Fractional Order Fuzzy Logic Controller Research Articles

Direct torque control and dynamic performance of induction motor using fractional order fuzzy logic controller

<p><span lang="EN-US">Conventional direct torque control (DTC) is one of the best control systems for regulating the torque of an induction motor (IM). However, the DTC’s enormous waves in flux and torque cause acoustic noise that degrades control performance, especially at low speeds due to the DTC’s low switching frequency. Direct torque control systems, which focus just on torque and flux, have been proposed as a solution to these problems. In order to improve DTC control performance, this work introduces a fractional-order fuzzy logic controller method. The objective is to analyze this technique critically with regard to its efficacy in reducing ripple, its tracking speed, its switching loss, its algorithm complexity, and its sensitivity to its parameters. Simulation in MATLAB/Simulink verifies the anticipated control approach’s performance.</span></p>

Optimum of fractional order fuzzy logic controller with several evolutionary optimization algorithms for inverted pendulum

AbstractThis paper compared the performance between Integer Order Fuzzy PID (IOFPID) and Fractional Order Fuzzy PID (FOFPID) controllers for inverted pendulum system as a controlling plant. The parameters of each controller were tuned with four evolutionary optimization algorithms (Social Spider Optimization (SSO), Swarm Optimization (PSO), Genetic Algorithm (GA), and Particle Ant Colony Optimization (ACO)). The comparisons were carried out between the two controllers IOFPID and FOFPID, as well as among the four optimization algorithms for the two controllers. The results of comparisons proved that the FOFPID controller with SSO has achieved the best time response characteristics and the least tuning time.

Improvement of Power Quality in grid Integrated Smart grid using Fractional-order Fuzzy Logic Controller

Improvement of Power Quality in grid Integrated Smart grid using Fractional-order Fuzzy Logic Controller

A SURVEY STUDY OF FRACTIONAL ORDER CONTROL TECHNIQUES

nowadays, there is an interest for using fractional calculus in many applications and different researches are presenting in many fields. Control engineering problems are also solved using fractional calculus because it analyzes real system dynamics accurately. In this paper, a review study that present different researches using factional order controllers(FOC).The fractional order PID controller are most widely used in the application of control systems due to its simple structure and easy implementation, then the researcher use different techniques mixed with fractional calculus like fractional order neural network, fractional order fuzzy logic controller, fractional order sliding mode controller and finally fractional order backstepping controller, the recently advances is demonstrated in this review study.

Photovoltaic and Thermoelectric Generator Combined Hybrid Energy System with an Enhanced Maximum Power Point Tracking Technique for Higher Energy Conversion Efficiency

In this paper, the design and performance investigation of the hybrid photovoltaic–thermoelectric generator (PV–TEG) system with an enhanced fractional order fuzzy logic controller (FOFLC)-based maximum power point tracking (MPPT) technique is presented. A control strategy of the variable incremental conduction (INC) method is employed using FOFLC for the MPPT control technique to efficiently harvest the maximum power from the PV module. The fractional factor α used in the MPPT control algorithm is a supporting fuzzy logic controller (FLC) for the accurate tracking of the maximum power point (MPP) and to maintain the constant output after reaching the MPP. In the proposed system configuration, the TEG is mounted with the PV panel for generating the extra electrical power using the waste heat energy produced on the PV panel due to the incident solar irradiation. The PV and TEG are connected electrically in series to increase output voltage level and thereby improve the power output. The hybrid energy module has better energy conversion efficiency when compared to the standalone PV array. The performance of the proposed MPPT technique is studied for the PV–TEG hybrid energy module under various thermal and electrical operating conditions using a MATLAB software-based simulation. The results of the FOFLC-based MPPT technique are compared with the conventional perturb and observe (P&O) and FLC-based P&O methods. The proposed MPPT technique confirms its effectiveness in extracting the maximum power in terms of speed and accuracy. Moreover, the PV and TEG combined system provides higher energy efficiency than the individual PV module.

A Variable Fractional Order Fuzzy Logic Control Based MPPT Technique for Improving Energy Conversion Efficiency of Thermoelectric Power Generator

Thermoelectric generation technology is considered to be one of the viable methods to convert waste heat energy directly into electricity. The utilization of this technology has been impeded due to low energy conversion efficiency. This paper aims to improve the energy conversion efficiency of the thermoelectric generator (TEG) model with a novel maximum power point tracking (MPPT) technique. A variable fractional order fuzzy logic controller (VFOFLC)-based MPPT technique is proposed in the present work in which the operating point of the TEG is moved quickly towards an optimal position to increase the energy harvesting. The fraction order term α, introduced in the MPPT algorithm, will expand or contract the input domain of the fuzzy logic controller (FLC to shorten the tracking time and maintain a steady-state output around the maximum power point (MPP). The performance of the proposed MPPT technique was verified with the TEG model by simulation using MATLAB /SIMULINK software. Then, the overall performance of the VFOFLC-based MPPT technique was analyzed and compared with Perturb and observe (P&O) and incremental resistance (INR)-based MPPT techniques. The obtained results confirm that the proposed MPPT technique can improve the energy conversion efficiency of the TEG by harvesting the maximum power within a shorter time and maintaining a steady-state output when compared to other techniques.

Survey Study of Factional Order Controllers

This is a survey study that presents recent researches concerning factional controllers. It presents several types of fractional order controllers, which are extensions to their integer order counterparts. The fractional order PID controller has a dominant importance, so thirty-one paper are presented for this controller. The remaining types of controllers are presented according to the number of papers that handle them; they are fractional order sliding mode controller (nine papers), fuzzy fractional order sliding mode controller (five papers), fractional order lag-lead compensator (three papers), fractional order state feedback controller (three papers), fractional order fuzzy logic controller (three papers). Finally, several conclusions were drawn from the results that were given in this papers

A switching-based collaborative fractional order fuzzy logic controllers for robotic manipulators

In the present work, a collaborative implementation of fractional order proportional-integral-derivative control and fractional order fuzzy logic control method is investigated for the controlled tracking performance of a manipulator plant. An integral time absolute error measured between the desired and actual output trajectories, which is obtained by the optimal parameters, drives the switching mechanism between the two controllers, fractional order proportional-integral-derivative and fractional order fuzzy logic control, in order to implement the collaboration scheme. Different possible ways of switching mechanism between fractional order proportional-integral-derivative controller and fractional order fuzzy logic control scheme are explored. The resulting controller's parameters are investigated with meta-heuristic technique namely cuckoo search algorithm. The performance of the proposed collaborative scheme is compared with existing control schemes and basic proportional-integral-derivative control method for obtaining the controlled tracking performance. To generalize the use and effectiveness of designed control scheme, the simulation studies are also investigated for a first order plant and an inverted pendulum for the trajectory tracking problem. To analyse the effects of the parameter variations, disturbance rejection, and payload variations, the performance results for the proposed scheme are also presented for robotic manipulator. The proposed controller has a potential application in robotic manipulator control for different applications.

Performance analysis of optimal hybrid novel interval type-2 fractional order fuzzy logic controllers for fractional order systems

The main objective of this paper is to propose the family of hybrid novel interval type-2 fractional order fuzzy PID (IT2FO-FPID) controllers, which incorporates fractional order integro-differentiator, taking into its consideration the advantages of the interval type-2 fuzzy controllers (IT2FLCs) and fractional order PID (FOPID) controllers. The incorporation of IT2FLCs with FOPID controllers has been investigated in terms of time response measure for unit set-point response and unit load disturbance. The resulting different hybrid IT2FO-FPID controller structures are examined on different fractional order processes followed by robustness analysis. It is observed that incorporation of fractional order integro-differential operators made the proposed control structures less sensitive to the parameters change. For this reason, fractional order integro-differential operators are adopted as design variables along with input/output scaling factors for designing of effective novel controllers. In order to do reasonable comparison, the tuning of the family of hybrid IT2FO-FPID controllers' parameters is done with newly Artificial Bee Colony-Genetic Algorithm (ABC-GA) optimization technique to develop optimal closed loop performance by considering the objective function as weighted sum of control loop error index and control output. The simulation analyses are executed for two different non-integer order plus time delay fractional order process plants (NIOPTD-I and NIOPTD-II). These processes represent a sensible estimation of most process plants and are employed to examine the comparative qualities of the presented hybrid IT2FO-FPID controllers. Further, the performance comparison and the significance of the different proposed hybrid controllers are investigated under unit set-point response, load disturbance rejection, and small control signal or actuators requirement. In order to test the efficacy of proposed controllers, the robustness analysis such as parameter variations is also investigated. Finally, the simulation investigations explicitly suggest that proposed different hybrid IT2FO-FPID control structures can be recommended in terms of better step response, better load disturbance rejection, small control signal response, and parameters variation.

Comments on “Design of two-layered fractional order fuzzy logic controllers applied to robotic manipulator with variable payload”

Sharma et al. have investigated the performance of two-layered fractional order fuzzy logic controller (TL-FOFLC) for a 2-link rigid planer robotic manipulator with payload. In this work, the performance of TL-FOFLC has been compared with two-layered FLC (TL-FLC), single-layered FLC (SL-FLC) and the conventional proportional-integral-derivative (PID) controllers, for trajectory tracking, model uncertainties and disturbance rejection. In this comment, it is pointed out that this work has several missing essential parameters, and therefore, it is not possible for the reader to validate all the claimed results of Sharma et al. (2016). Six numerical values, three gains for each of the used two PID controllers are found to be unreported in addition to the six gains for each of the used two SL-FLCs. Since the performances of the PIDs and the SL-FLCs are highly dependent on their tuned gains it is concluded that the reported performances of these controllers cannot be validated.

Design of two-layered fractional order fuzzy logic controllers applied to robotic manipulator with variable payload

The robotic manipulators are highly coupled and nonlinear systems wherein the time-varying parameters and uncertainties adversely affect the characteristics and response of these systems. Hence, these systems require an effective and robust controller to handle such complexities which is a difficult challenge for control engineers. This paper presents two-layered fractional order fuzzy logic controller (TL-FOFLC) scheme for a two-link planar rigid robotic manipulator with payload for trajectory tracking task. For the optimal design, the controller parameters of the proposed scheme are obtained with potential meta-heuristic technique named as cuckoo search algorithm (CSA). In order to ensure effectiveness, the performance of proposed TL-FOFLC is compared with that of its integer order design approach, i.e., two-layered FLC (TL-FLC), single-layered FLC (SL-FLC), and the conventional proportional-integral-derivative (PID) controllers. Further, the robustness testing is carried out for parameter variations and external disturbance rejection.