Type-2 Fuzzy Logic Controller Research Articles

Active fault tolerant control based on interval type-2 fuzzy sliding mode controller and non linear adaptive observer for 3-DOF laboratory helicopter

In this paper, a robust controller for a three degree of freedom (3 DOF) helicopter control is proposed in presence of actuator and sensor faults. For this purpose, Interval type-2 fuzzy logic control approach (IT2FLC) and sliding mode control (SMC) technique are used to design a controller, named active fault tolerant interval type-2 Fuzzy Sliding mode controller (AFTIT2FSMC) based on non-linear adaptive observer to estimate and detect the system faults for each subsystem of the 3-DOF helicopter.The proposed control scheme allows avoiding difficult modeling, attenuating the chattering effect of the SMC, reducing the rules number of the fuzzy controller.Exponential stability of the closed loop is guaranteed by using the Lyapunov method. The simulation results show that the AFTIT2FSMC can greatly alleviate the chattering effect, providing good tracking performance, even in presence of actuator and sensor faults.

Robust control of shunt active power filter using interval type-2 fuzzy logic controller for power quality improvement

Robust control of shunt active power filter using interval type-2 fuzzy logic controller for power quality improvement

Type-2 fuzzy adaptive sliding mode control of hypersonic flight

This paper proposes a type-2 fuzzy adaptive sliding mode control scheme for tracking control of hypersonic aircraft with uncertainties. This method uses full-state feedback to linearize the nonlinear model of hypersonic aircraft. Combining the interval type-2 fuzzy approach and adaptive sliding mode control keeps the system stable in the existence of uncertain parameters. For rapid stabilization of the system, the adaptive laws are designed using a direct constructive Lyapunov analysis together with a well-established type-2 fuzzy logic control. Simulation test results indicate that the proposed control scheme provides enhancement of robustness to parametric uncertainty and improvement in tracking performance of the hypersonic aircraft.

Double anti-roll bar hardware-in-loop experiment for active anti-roll control system

Active anti-roll bar (AARB) is a cheaper alternative for a fully active suspension system, which can be adapted into passenger cars, made possible by today’s technology. AARB minimizes body roll and improve ride comfort. In this paper, the design of a Hardware-in-loop (HIL) test bench is presented. The HIL test bench is able to test dual AARB system, each for front and rear of a car respectively. HIL testing will allow designer to analyze and validate the performance of the proposed AARB system before it could be implemented in a real car. This paper focuses on the practicality and adaptability of implementing Fuzzy based PID controllers into the AARB system. HIL experiment compares the performance of proposed Self-Tuning Fuzzy PI-PD (STF PI-PD) controller against the PI-PD Type Fuzzy Logic Controller (PI-PD Type FLC) and Self-Tuning Fuzzy PID (STF PID) controllers. STF PID controller was proposed by previous researchers for an AARB system. Experimental results suggest that the proposed AARB system, which incorporates STF PI-PD controller is able to reduce 87.68 % of roll angle and 50.04 % in roll rate in average, thus improving the vehicle dynamics. STF PI-PD controller significantly outperforms both STF PID and PI-PD Type FLC controllers in various handling tests.

Novel type-2 fuzzy logic approach for inference of corrosion failure likelihood of oil and gas pipeline industry

Abstract Among the various means of transportation of products from oil and gas industry, pipelines are considered to be the safest way. Still pipelines are to failure due to corrosion resulting (that causes) leakage and rupture. Although corrosion has the nature of uncertainty, the estimation of corrosion failure likelihood (CFL) is very difficult. To mitigate this difficulty, an analytic model for estimating CFL of oil and gas pipelines was developed by means of type-2 fuzzy logic controller system (T2FLCS) approach. The corrosion failure modes considered two types of events such as corrosion thinning and corrosion cracking. The major controlling factors of CFL of pipelines were Corrosion thinning factor, corrosion cracking factor, inspection effectiveness, and inspection times. The influence of controlling factors on type-2 fuzzy rules between the factors and CFL was determined. The assessment results derived from the model can be used as valuable reference for working out pipeline inspection and maintenance plans to a natural gas pipeline to assess the CFL.

Takagi-Sugeno Fuzzy Perpose as Speed Controller in Indirect Field Oriented Control of Induction Motor Drive

This paper deal with the problem in speed controller for Indirect Field Oriented Control of Induction Motor. The problem cause decrease performance of Induction Motor where it widely used in high-performance applications. In order decrease the fault of speed induction motor, Takagi-Sugeno type Fuzzy logic control is used as the speed controller. For this, a model of indirect field oriented control of induction motor is built and simulating using MATLAB simulink. Secondly, error of speed and derivative error as the input and change of torque command as the output for speed control is applied in simulation. Lastly, from the simulation result overshoot is zero persent, rise time is 0.4s and settling time is 0.4s. The important data is steady state error is 0.01 percent show that the speed can follow reference speed. From that simulation result illustrate the effectiveness of the proposed approach.

Adaptive Interval Type-2 Fuzzy Logic Control for PMSM Drives With a Modified Reference Frame

In this paper, an adaptive interval type-2 fuzzy logic control scheme is proposed for high-performance permanent magnet synchronous machine drives. This strategy combines the power of type-2 fuzzy logic systems with the adaptive control theory to achieve accurate tracking and robustness to higher uncertainties. Unlike other controllers, the proposed strategy does not require electrical transducers and hence, no explicit currents loop regulation is needed, which yields a simplified control scheme. But, this limits the machine's operation range since it results in a higher energy consumption. Therefore, a modified reference frame is also proposed in this paper to decrease the machine's consumption. To better assess the performance of the new reference frame, comparison against its original counterpart is carried-out under the same conditions. Moreover, the stability of the closed-loop control scheme is guaranteed by a Lyapunov theorem. Simulation and experimental results for numerous situations highlight the effectiveness of the proposed controller in standstill, transient, and steady-state conditions.

Cuckoo search algorithm based design of interval Type-2 Fuzzy PID Controller for Furuta pendulum system

The Interval Type-2 Fuzzy Logic Controller (IT2FLC) is an advanced version of Type-1 Fuzzy Logic Controller (T1FLC) that improves the control strategies by using the advantage of its footprint of uncertainty of the Fuzzy Membership Function (MF). Numerous experimental investigations have shown the superiority of IT2FLC over T1FLC, particularly in high level of uncertainties and nonlinearities. Nevertheless, the systematic design of IT2FLCs remains an attractive problem because of the difficulty in finding the parameters associated with IT2FLCs. In this study, a novel application of Cuckoo Search (CS) algorithm in the design of an optimized cascade Interval Type-2 Fuzzy Proportional Integral Derivative Controller (IT2FPIDC) is presented. The PID gains and the parameters of the antecedent MFs of IT2FPIDC are optimized using CS algorithm. Considering the higher number of parameters to be optimized in cascade IT2FPIDC, the CS method was employed due to its high convergence speed and less computational cost. The proposed CS based cascade optimized IT2FPIDC is compared with CS-based Type-1 Fuzzy Proportional Integral Derivative Controller (T1FPIDC). The present research presents a new application of proposed CS based cascade optimized IT2FPIDC for the balancing control and trajectory tracking control of the Furuta pendulum (FP) which is a nonlinear, non-minimum phase and unstable system. Furthermore, the disturbance rejection ability of the proposed controller is analyzed. The proposed control strategies are evaluated on FP produced by Quanser through numerous experimentations in the real world as well as simulation. The performance characteristic considered for these controllers are settling time (ts), steady state error (Ess), rise time (tr) and maximum overshoot (Mp). Both the simulation and real world experiments results demonstrated the robustness and effectiveness of the proposed CS based IT2FPIDC with respect to parameter variation, noise effects and load disturbances, with an improved performance of 27.1%, 5.7% and 20.8% for tr, ts and Mp respectively over its CS based T1FPIDC counterpart.

Simulation of Type 1Fuzzy Logic MPPT Controller for PV System

Simulation of Type 1Fuzzy Logic MPPT Controller for PV System

A novel interval type-2 fractional order fuzzy PID controller: Design, performance evaluation, and its optimal time domain tuning

In this paper, a novel concept of an interval type-2 fractional order fuzzy PID (IT2FO-FPID) controller, which requires fractional order integrator and fractional order differentiator, is proposed. The incorporation of Takagi-Sugeno-Kang (TSK) type interval type-2 fuzzy logic controller (IT2FLC) with fractional controller of PID-type is investigated for time response measure due to both unit step response and unit load disturbance. The resulting IT2FO-FPID controller is examined on different delayed linear and nonlinear benchmark plants followed by robustness analysis. In order to design this controller, fractional order integrator-differentiator operators are considered as design variables including input-output scaling factors. A new hybridized algorithm named as artificial bee colony-genetic algorithm (ABC-GA) is used to optimize the parameters of the controller while minimizing weighted sum of integral of time absolute error (ITAE) and integral of square of control output (ISCO). To assess the comparative performance of the IT2FO-FPID, authors compared it against existing controllers, i.e., interval type-2 fuzzy PID (IT2-FPID), type-1 fractional order fuzzy PID (T1FO-FPID), type-1 fuzzy PID (T1-FPID), and conventional PID controllers. Furthermore, to show the effectiveness of the proposed controller, the perturbed processes along with the larger dead time are tested. Moreover, the proposed controllers are also implemented on multi input multi output (MIMO), coupled, and highly complex nonlinear two-link robot manipulator system in presence of un-modeled dynamics. Finally, the simulation results explicitly indicate that the performance of the proposed IT2FO-FPID controller is superior to its conventional counterparts in most of the cases.

Forkloader Position Control for A Mini Heavy Loaded Vehicle using Fuzzy Logic-Antiwindup Control

This paper presents a proposed integrated Takagi-Sugeno-Kang (TSK) type Fuzzy Logic control (TSK-FLC) with Antiwindup elements for a forkloader position control of a Mini Heavy Loaded Forklift Autonomous Guided Vehicle (MHeLFAGV). The study was carried out by modeling TSK-FLC as a close-loop control for the each axis of the fork-lift’s movement. The degree of membership is designed with reference to the system response, in which ultrasonic sensor with 1cm resolution is used. Moreover, the rule base is determined and optimized to deal with microcontroller processing speed. In order to cater for the windup phenomenon, a proportional and integrated antiwindup elements are integrated into the TSK-FLC model. This control strategy consumes less memory and is expected to increase the time response of the control system. The experiment and analysis is done on the actual forkloader unit of MHeLFAGV system. The experiment was done on the vertical axis motion since horizontal motion will have the same characteristic pattern of implementation and characteristic of tuning. The experiment shows that the proposed integrated TSK-FLC with antiwindup elements is able to speed up the time response of the system and eliminate the overshoot as well as oscillation on the forkloader movement.

A Singleton Type-1 Fuzzy Logic Controller for On-Line Error Compensation During Robotic Welding

During robot welding operations in the manufacturing industry there is a need to modify on-line the welding path due to a mismatch in the position of the components to be welded. These positioning errors are due to multiple factors such as ageing of the components in the conveyor system, clamp fixtures, disturbances, etc. Therefore, robot reprogramming is needed which requires a stop in the production line and consequently an increment in production costs. This article is an extension of [1]a and presents an alternative solution to this problem that involves the use of structured lighting using a low-cost laser beam, a CMOS camera and a Gaussian singleton fuzzy logic controller. To validate the proposed control system, a robotic cell was designed using an industrial KUKA KR16 robot for welding metallic plates. The method was evaluated experimentally under lateral and vertical positioning errors.

A time-varying strategy for urban traffic network control: a fuzzy logic control based on an improved black hole algorithm

Urban traffic network (UTN) models are usually illustrated by state-charts (CH) and object-diagrams (OD). So, a state space model is usually used to calculate the half-value waiting time of vehicles in UTN with a stabled time control. In this study, a combination of the general type-2 fuzzy logic sets (GT2FLS) and the modified black hole (MBH) algorithm techniques is used in order to control the traffic signal scheduling and phase succession so as to guarantee the smooth flow of traffic with the least waiting time and average queue length. A comparison is made between the results obtained regarding the performance of the proposed model and those of the optimal type-1 fuzzy logic (OT1FL) and conventional type-1 fuzzy logic (CT1FL) controllers, which are the most recent researches in the problem at hand. The simulation results prove the successfulness and effectiveness of the proposed controller.

Design of Type-2 Fuzzy Logic Controller for Fluid Catalytic Cracking Unit

Modelling and controlling of fluid catalytic cracking unit (FCCU) is a challenging problem since it is a highly nonlinear and interacting process. Model of FCCU that describes the dynamic behaviour of reactor and regenerator has been developed by considering energy and material balance equations. Fuzzy logic control technique in the field of intelligent control has been used in this paper since it handles uncertainty very well. In this work, centralised Mamdani types T1-FLC and T2-FLC have been designed for FCCU to control the reactor and regenerator temperature (RT). The closed-loop simulation study for servo and servo with regulatory performance has been carried out for the two controllers and the performances have been analysed. The comparative study of these two control schemes reveals that the type-2 FLC gives better performance than type-1 FLC.

Satellite antenna position control with adaptive controller

The paper deals with satellite antenna position control system for the vehicle, which controlled by using conventional proportional-integral-derivative (PID) controllers and adaptive controller with Takagi-Sugeno-Kang type fuzzy logic controllers, which was developed. In order to obtain performance of the step-tracking algorithm and system response to various external perturbations the simulation model was developed in Matlab / Simulink environment. In the considered systems, adaptive controller is more suitable for the implementation of the step-tracking algorithm and it is more robust to external perturbations in comparison with conventional PID-controllers. Figs.: 5. Refs.: 10 titles.Keywords: fuzzy logic controller; Takagi-Sugeno-Kang; adaptive controller; position control; satellite antenna; step-tracking algorithm.

Modelling and Performance Comparison of PD and Takagi-Sugeno Type Fuzzy Logic Controllers for Inverted Pendulum System

In recent years, fuzzy logic based modeling and control methods have been increasingly used in both industrial applications and academic field. Inverted pendulum system consists of conventional materials with nonlinear dynamic structure to test types of controllers. This paper presents a simulation study of Takagi-Sugeno type Fuzzy Logic Controllers for an inverted pendulum (cart-pole) system. A Takagi-Sugeno method was applied to the inverted-pendulum system, which can balance the pendulum over a bigger range of pole angle and cart position. Fuzzy logic controller proposed in this study is compared with the conventional PD controller in order to demonstrate the successes of the proposed controller. This study aims to determine the best control strategy that provides better performance with reference to pendulum's angle and cart's position. A Takagi-Sugeno type Fuzzy Logic Controller yields better results in terms of rise time, settling time, overshoot and steady state error compared to PD controller. Simulation results are shown to prove the effectiveness and robustness of the suggested fuzzy controller.

Fuzzy Logic Controller Based Distributed Generation Integration Strategy for Stochastic Performance Improvement

In the restructured environment, distributed generation (DG) is considered as a very promising option due to a high initial capital cost of conventional plants, environmental concerns, and power shortage. Apart from the above, distributed generation (DG) has also abilities to improve performance of feeder. Most of the distribution feeders have radial structure, which compel to observe the impact of distributed generations on feeder performance, having different characteristics and composition of time varying static ZIP load models. Two fuzzy-based expert system is proposed for selecting and ranking the most appropriated periods to an integration of distributed generations with a feeder. Madami type fuzzy logic controller was developed for sizing of distributed generation, whereas Sugeno type fuzzy logic controller was developed for the DG location. Input parameters for Madami fuzzy logic controller are substation reserve capacity, feeder power loss to load ratio, voltage unbalance, and apparent power imbalances. DG output, survivability index, and node distance from substation are chosen as input to Sugeno type fuzzy logic controller. The stochastic performance of proposed fuzzy expert systems was evaluated on a modified IEEE 37 node test feeder with 15 minutes characteristics time interval varying static ZIP load models.

An optimal general type-2 fuzzy controller for Urban Traffic Network

Urban traffic network model is illustrated by state-charts and object-diagram. However, they have limitations to show the behavioral perspective of the Traffic Information flow. Consequently, a state space model is used to calculate the half-value waiting time of vehicles. In this study, a combination of the general type-2 fuzzy logic sets and the Modified Backtracking Search Algorithm (MBSA) techniques are used in order to control the traffic signal scheduling and phase succession so as to guarantee a smooth flow of traffic with the least wait times and average queue length. The parameters of input and output membership functions are optimized simultaneously by the novel heuristic algorithm MBSA. A comparison is made between the achieved results with those of optimal and conventional type-1 fuzzy logic controllers.

Free chattering hybrid sliding mode control for a class of non‐linear systems: electric vehicles as a case study

In current study, in order to find the control of general uncertain nonlinear systems, a new optimal hybrid control approach called Optimal General Type II Fuzzy Sliding Mode (OGT2FSM) is presented. In order to estimate unknown nonlinear activities in monitoring dynamic uncertainties, the benefits of general type-2 fuzzy logic systems (GT2FLS) is utilized by the suggested controller. The suggested controller not only warranties the constancy and hardiness against uncertainties of the lumped resulted by external disturbances and un-modeled dynamics, but also considerably decreases the control chattering inherent in traditional sliding mode control. Moreover, the Modified Backtracking Search Algorithm (MBSA), which is a new heuristic algorithm, is used in the offered controller. A comparison is performed between the results of current study and the results of some of the most recent studies on the same topic, which are an Adaptive Interval Type-2 Fuzzy Logic Controller (AGT2FLC) and Conventional Sliding Mode Controller (CSMC), to assess the efficiency of the suggested controller. The suggested control scheme is finally used to the Electric Vehicles type as a case study. Results of simulation confirm the good performance the suggested controller.

A new fuzzy bee colony optimization with dynamic adaptation of parameters using interval type-2 fuzzy logic for tuning fuzzy controllers

This paper presents a new fuzzy bee colony optimization method to find the optimal distribution of the membership functions in the design of fuzzy controllers for complex nonlinear plants. We used interval type-2 and type-1 fuzzy logic systems in dynamically adapting the alpha and beta parameter values of the bee colony optimization algorithm (BCO). Simulation results with a type-1 fuzzy logic controller for benchmark control plants are presented. The advantage of using interval type-2 fuzzy logic systems for dynamic adjustment of parameters in BCO applied in fuzzy controller design is verified with two benchmark problems. We considered different levels and types of noise in the simulations to analyze the approach of interval type-2 fuzzy logic systems to find the best values of alpha and beta for BCO when applied in the design of fuzzy controllers.