate the robustness of the controllers a change in the motor loading unit is considered for the conducted experiments. Due to the change in the brake unit, the gain and time constant of the system are also modified. The performances of both classical integer-order approach and fractional-order approach are analyzed through simulations and real-time experiments. The control design method and the application are kept simple, yet effective to illustrate basic time domain and frequency domain concepts. The experimental results revealed better performances of the fractional approach in comparison with the classical one.
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Analysis of Fractional Order Control System with Performance and Stability

Analysis of Fractional Order Control System with Performance and Stability

In this paper, a new approach to stability for fractional order control system is proposed. Here a dynamic system whose behavior can be modeled by means of differential equations involving fractional derivatives. Applying Laplace transforms to such equations, and assuming zero initial conditions, causes transfer functions with no integer powers of the Laplace transform variable s to appear. In recent time, the application of fractional derivatives has become quite apparent in modeling mechanical and electrical properties of real materials. Fractional integrals and derivatives have originated wide application in the control systems. The measured system and the controller are termed by a set of fractional order differential equations.
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Fractional-order feedback control of a poorly damped system

Fractional-order feedback control of a poorly damped system

The classical mass-spring-damper system is a challenging system as each mass-spring construction introduces a peak in the frequency response of the system, resulting in resonance frequencies and high oscillations if damping is poor (like the case in this paper). Traditionally, these kind of systems are difficult to control by an integer-order proportional-integral- derivative (PID) controller as this controller has only one pair of zeros to compensate the system. Therefore, a controller of higher order would be more suitable to control poorly damped systems such as the mass-spring-damper. Advanced controllers such as fractional-order controllers may be better but also more complex as they can be approximated by high order integer- order transfer functions.
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Fractional order polytopic systems: robust stability and stabilisation

Fractional order polytopic systems: robust stability and stabilisation

Remark 1 Throughout the article, triplet (A, B, C) is always supposed to be minimal. Testing if the eigenvalues of matrix A belong to a region of the left half plane defined by (3) with 1 < ν < 2 is a well-known problem in LMI control theory because it corresponds to a performance requirement on the damping ratio of the system. A solu- tion of this problem is provided by the LMI region framework [13]. Extending this LMI condition to the case 0 < ν < 1 is far from trivial because the location of eigenva- lues in this region corresponds to unstable integer order systems. Moreover, region of the complex plane defined by (3) is not convex as shown in Figure 1. However, this problem has been solved in [4] in which the following result was proposed.
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Hybrid projective synchronization between the fractional order systems

Hybrid projective synchronization between the fractional order systems

methods have been proposed to synchronize chaotic systems such as the sliding mode control method [2], active control method [3-6], linear and non linear feedback control method [7-8], adaptive control method [9-10], backstepping control [11-12] and impulse control method [13- 14]. Using these methods, numerous synchronization problems of well- known chaotic systems such as L¨u, R¨ossler, Lorenz, Chen, Genesio have been studied.

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Design of fractional-order controller for trajectory tracking control of a non-holonomic autonomous ground vehicle

Design of fractional-order controller for trajectory tracking control of a non-holonomic autonomous ground vehicle

The dynamics model of an autonomous ground vehicle repre- sents the study of the relationship between the various forces action on a robot mechanism and their accelerations. This is mainly used for simulation study and analysis of vehicle’s design and a motion controller design for the vehicle. The description of the mechanism of the robot movement is given in terms of its component parts; bodies, joints and the para- meters that characterize them. In fact, several parameters are required to define the dynamic model of a given rigid body such inertia, centre of mass and applied forces. The energy- based Lagrangian approach can be used to derive the dynamic model of the autonomous vehicle which is represented in the following general form Fierro and Lewis (1997):
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Robust convergence analysis of iterative learning control for impulsive Riemann Liouville fractional order systems

Robust convergence analysis of iterative learning control for impulsive Riemann Liouville fractional order systems

The rest of this paper is organized as follows. In Section , we give some necessary nota- tions, concepts, and lemmas. In Section , two sufficient conditions ensuring convergence results of the system () are presented. An interesting example is given in the final section to demonstrate the application of our main results.

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