Logic Controller Structure Research Articles

Experimental validation of fuzzy type‐2 against type‐1 scheme applied in DC/DC converter integrated to a PEM fuel cell system

AbstractThis research presents and compares the outcomes of experimental implementations of different fuzzy logic control structures for a proton exchange membrane fuel cell (PEMFC). These devices are well known for their capability to transform chemical energy into electrical with low emissions. Commonly, a PEMFC has a linkage with a boost converter which allows a suitable end‐user voltage through a nonlinear control law. Hence, the contribution in this sense is the experimental comparison of two fuzzy logic strategies known as type‐1 and type‐2 that were implemented in a PEMFC system. The approaches were embedded in a control board dSPACE 1102 which also has the capability to acquire data. The contrast of results showed capabilities improvement against disturbances in terms of error reduction, control signal, and robustness.

Aggressive maneuvering of a quadcopter via differential flatness-based fuzzy controllers: From tuning to experiments

In recent years, the rapid development in contemporary technology has brought nano quadcopters with high agility. This paper presents a new differential flatness-based Single Input Fuzzy Logic Controller (SFLC) structure for aggressive maneuvering control alongside its real-world application on Crazyflie 2.1 nano quadcopter. We propose both Type-1 and Interval Type-2 SFLCs as the primary controllers in the flight control system, which are built on the concept of differential flatness. We investigate how the design parameters of SFLCs shape the characteristics of the fuzzy mapping through a geometric approach by analyzing the region and level of aggressiveness/smoothness. Based on the analysis, we present simple tuning guidelines and then design fuzzy logic-based flight control systems, which were implemented as onboard real-time controllers. Finally, we evaluate the performance of SFLCs in comparison with their crisp differential flatness-based nonlinear counterparts for four trajectories with distinct dynamics and shapes in the real world. The presented comparative experimental results clearly show the performance improvements when the proposed T1 and IT2 SFLCs are deployed for real-time aggressive maneuvering.

Optimal design of fuzzy-PID controller for automatic generation control of multi-source interconnected power system

This paper suggests a fuzzy logic controller (FLC) structure from seven membership functions (MFs) and its input–output relationship rules to design a secondary controller to reduce load frequency control (LFC) issues. The FLC is coupled to a proportional–integral–derivative (PID) controller as the proposed FPID controller, which is tuned by an optimized water cycle algorithm (WCA). The proposed WCA: FPID scheme was implemented with two models from the literature under the integral time absolute error cost function. Initially, a two-area non-reheat unit was implemented, and the gains of PID and FPID controllers were adjusted to verify the suitability of WCA in solving LFC issues. Then, in order to identify the robustness of the closed-loop system, sensitivity analysis is carried out. Additionally, a two-area non-reheat unit was tested under the governor dead band nonlinearity. To guarantee the suitability of the proposed FPID controller, a model with a mixture of power plants, such as reheat, hydro, and gas unit in each area was carried out with and without the HVDC link, which can increase practical issues with LFC. The proposed controller's robustness was studied for all models under numerous scenarios, step load perturbations (SLP), and different objective functions. Simulation results proved that the proposed FPID controller provided superior performance compared to recently reported techniques in terms of peaks and settling time.

Enhancement of Transient Stability in a Grid-Connected Wind Power Plant Utilizing PI-FL Controller

This paper proposed a blend of corresponding PIC and FLC for controlling the pitch angle of wind turbine connected to grid. Initially, conventional control methodology is employed to design the PI controller and later on, the concept of fuzzy logic methodology is adapted to analyze the gains of proportional integral controller. Due to versatility of fuzzy logic controller and rugged structure, sturdy nature of proportional integral controller are clubbed together, it provides a virtuous stagnant and dynamic outcomes. The proposed novel technique can be assessed by considering various disturbances such as short circuit network fault. The reenactment after effects of proposed controller is contrasted with proportional integral controller and FLC. From the findings it is shown that the proposed methodology could improve stability even the wind farm is subjected to different operating conditions. Moreover, a performance index in terms of absolute maximum deviations is defined in order to evaluate the adequacy of the proposed controller.

Comparison of regular and irregular 32 pulse density modulation patterns for induction heating

In this study, an induction heating (IH) application is carried out by transferring the maximum power extracted from photovoltaic (PV) panels to the stainless steel with the designed regular and irregular 32 pulse density modulation (PDM) controlled series resonant inverter. The main objective of this study is to analyse the changes in the system due to regular and irregular PDM patterns. Maximum power point tracker (MPPT) is used to control the output power at different solar irradiation values with varying PDM patterns. Regular and irregular PDM control methods are compared in terms of MPPT efficiency, cost, algorithm complexity, logic control structure and current/voltage stresses of the power switches. Zero current switching (ZCS) conditions are provided by using phase locked loop (PLL) technique at all power points of the PV system. The appropriate switching conditions are tracked continuously at resonant frequency, and therefore soft switching is realised. Perturb and observe (P&O) algorithm is used with the aim of tracking the maximum power in PV panels and high tracking efficiency is obtained with PDM-controlled P&O MPPT algorithm. ATMEL328P-AU microcontroller is used to control the inverter in the system.

A novel-designed fuzzy logic control structure for control of distinct chaotic systems

In this paper, a Lyapunov-based fuzzy logic control (FLC) system is developed for controlling of complicated as well as distinct nonlinear systems. According to Lyapunov Stability Theory, a candidate Lyapunov function with simple quadratic form is designed. Via constructing the fuzzy IF–THEN rules through referencing the statuses of errors states and error derivatives in each sub-space of the Lyapunov function derivatives, the proposed structure of FLC system is able to appropriately as well as flexibly adjust the control forces with minimum magnitude compensating the nonlinear systems in real-time. In addition, the designed FLC system can be applied to different kinds of control systems without further information and operation experience. Two nonlinear systems with distinct structures, classical Lorentz system and Mathieu-van der Pol system, are illustrated for simulation examples. In comparison of the previous research work, the simulation results reveal the effectiveness, flexibility and convenient-design of the proposed method.

CPG-based autonomous swimming control for multi-tasks of a biomimetic robotic fish

This work emphasizes the artificial intelligent control of the developed biomimetic robotic fish (i-RoF) based on sensory feedback Central Pattern Generator (CPG) approach. In order to obtain rhythmic, robust and adaptable closed loop control performance, a novel control mechanism, composed of two subsystems; as a biological based CPG network and a Fuzzy Logic controller, is proposed. The CPG network behaves as an artificial spinal cord, inspired by Lampreys. It is constructed as unidirectional chained network with Sensory Neurons (SNs) which can perceive the external stimulus. The Fuzzy Logic control structure is also designed as a decision-making mechanism and a Finite State Machine (FSM) algorithm is proposed to perform the given missions autonomously. In the experimental studies, different scenarios are created for both situations as autonomous swimming and encountering obstacles while taking on a primary task, which is determined with yaw control. Autonomous swimming ability is performed in the real pool environment with proposed scenarios that are likely to be encountered in a real environment. It is observed that autonomous swimming performance is excellent and yaw control is quite good even in the presence of obstacles. It is also proved that the escape performance of the robot is very fast.

Locomotion control of a biomimetic robotic fish based on closed loop sensory feedback CPG model

ABSTRACT This paper presents mechatronic design and hierarchical locomotion control of a biomimetic robotic fish for three-dimensional swimming modes. Inspired by biological features of Lamprey, a closed loop sensory feedback Central Pattern Generator (CPG) model is adapted to hierarchical control mechanism in order to provide robust and effective biomimetic control structure. A sensory feedback mechanism plays an important role to react external stimuli from environment. In addition, a closed loop fuzzy logic control structure is developed as a brain model to decide adaptive swimming modes according to sensory information. In order to provide three-dimensional motion abilities, the Centre of Gravity (CoG) control mechanism is designed and controlled by a back-forth proportional control structure. Experimental results are obtained to prove the CPG-based closed loop sensory feedback control structure with the developed robotic fish prototype.

Programming of Job Shop Production Systems with Fuzzy Logic

This article proposes a decision-making algorithm based on the "fuzzy logic" as an optimization technique, which allows to find a good solution to the problem of determining the priority (sequencing) of service or manufacture of jobs in the programming of intermittent production systems, Job Shop. The combinatorial nature and complexity of the problem motivates the exploration of other alternatives solutions to the traditionally used. Initially, the fuzzy logic controller structure (number of input variables, rules and output) is determined in accordance with the objective functions to be optimized. Triangular membership functions are selected for the batch size, the delivery date, the processing time, the number of tools required in each operation, and the priority of the processing the jobs. The fuzzy rules base is defined, and the controller model is formulated (fuzzification, evaluation and defuzzification). The algorithm is developed in Matlab’s ®Simulink ®Fuzzy logic toolbox, achieving better results than those obtained with other methods.

Grid interconnection of renewable energy sources using multifunctional grid-interactive converters: A fuzzy logic based approach

This paper proposes a multi-objective control strategy using adaptive fuzzy PI (AFPI) controller for grid-interactive converter (GIC). The proposed controller utilizes the robust and adaptive nature of fuzzy logic control (FLC) and simple structure of PI controller to effectively improve the dynamic performance of the GIC during uncertainties. In the proposed method, the gains of the PI controller are dynamically adjusted by the fuzzy logic based supervisory control system according to the system operating conditions. Hence, it provides fast dynamic response with reduced overshoot and settling time during disturbances. In addition, the proposed Takagi–Sugeno (TS) fuzzy model is computationally more effective when compared to mamdani type fuzzy models. In the proposed multi-objective control scheme, the GIC is utilized to provide various ancillary services in addition to its primary function of injecting active power to the grid. Computer simulation shows that the dynamic performance of the proposed controller is robust than the conventional PI controller during disturbances. Additionally, the results are compared with the existing literature to validate the performance of the proposed controller.

A Novel and Simple Hybrid Fuzzy/PI Controller for Brushless DC Motor Drives

A novel speed controller for the trapezoidal three--phase Brushless DC (BLDC) Motor Drive is proposed using a hybrid fuzzy logic and proportional plus integral (PI) control. The fuzzy logic control structure is different from conventional fuzzy logic implementations such that it only uses three simple rules based on speed error being either in the positive, negative or zero regions. The controller outputs a reference current, that is enforced through the motor phases by pulsewidth modulation (PWM) control. The proposed fuzzy logic controller can be used individually in applications requiring lower computation load and accepting small steady state offset. For high performance applications requiring offset free tracking, a PI controller is augmented with the fuzzy logic controller and a simple switching scheme is devised based on error variance to switch the active controller based on operating conditions. The response of the drive system under the proposed composite control structure is compared with the conventional PI based and the sliding mode controllers to demonstrate its improved performance. Simulations studies using detailed models in MATLAB/Simulink's Simpowersystems toolbox are carried out to show the validity of proposed control.

Interval type-2 fuzzy PID load frequency controller using Big Bang–Big Crunch optimization

This paper proposes an optimization based design methodology of interval type-2 fuzzy PID (IT2FPID) controllers for the load frequency control (LFC) problem. Hitherto, numerous fuzzy logic control structures are proposed as a solution of LFC. However, almost all of these solutions use type-1 fuzzy sets that have a crisp grade of membership. Power systems are large scale complex systems with many different uncertainties. In order to handle these uncertainties, in this study, type-2 fuzzy sets, which have a grade of membership that is fuzzy, have been used. Interval type-2 fuzzy sets are used in the design of a load frequency controller for a four area interconnected power system, which represents a large power system. The Big Bang–Big Crunch (BB–BC) algorithm is applied to tune the scaling factors and the footprint of uncertainty (FOU) membership functions of interval type-2 fuzzy PID (IT2FPID) controllers to minimize frequency deviations of the system against load disturbances. BB–BC is a global optimization algorithm and has a low computational cost, a high convergence speed, and is therefore very efficient when the number of optimization parameters is high as presented in this study. In order to show the benefits of IT2FPID controllers, a comparison to conventional type-1 fuzzy PID (T1FPID) controllers and conventional PID controllers is given for the four-area interconnected power system. The gains of conventional PID and T1FPID controllers are also optimized using the BB–BC algorithm. Simulation results explicitly show that the performance of the proposed optimum IT2FPID load frequency controller is superior compared to the conventional T1FPID and PID controller in terms of overshoot, settling time and robustness against different load disturbances.

Real-Time Implementation of a Fuzzy Logic Controller for Switch-Mode Power-Stage DC–DC Converters

This paper presents a successful implementation of a fuzzy logic controller structure for switch-mode power-stage dc-dc converters and evaluates experimentally its sensitivity for variable supply voltages and load resistance variations. The optimum topology of the controller structure is determined using experimental tests. An advanced test-bed system is used to evaluate the robustness capacities of the controller under varying loading conditions and input voltage variations. The experiment is performed using a low-cost microcontroller PIC16F877 to verify the design performance over a wide range of operating conditions. The controller shows very interesting tracking features and is able to cope with load changes and input voltage variations. The proposed controller structure is general and can be directly applied to any dc-dc converter topologies. The fuzzy controller structure is compared experimentally with the existing proportional-integral control used in industry. It yields a better dynamic performance without overshoot

A stable self-tuning fuzzy logic control system for industrial temperature regulation

A closed-loop control system incorporating fuzzy logic has been developed for a class of industrial temperature control problems. A unique fuzzy logic controller (FLC) structure with an efficient realization and a small rule base that can be easily implemented in existing industrial controllers was proposed. The potential of FLC in both software simulation and hardware tests in an industrial setting was demonstrated. This includes compensating for thermo mass changes in the system, dealing with unknown and variable delays, operating at very different temperature set points without retuning, etc. It is achieved by implementing, in the FLC, a classical control strategy and an adaptation mechanism to compensate for the dynamic changes in the system. The proposed FLC was applied to two different temperature processes and performance and robustness improvements were observed in both cases. Furthermore, the stability of the FLC is investigated and a safeguard is established.

Fuzzy Logic in Simulation of Lockheed L1011 Aircraft Three-rate Model

ABSTRACT This paper describes a three-rate continuous-time stochastic control system as state-space (SS) type decentralized models of multi-inputlmulti-output (MIMO) stochastic subsystems with optimal linear-quadratic-Gaussian (LQG) regulators and fuzzy logic (FL) control structure. An illustrative example - FL control of three-rate decentralized stochastic model of the Lockheed Ll 0 11 aircraft at cruise flight conditions - was carried out using the proposed three-rate SS decentralization technique. This example demonstrates that the research technique results in simplified low-order MIMO autonomous subsystems with low-order LQG regulators running at different rates and shows the quality of the proposed technique. The simulation results were obtained using the software package Simulink.

A modeling and analysis methodology for modular logic controllers of machining systems using Petri net formalism

Logic controllers for machining systems typically have three control modes: auto, hand and manual. In this paper, a unified formal representation of logic controllers with three control modes is provided using Petri nets (PNs). A modular logic controller structure is introduced and formalized for high-volume transfer lines. The modular logic controller consists of one control module for the mode decision and other control modules for station logic controllers. Each station control module is represented by connecting together operation modules, which are designed with respect to the fault recovery processes of operations; their connection algorithm is also provided. In our formal representation, each control module is represented by a live, safe and reversible PN. A condition for the modular logic controller to generate a correct control logic is provided: the operation causality condition. Using the modular structure of a logic controller, the control logic can be easily reconfigured and automatic code generation is possible.

Wastewater Neutralization Control Based on Fuzzy Logic: Experimental Results

Many industrial wastes contain acidic or alkaline materials that require neutralization of previous discharge into receiving waters or to chemical and biological treatment plants. The control of the wastewater neutralization process is subjected to several difficulties, such as the highly nonlinear titration curve (with special sensitivity around neutrality), the unknown water composition, the variable buffering capacity of the system, and the changes in input loading. To deal with these problems, this study proposes a fixed fuzzy logic controller (FLC) structure coupled with a tuning factor. The versatility and robustness of this controller has been proved when faced with solutions of variable buffering capacity, with acids that cover a wide pK range and with switches between acids throughout the course of a test. Laboratory experiments and simulation runs using the proposed controller were successful in a wide operational range.

Specification, design, and implementation of logic controllers based on colored Petri net models and the standard IEC 1131. I. Specification and design

This work aims at designing and implementing logic control structures that allow a combination of the advantages of classical techniques for the development of programmable logic controller code and elimination of disadvantages such as the lack of formal validation. This paper introduces ordered color Petri nets in combination with some extensions as a modeling tool for logic controllers. The validation of both the model and the specifications of the logic control structures is then pursued through a structural analysis of the net. A special compiler that generates code according to the standard IEC 1131 is discussed. The modeling and implementation of a logic control system of a sector of a flexible assembly cell serves as an example.

Specification, design, and implementation of logic controllers based on colored Petri net models and the standard IEC 1131. II. Design and implementation

This work aims at designing and implementing logic control structures that allow a combination of the advantages of classical techniques for the development of programmable logic controller code and elimination of disadvantages such as the lack of formal validation. This paper introduces a method to automatically generate code for a programmable logic controller from a validated textual description of this kind of Petri nets. A special compiler that generates code according to the standard IEC 1131 is discussed. The modeling and implementation of a logic control system for flexible assembly cell using the method describe serves as an example.

Material flow and control sequence specification of flexible production systems using coloured Petri nets

Starting with the specification of each resource and the whole structure of a flexible production system, in this approach a special kind of coloured Petri nets is used for performing the modelling and the validation of the coordination control structure of the systems. In a second phase, it is proposed to modify the first models to synchronised Petri net schemas to facilitate the supervision and the interaction of the coordination model with the physical components of the system as well as the development and maintainability of the discrete-event control structures. The final result is a formal specification of coloured Petri net based coordination control of resources of the system, and logic control structures for control sequencing based on the use of synchronised subPetri net structures derived from the first one by refining transitions, i.e., their occurrence. Based on the proposed approach, the coordination control model of resources and a first skeleton of the logic control structures of a flexible assembly cell located at the Institute of Manufacturing Automation and Production Systems at the University of Erlangen-Nuremberg, Germany is elaborated and then the correctness of the obtained models with regard to material flow and control sequence specifications is validated by means of the structural analysis of the coloured Petri net-based models.