Type-2 Controller Research Articles

Fuzzy type-2 fractional Backstepping blood glucose control based on sliding mode observer

A new combination of fractional order (FO) nonlinear control and sliding mode observer (SMO) for blood glucose regulation in type 1 diabetes mellitus is proposed in this paper. An observer estimates the difficult-to-measure process variables that are significant to control law design and to prevent failures. A SMO is proposed to estimate non-measurable states variables of Bergman minimal model by data acquired from a continuous glucose monitoring sensor. At first based on Backstepping method with FO sliding surface a control signal is proposed, and then interval type 2 fuzzy logic is utilized to reduce the chattering phenomenon in control signal. The FO sliding mode control provides robust performance and the Backstepping algorithm protects the controller in front of mismatched and matched uncertainties. Simulation results of the proposed controller are compared with its integer counterpart.

Artificial Intelligent Fuzzy Logic Controller Applied on 6DOF Robot Arm Using LabVIEW and FPGA

In this work an efficient Artificial Intelligent Robotic Fuzzy Logic Controller (AIRFC) system have been constructed to control the robot arm. A serial link Robot manipulator with 6 Degree of Freedom (DOF) from DFROBOT of code ROB0036 is used as a case study. A fuzzy logic type1 controller is implemented on LabVIEW to control each joint of the robot arm for nonlinearity measurements and a fuzzy logic type2 controller is applied which is more suitable for uncertainty. The hardware design is implemented and finally downloaded using the Field Programmable Gate Array (FPGA) kit named PCI-7833R from National Instrument. By using the LabVIEW FPGA MODEL the target board can be detected for software implementation of the controllers’ systems. The work shows that in case of type2 fuzzy logic the rise time is less than that of type1 fuzzy logic for the shoulder, wrist roll and the gripper angles and it is higher for base, elbow and wrist pitch angles. The settling time is the same in elbow and wrist pitch angles and for the type2 fuzzy controller it is less for other angles.

Artificial Intelligent Fuzzy Logic Controller Applied on 6DOF Robot Arm Using LabVIEW and FPGA

In this work an efficient Artificial Intelligent Robotic Fuzzy Logic Controller (AIRFC) system have been constructed to control the robot arm. A serial link Robot manipulator with 6 Degree of Freedom (DOF) from DFROBOT of code ROB0036 is used as a case study. A fuzzy logic type1 controller is implemented on LabVIEW to control each joint of the robot arm for nonlinearity measurements and a fuzzy logic type2 controller is applied which is more suitable for uncertainty. The hardware design is implemented and finally downloaded using the Field Programmable Gate Array (FPGA) kit named PCI-7833R from National Instrument. By using the LabVIEW FPGA MODEL the target board can be detected for software implementation of the controllers’ systems. The work shows that in case of type2 fuzzy logic the rise time is less than that of type1 fuzzy logic for the shoulder, wrist roll and the gripper angles and it is higher for base, elbow and wrist pitch angles. The settling time is the same in elbow and wrist pitch angles and for the type2 fuzzy controller it is less for other angles.

Application of adaptive-SOS (ASOS) algorithm based interval type-2 fuzzy-PID controller with derivative filter for automatic generation control of an interconnected power system

In this article, a maiden comparative performance analysis of interval type-2 fuzzy-PID controller with & without derivative filter (T2FPIDF & T2FPID), type-1 fuzzy-PID controller (T1FPID) and conventional PID controller for Automatic Generation Control (AGC) in a two area interconnected thermal power system is presented. The proposed controllers are optimally designed using a novel adaptive symbiotic organism search (ASOS) & symbiotic organism search (SOS) optimization techniques. Symbiotic organism search (SOS) algorithm is established from the interrelation of organisms to survive in the ecosystem and in this article it is modified by using self-tuned benefit factors. This makes the ASOS superior over SOS. To prove the superiority of ASOS algorithm over SOS algorithm and T2FPIDF controller over other proposed controllers, transient performance of the AGC system is studied by applying a sudden step load change of 10% in area-1 of the two unequal area power system. Various transient parameters such as undershoot, overshoot and settling time are considered to carry out the performance analysis study. Robustness analysis is performed by varying all the system parameters to prove the effectiveness of the proposed controller against parametric variation. Finally it observed that ASOS optimized T2FPIDF controller outperforms other proposed controllers in terms of less undershoot, overshoot and settling time.

A distributed load balancing and admission control algorithm based on Fuzzy type-2 and Game theory for large-scale SaaS cloud architectures

With the advent of cloud computing and virtualization technologies, business models are created to serve users with applications, platforms or processing resources. One of these models is providing software as a service (SaaS) in cloud environments. Due to its user-friendly nature, the demand for SaaS is increasing exponentially in recent years, so geographically distributed cloud infrastructures are required for hosting such services. On the other hand, with the world wide spread of applications, users need to access them all over the world. Common centralized architecture of resources is not responsive and clusters of large-scale distributed servers are required to host applications in different geographical locations. In this paper, a novel two-layer (regional–local) distributed resource management algorithm is proposed which can handle management tasks such as requests admission control and load balancing in large scales. The proposed algorithm is scalable, in which the control tasks are divided among application and proxy servers. Therefore, each component performs the task of managing resources independently. To control the admission of requests, a Self-Adaptive Fuzzy type-2 Controller containing two fuzzy controllers is introduced. Also, for distributing requests and balancing load in the proxy servers, a Game theory based algorithm proposed which converged to Nash equilibrium. The proposed algorithm is implemented and tested using four physical machines. The algorithm is evaluated using two standard dynamic workloads. By deploying this algorithm, the average percentage of rejected requests and LBM value are improved compared to rival algorithms about 15% and 4.5% respectively.

Obtaining Performance of Type-3 Phase-Locked Loop Without Compromising the Benefits of Type-2 Control System

A phase-locked loop (PLL) is a closed-loop feedback control system that estimates the frequency as well as phase of an input signal. The most commonly deployed synchronization method in three-phase applications is a type-2 synchronous reference frame PLL. With pre/in-loop selective harmonic filtering stage, type-2 PLLs can obtain good detection speed, decent stability margins, and better disturbance rejection. However, it suffers from the finite steady-state phase error during ramp change in input signal frequency. To tackle this challenge type-3 PLLs have been developed recently, either by adding a feed-forward path to the PLL structure, or by using a second-order controller as the loop filter. However, recent analysis carried out of type-3 PLLs show that they aggravate stability problem and compromise the performance in terms of detection speed and disturbance rejection. A new concept of synchronization is proposed in this paper that obtains the performance of type-3 PLL but retains all the advantages associated with type-2 PLL. Extensive experimental results are provided to validate the proposed work.

Adaptive type-2 fuzzy controller for nonlinear delay dominant MIMO systems: an experimental paradigm in LabVIEW

Higher order nonlinear systems with prevailing delay have been very challenging in significance with stability and process performance. This paper investigates the performance of a type-2 Mamdani intelligent controller implemented a delay dominant system which is modelled using black box approach identified to be a second order nonlinear model for a dual spherical tank liquid level system (DSTLLS) under LabVIEW environment. The adaptive approach of the intelligent Mamdani-based fuzzy controller proves itself to be very competent compared with the earlier experimented methods that already exist. The performance indices like integrated absolute error (IAE) and integrated squared error (ISE) are also calculated for different varying set point changes of DSTLLS. The response and error reduction efficiency of this method of adaptive type-2 intelligent fuzzy (ATIF) controller has been experimented for different flow configurations of this DSTLLS, like multiple input single output (MISO), multiple input multiple output (MIMO) and single input single output (SISO).

Fuzzy Type-2 Controller Design for Small-Signal Stability Considering Time Latencies and Uncertainties in PMU Measurements

Wide-area damping controllers are generally provided in a large network to prevent small-signal oscillations. These controllers utilize remote measurements provided by synchrophasors. However, these communicated measurements are delayed and uncertain. Type-2 fuzzy provides higher order approximation of uncertainty and is able to provide solutions for real-world problems in more a reliable manner. Therefore, in this paper, a wide-area damping controller based on interval type-2 fuzzy system is designed. Proposed controllers not only consider time latencies of communicated signals but also eliminate various measurement uncertainties and noise by modeling foot of uncertainty (FOU). First, eigenvalue analysis of the system is performed to identify interarea modes responsible for small-signal instability. To nullify this instability, a control scheme is proposed. In proposed control scheme, participation factors are utilized to select suitable controller location. However, feedback signals are chosen through controllability indexes. Later, type-1 and type-2 controllers are designed by changing membership functions. Performance of type-2 controllers is checked for different FOUs. Furthermore, type-1 and type-2 controllers are compared, in terms of settling time, peak overshoot, and damping factor. Effectiveness of proposed control scheme and controllers are successfully tested on two-area four-machine and five-area sixteen-machine systems.

Hybrid Passivity Based and Fuzzy Type-2 Controller for Chaotic and Hyper-Chaotic Systems

Abstract In this paper a hybrid passivity based and fuzzy type-2 controller for chaotic and hyper-chaotic systems is presented. The proposed control strategy is an appropriate choice to be implemented for the stabilization of chaotic and hyper-chaotic systems due to the energy considerations of the passivity based controller and the flexibility and capability of the fuzzy type-2 controller to deal with uncertainties. As it is known, chaotic systems are those kinds of systems in which one of their Lyapunov exponents is real positive, and hyper-chaotic systems are those kinds of systems in which more than one Lyapunov exponents are real positive. In this article one chaotic Lorentz attractor and one four dimensions hyper-chaotic system are considered to be stabilized with the proposed control strategy. It is proved that both systems are stabilized by the passivity based and fuzzy type-2 controller, in which a control law is designed according to the energy considerations selecting an appropriate storage function to meet the passivity conditions. The fuzzy type-2 controller part is designed in order to behave as a state feedback controller, exploiting the flexibility and the capability to deal with uncertainties. This work begins with the stability analysis of the chaotic Lorentz attractor and a four dimensions hyper-chaotic system. The rest of the paper deals with the design of the proposed control strategy for both systems in order to design an appropriate controller that meets the design requirements. Finally, numerical simulations are done to corroborate the obtained theoretical results.

Semi-active seismic control of an 11-DOF building model with TMD+MR damper using type-1 and -2 fuzzy algorithms

Nowadays, vibration control of structures is considered as a challenging field among scientists and engineers. Structural damage and financial losses due to recent earthquakes in different countries have more than ever before accentuated the importance of controlling earthquake-induced vibrations. In recent years, semi-active control has been introduced as an efficient and reliable type of structural control which provides the reliability of passive control and flexibility of active control systems at the same time. In this study, the performance of a semi-active tuned mass damper (TMD) with adaptive magnetorheological (MR) damper is investigated using type-1 and -2 fuzzy controllers for seismic vibration mitigation of an 11-degree of freedom building model. The TMD is installed on the roof and the MR damper is located on the 11th story. The MR damper has a capacity of producing a 1000 kN control force. The fuzzy system is designed based on the acceleration and velocity of the top floor determining the input voltage needed to produce the control force based on accelerating or decelerating movements of structure. The seismic performance of semi-active type-2 controller, which considers the uncertainties related to input variables, is higher than that of the type-1 fuzzy controller. The type-2 fuzzy controller is capable of reducing further the maximum displacement, acceleration, and base shear of the structure by 11.7, 14, and 11.2%, respectively, compared to the type-1 fuzzy controller.

Type-2 fuzzy logic controller for position control of shape memory alloy wire actuator

The main aim of this article is to present the usage of type-2 fuzzy logic controller to control a shape memory actuator. One of the main advantages of the fuzzy systems is that they do not require creating any mathematical model of the controlled plant which simplifies the control task. However, a dynamic system model was created to adjust the proportional–integral–derivative controller parameters. Different types of controllers were tested experimentally by controlling the position of the commercially available shape memory alloy actuator NM70 made by Miga Motor company. Despite its small size, it distinguishes itself by its strength. To enhance real-time performance, simplified interval fuzzy sets were used. The algorithm was implemented in the ATmega32 microcontroller. The dedicated PC application was also built. The obtained results confirmed that type-2 fuzzy controller performed efficiently with a nonlinear plant which is difficult to control. The research also proved that interval type-2 controllers, which are a simplified version of the general type-2 controllers, are very efficient. They can handle uncertainties without increasing drastically the computational complexity. Experimental data comparison of the proportional–integral–derivative reference with the fuzzy logic controller type-2 and type-1 clearly indicates the superiority of the former, especially in reducing overshooting.

이동로봇 선회를 위한 Type-2 Fuzzy Self-Tuning PID 제어기 설계 및 조향각 제어

이동로봇 선회를 위한 Type-2 Fuzzy Self-Tuning PID 제어기 설계 및 조향각 제어

Status of some Trace Elements in Type-2 Diabetic Patients and its Relationship with Lipid Profile

Investigation of the serum level of copper, zinc, magnesium and manganese in type-2 diabetes mellitus and their possible association with lipid profile was carried out. The comparative study included 100 type-2 diabetic patients in Gr-II and 100 non-diabetic as control in (Gr-I). Results indicated that there is a significant lower level (p < .001) of serum Zn, Cu, Mg and Mn in diabetic patients compared with the control group, showing p value < .001. In type-2 DM patients (Gr-II) there were significant correlations between serum Zn and TAG (r = 0.209) and between Zn and HDL-C level (r = .199) showing p value <.05. Non significant relationships were found in between Zn and lipid profile (TAG, Cholesterol, HDL-C and LDL-C) of control (Gr-I) group. Significant correlation was found between serum magnesium and TAG of control (Gr-I) where p < .01 and non significant correlations were found in serum Mg and total cholesterol, HDL-C, LDL-C of both type-2 diabetic (Gr-II) and control (Gr-I). Significant correlations were also found in between serum of Cu and Mn and TAG of control (Gr-I) where p < .05 and non significant correlations were found in other component of lipid profile of both cases (Gr-II) and control (Gr-I).Journal of Bangladesh Academy of Sciences, Vol. 40, No. 1, 79-85, 2016

Deriving and Analyzing Analytical Structures of a Class of Typical Interval Type-2 TS Fuzzy Controllers.

A conventional controller's explicit input-output mathematical relationship, also known as its analytical structure, is always available for analysis and design of a control system. In contrast, virtually all type-2 (T2) fuzzy controllers are treated as black-box controllers in the literature in that their analytical structures are unknown, which inhibits precise and comprehensive understanding and analysis. In this regard, a long-standing fundamental issue remains unresolved: how a T2 fuzzy set's footprint of uncertainty, a key element differentiating a T2 controller from a type-1 (T1) controller, affects a controller's analytical structure. In this paper, we describe an innovative technique for deriving analytical structures of a class of typical interval T2 (IT2) TS fuzzy controllers. This technique makes it possible to analyze the analytical structures of the controllers to reveal the role of footprints of uncertainty in shaping the structures. Specifically, we have mathematically proven that under certain conditions, the larger the footprints, the more the IT2 controllers resemble linear or piecewise linear controllers. When the footprints are at their maximum, the IT2 controllers actually become linear or piecewise linear controllers. That is to say the smaller the footprints, the more nonlinear the controllers. The most nonlinear IT2 controllers are attained at zero footprints, at which point they become T1 controllers. This finding implies that sometimes if strong nonlinearity is most important and desired, one should consider using a smaller footprint or even just a T1 fuzzy controller. This paper exemplifies the importance and value of the analytical structure approach for comprehensive analysis of T2 fuzzy controllers.

Speed control of electrical vehicles: a time‐varying proportional–integral controller‐based type‐2 fuzzy logic

The control of electrical vehicles (EVs) should be designed robustly and adaptively to improve the system on both dynamic and steady-state performances, because EV systems are basically time variant (e.g. the operation parameters of EV and the road condition are always varying) that make the operation of controlling an EV difficult. In this study, general type-2 fuzzy logic sets and the modified harmony search algorithm techniques for adaptive tuning of the most popular existing proportional–integral (PI) controller is integrated in order to address these uncertainties. Although it is computationally expensive to carry out general type-2 fuzzy systems, it can be examined as a composition of several interval type-2 fuzzy logic systems with a corresponding level of α for each by using a new plan which is presented, general type-2 fuzzy set. The controller uses the linguistic rules directly. The achieved results are compared with optimal fuzzy-PI controller and optimal interval type-2 fuzzy-PI controller results which are the most recent researches into in the present issue to evaluate the proficiency of the proposed controller. The simulation results demonstrate the successfulness and effectiveness of the proposed controller.

A Novel Type-1 Frequency-Locked Loop for Fast Detection of Frequency and Phase With Improved Stability Margins

The synchronous reference frame phase-locked loop (SRF-PLL) is a widely used synchronization technique in power electronics and power systems applications due to its ease of implementation and robust performance. The conventional SRF-PLL is a type-2 control system due to the use of proportional-integral controller as loop filter. With higher bandwidth design, it can achieve fast detection of frequency and phase under ideal grid conditions. However, its bandwidth should be sufficiently lowered to obtain proper disturbance rejection under unbalanced and distorted grid conditions. This results in a slower detection speed. Recently, several advanced PLLs with pre/in-loop filtering stage have been proposed to improve the detection speed. A major challenge with the PLLs is how to further improve their dynamic performance without compromising the disturbance rejection capability and stability. To resolve this issue, in this paper, a novel type-1 frequency-locked loop (FLL) is proposed. The disturbance rejection capability of the proposed FLL is improved using a modified structure low-pass filter with selective harmonics filtering ability. As the proposed FLL is type-1 control system, it achieves better dynamic performance with higher stability margins. The effectiveness of the proposed FLL is confirmed through experimental results and comparison with advanced type-2 PLLs.

ON THE CONTROL OF TUMOR GROWTH VIA TYPE-1 AND INTERVAL TYPE-2 FUZZY LOGIC

This paper deals with growth control of cancer cells population using type-1 and interval type-2 fuzzy logic. A type-1 fuzzy controller is designed in order to reduce the population of cancer cells, adjust the drug dosage in a manner that allows normal cells re-grow in treatment period and maintain the maximum drug delivery rate and plasma concentration of drug in an appropriate range. Two different approaches are studied. One deals with reducing the number of cancer cells without any concern about the rate of decreasing, and the other takes the rate of malignant cells damage into consideration. Due to the fact that uncertainty is an inherent part of real systems and affects controller efficacy, employing new methods of design such as interval type-2 fuzzy logic systems for handling uncertainties may be efficacious. Influence of noise on the system is investigated and the effect of altering free parameters of design is studied. Using an interval type-2 controller can diminish the effects of incomplete and uncertain information about the system, environmental noises, instrumentation errors, etc. Simulation results confirm the effectiveness of the proposed methods on tumor growth control.

A coordinated genetic based type-2 fuzzy stabilizer for conventional and superconducting generators

This paper presents a new coordinated genetic interval type-2 fuzzy stabilizer for enhancing stability of a single machine infinite-bus (SMIB) power system including conventional or superconducting generators. Its principle is based on a coordination done by implementing simultaneously, interval type-2 fuzzy controllers, into excitation and turbine governor systems. Optimal adjustment of scaling factors has been carried out using genetic algorithms (GAs). Type-2 fuzzy controller provides improvement in comparison with type-1 controller in terms of modeling and minimizing the effect of uncertainties. Furthermore, governor control helps in damping oscillations enhancement especially in case of superconducting machine when excitation control alone is not sufficient. Non-linear simulation results of a SMIB power system, under different operating conditions, prove the effectiveness and the robustness of the proposed optimized type-2 fuzzy stabilizer (GFLC2EG) for both conventional and superconducting generators. In order to validate the robust performance of the proposed stabilizer, a comparative study is presented showing its superiority over other types of stabilizers.

A Self-Tuning zSlices-Based General Type-2 Fuzzy PI Controller

The interval type-2 fuzzy Proportional-Integral (PI) controller (IT2-FPI) might be able to handle high levels of uncertainties to produce a satisfactory control performance, which could be potentially due to the robust performance as a result of the smoother control surface around the steady state. However, the transient state and disturbance rejection performance of the IT2-FPI may degrade in comparison with the type-1 fuzzy PI (T1-FPI) counterpart. This drawback can be resolved via general type-2 fuzzy PI controllers which can provide a tradeoff between the robust control performance of the IT2-FPI and the acceptable transient and disturbance rejection performance of the type-1 PI controllers. In this paper, we will present a zSlices-based general type-2 fuzzy PI controller (zT2-FPI), where the secondary membership functions (SMFs) of the antecedent general type-2 fuzzy sets are adjusted in an online manner. We will examine the effect of the SMF on the closed-system control performance to investigate their induced performance improvements. This paper will focus on the case followed in conventional or self-tuning fuzzy controller design strategies, where the aim is to decrease the integral action sufficiently around the steady state to have robust system performance against noises and parameter variations. The zSlices approach will give the opportunity to construct the zT2-FPI controller as a collection of IT2-FPI and T1-FPI controllers. We will present a new way to design a zT2-FPI controller based on a single tuning parameter where the features of T1-FPI (speed) and IT2-FPI (robustness) are combined without increasing the computational complexity much when compared with the IT2-FPI structure. This will allow the proposed zT2-FPI controller to achieve the desired transient state response and provide an efficient disturbance rejection and robust control performance. We will present several simulation studies on benchmark systems, in addition to real-world experiments that were performed using the PIONEER 3-DX mobile robot that will act as a platform to evaluate the proposed systems. The results will show that the control performance of the self-tuning zT2-FPI control structure enhances both the transient state and disturbance rejection performances when compared with the type-1 and IT2-FPI counterparts. In addition, the self-tuning zT2-FPI is more robust to disturbances, noise, and uncertainties when compared with the type-1 and interval type-2 fuzzy counterparts.

Design and Implementation of Type-2 Fuzzy Logic Controllers for the Posture of Manipulator Robot Tip

Uncertainty is an inherent part in controllers for real world applications. In this paper fuzzy logic controllers in two structure type-1 (FLCT1) and type-2 (FLCT2) are proposed, the FLCT2 introduce with three terms and with five terms to use as controller for the tip manipulator robot. We compare the performance of the manipulator robot with the FLCT1 and FLCT2, with five and three term membership functions. The controllers were used to control a PM DC motor model in a closed loop real time system. The results showed that there was statistical difference between the type-1 and type-2 controllers. It was also found that a type-2 three term controller was as good as a type-1five term or type-2 five term controller.