Design Of Logic Controller Research Articles

Chaos synchronization using fuzzy logic controller

The design of a rule-based controller for a class of master-slave chaos synchronization is presented in this paper. In traditional fuzzy logic control (FLC) design, it takes a long time to obtain the membership functions and rule base by trial-and-error tuning. To cope with this problem, we directly construct the fuzzy rules subject to a common Lyapunov function such that the master–slave chaos systems satisfy stability in the Lyapunov sense. Unlike conventional approaches, the resulting control law has less maximum magnitude of the instantaneous control command and it can reduce the actuator saturation phenomenon in real physic system. Two examples of Duffing–Holmes system and Lorenz system are presented to illustrate the effectiveness of the proposed controller.

The design of a fuzzy logic controller of an ATM switch and its simulation

Available Bit Rate (ABR) streams are carried whenever bandwidth is available to do so. When transporting MPEG streams over ATM networks, the link utilization cannot be brought close to 100% no matter how efficient the connection control admission scheme is, but can be improved by ABR traffic. Due to the unpredictable fluctuations and burstiness of the MPEG streams, it is difficult to accurately control the ABR flow rate. A traffic control mechanism based on fuzzy logic is therefore required to effectively transport ABR traffic so that network operators can use most of the unused bandwidth. In this paper, we present the design of an optimized Fuzzy Logic Controller (FLC) of an ATM switch for the rate control of an ABR stream. Unlike the previous work where synthetic data and trial and error were used for tuning an FLC, the merits of our method are that we used simulations and real MPEG data to generate the input-output data for the optimal design of the FLC, and that our technique enables the output of the FLC to be symmetrical.

Event-Condition-Action Systems for Reconfigurable Logic Control

The contribution of this paper is the introduction of the event-condition-action (ECA) paradigm for the design of logic controllers that are reconfigurable. ECA rules have been used extensively to specify the behavior of active database and expert systems and are recognized as a highly reconfigurable tool to design reactive behavior. This paper develops a method to design logic controllers whose dynamics are governed by ECA rules, with the ultimate goal of producing reconfigurable control. Modularity, integrability, and diagnosability measures that have in the past been used to measure the reconfigurability of manufacturing systems are used to assess the reconfigurability of the developed controllers. For the modularity measure, criteria found in computer science to evaluate the modularity of object-oriented programs are adapted to evaluate the modularity of logic controllers. The results of this paper are that reconfigurability is highly dependent on the level of modularity of the logic control system, and that not all modular structures are reconfigurable. There are approaches, such as the one shown in this paper using ECA rules, that can greatly increase the modularity, integrability, and diagnosability of the logic control system, thus increasing its reconfigurability. Note to Practitioners-This paper has been motivated by the problem of designing reconfigurable logic controllers. Reconfiguration is important in manufacturing, but it has also been an issue in the software design domain. There are software systems that currently exist, such as active data bases or expert systems with very powerful reconfiguration capabilities enabled by event-condition-action (ECA) rules. This paper applies the ECA concept to the design of logic controllers. This paper begins by describing what an ECA logic system is and then focuses on how ECA logic systems can be implemented with control approaches. To this end, two designs are considered. First, finite state machines are used to construct ECA logic systems, and a theoretical framework is built using this approach. Three qualitative measures for reconfigurability (modularity, integrability, and diagnosability) are presented and the controllers are evaluated using these measures. Second, an implementation using the IEC 61499 function block standard is presented as it is a widely understood and accepted standard for control applications. Future work entails theoretical analysis using verification techniques that exploit a controller structure

Design of an advanced incremental fuzzy logic controller for laser surface heat treatments

This work presents an innovative incremental PI fuzzy logic controller developed specifically to laser surface heat treatments, analyzing the specific issues related to the monitoring and control of the process. This real time control system improves considerably the treatment uniformity, reducing the rejection rate and increasing the productivity and final quality of the obtained products. An interesting contribution of this work is the characterization of the developed control strategy in terms of several quantitative criteria not usually analyzed, specially the design time and the experience and knowledge needed to develop and tune the control algorithm, without forgetting the classical validation criteria, such as the rise and settling time, the overshoot, and the steady state error, etc.

ADAPTIVE NEURO-FUZZY CONTROL DESIGN FOR TWO COOPERATING ROBOT MANIPULATORS HANDLING A FLEXIBLE BEAM

This paper presents an adaptive neuro-fuzzy logic control design by using singular perturbation approach for trajectory tracking of two cooperating planar rigid robots handling a flexible beam which does not require any vibration measurement of the beam. First, applying two-time scale control theory on the combined dynamics, a control scheme is elaborated which makes the position and orientation of the mass centre of the beam track a desired trajectory while suppressing the beam vibration. In the proposed controller, fast subsystem controller will damp out the vibration of the flexible beam by an optimal design and the other slow subsystem fuzzy controller dominates the trajectory tracking. The Neural Network is used to learn the rules weights of the fuzzy logic controller. To avoid requiring any beam vibration measurement for the fast control law, a linear time-variant observer is also designed. The simulation results show the Neuro-fuzzy techniques have been more successful than conventional control because they combine the learning capabilities of neural network with the transparent Knowledge representation of fuzzy controller.

DEVELOPMENT OF SIMPLE FUZZY LOGIC CONTROLLER FOR EXTENDED PERIOD-ZCS/ZVS-QUASI RESONANT CONVERTER: DESIGN, SIMULATION, AND EXPERIMENTATION

This paper describes the design and implementation of simple fuzzy logic controller (SFLC) for a nonlinear quasi-resonant converter (QRC). It is shown that the two-dimensional rule table of conventional FLCs (CFLCs) used in power converters can be reduced to one-dimensional rule table using SFLC. The proposed SFLC reduces the memory space and computing time of the fuzzy algorithm. The tuning of scaling factors and the generation of fuzzy rules are also easier when compared with CFLC. As a result, realizing SFLC in a Microcontroller or Digital Signal Processor (DSP) is made simple. The proposed controller structure is universal and it can be directly applied to any of the dc–dc converter topologies. In this paper, the application of SFLC is successfully verified for the voltage control of Extended Period (EP)-ZCS/ZVS-QRC through simulation and experimental studies using TMS320F2407A Processor. The ability of SFLC, compared to CFLC, to achieve good transient response for load variations and supply disturbances is demonstrated.

Simplifying the automatic design of a fuzzy logic controller using evolutionary programming

With the availability of a wide range of Evolutionary Algorithms such as Genetic Algorithms, Evolutionary Programming, Evolutionary Strategies and Differential Evolution, every conceivable aspect of the design of a fuzzy logic controller has been optimized and automated. Although there is no doubt that these automated techniques can produce an optimal fuzzy logic controller, the structure of such a controller is often obscure and in many cases these optimizations are simply not needed. We believe that the automatic design of a fuzzy logic controller can be simplified by using a generic rule base such as the MacVicar-Whelan rule base and using an evolutionary algorithm to optimize only the membership functions of the fuzzy sets. Furthermore, by restricting the overlapping of fuzzy sets, using triangular membership functions and singletons, and reducing the number of parameters to represent the membership functions, the design can be further simplified. This paper describes this method of simplifying the design and some experiments performed to ascertain its validity.

Design of a fuzzy logic approach for optimization reinforced zirconia depositions using plasma sprayings

This paper presents the application of a fuzzy logic controller and Taguchi's design in developing partially stabilized zirconia (PSZ) plasma spraying coatings. In this study, a fuzzy logic controller was used to explore functional relationships between variables, to determine the effect of operating parameter, and to achieve optimal process conditions. In addition, the most relevant input variables are identified through analysis of variance, and implemented in the construction of an appropriate fuzzy logic controller model.The experimental results indicate that the combination of Taguchi's design and a fuzzy logic controller makes a robust, effective, and efficient approach. A confirmation run of the optimal conditions was successfully carried out and shown to achieve desirable results.

Circuit Design Techniques for a First-Generation Cell Broadband Engine Processor

The Cell Broadband Engine (Cell BE) is a multicore system-on-chip (SoC), implemented in a 90-nm high-performance silicon-on-insulator (SOI) technology, and optimized, within the triple constraints of area, power, and performance, to run at frequencies in excess of 3 GHz. The large scale of the design (~75 million logic transistors, and about 750 000 latches and flip-flops), high-volume requirements, and the desire to support multiple manufacturing facilities dictated a need for very robust circuit practices, but at the same time, the high-frequency goal drove the use of more aggressive styles in certain critical regions of the design. This paper describes the local clock design, along with the various latches and flip-flops deployed, followed by a discussion of the circuit techniques used for the digital logic implementation, including special considerations for high-speed synthesized control logic, semi-custom and full-custom static circuit design and full-custom dynamic logic circuits. In addition, the synergistic processor element (SPE) circuit design is described, followed by the techniques and issues associated with the SRAM design. Finally, the methods used for electrical verification are described, these being an important part of the strategy for ensuring overall design robustness and first-silicon success

객체지향 설계 및 시뮬레이션을 이용한 자동 물류 핸들링 시스템의 제어 로직 검증

Recently, many enterprises are installing AMSs(Automated Manufacturing Systems) for their competitive advantages. As the level of automation increases, proper design and validation of control logic is a imperative task for the successful operation of AMSs. However, current discrete event simulation methods mainly focus on the performance evaluation. As a result, they lack the modeling capabilities for the detail logic of automated manufacturing system controller. Proposed in this paper is a method of validation of the controller logic for automated material handling system using an object-oriented design and simulation. Using this method, FA engineers can validate the controller logic easily in earlier stage of system design, so they can reduce the time for correcting the logic errors and enhance the productivity of control program development Generated simulation model can also be used as a communication tool among FA engineers who have different experiences and disciplines

Design and installation of an advanced EIB ™ fuzzy indoor comfort controller using Matlab ™

The aim of this paper is to present the design and installation of a fuzzy logic controller of indoor thermal and visual comfort as well as indoor air quality, using the EIB (European Installation Bus) system through interconnection with Matlab. An experimental chamber is implemented for testing and optimization of the system. The chamber which controls the indoor environment, consists of interconnected nodes (sensors and actuators) in an EIB fieldbus network infrastructure connected with a PC, through RS-232 port. Control is achieved by a fuzzy controller, which is programmed in Matlab. The interconnection between EIB and Matlab is realized via the EIB OPC server and an OPC Client for Matlab. In this way artificial intelligence control, EIB-based platforms and Matlab are interconnected in order to explore the possibilities of using advanced control techniques in energy efficient practices in real buildings.

Heuristic algorithm for an effective state encoding for reconfigurable matrix - based logic controller design

Abstract The paper presents the new effective version of heuristic algorithm for state assignment of concurrent finite state machines. The algorithm is devoted for effective, rapid local state encoding, during an implementation of logic controller programs, specified in Structured Text (ST) - taken from international standard IEC 1131-3. It is considered that textual specification in ST is closely related with an equivalent Sequential function Chart SFC. For the sake of simplicity the slightly restricted sound SFC is treated as a standardised version of control interpreted Petri Net. The obtained state encoding is especially suited and useful for a compact representation of binary control algorithms.

Fuzzy logic controller design methodology for Cartesian robot control

This paper presents an approach for complex task control involving robot-environment interaction. For this purpose, an effective hybrid force/position based-approach for MIMO robot control is proposed. This approach is based on Fuzzy Logic Controller (FLC) design and optimisation methodology operating in two stages: At the first stage, the FLC is trained offline on the basis of data acquired during free motion of the robot, in order to map FLC outputs to real behaviour. A method based on Solis' and Wetts' algorithm is then applied for fuzzy parameter optimisation so that the constraints in terms of interpretability of the predefined rules are respected. Finally, an online learning is implemented into the proposed control structure. The approach has been implemented into an experimental setup, including a 2D Cartesian robot linked to a C5 parallel robot, performing contour following under force constraints. The analysis of the obtained results shows the efficiency of the proposed approach.

Design of a Fuzzy Logic Controller With Evolutionary Q-Learning

Abstract In this paper, an Evolutionary Q-Learning(EQL) algorithm is proposed, which is based on the modified Q-learning and evolutionazy algorithm. The objective of the proposed EQL algorithm is to fmd a fuzzy logic controller (FLC) when only a binary reinforcement signal is available from un unknown target environrnent. The proposed EQL algorithm utilizes and evolves a group of FLCs simultaneously to obtain more feasible solution set. By defining Q-values as functional values of states and FLCs, whole FLCs in the group experience Q-learning process together during the same generation. The Q-learning process assists the proposed EQL algorithm in fmding better FLCs with good quality consequent parts. At the end of each generation, the best FLC is constructed by the unique elite construction algorithm. In usual case where evolutionazy process, which is basically parallel process, is used with reinforcement learning, multiple instances of tazget systems are necessary to make the algorithm applied on-line. O...

Intelligent control of dynamic systems using type-2 fuzzy logic and stability issues

Stability is one of the more important aspects in the traditional knowledge of Automatic Control. Type-2 Fuzzy Logic is an emerging and promising area of application to Intelligent Control (in this case, Fuzzy Control). We present a design methodology based on the Margaliot work [10] for the design of Stable Mamdani Type-2 Fuzzy Logic Controllers.

Design and Implementation of a Fast Digital Fuzzy Logic Controller Using FPGA Technology

Fuzzy logic controllers (FLCs) are finding increasing popularity in real industrial applications, especially when the available system models are inexact or unavailable. This paper proposes a zero-order Takagi---Sugeno parameterized digital FLC, processing only the active rules (rules that give a non-null contribution for a given input data set), at high frequency of operation, without significant increase in hardware complexity. To achieve this goal, an improved method of designing the fuzzy controller model is proposed that significantly reduces the time required to process the active rules and effectively increases the input data processing rate. The digital fuzzy logic controller discussed in this paper achieves an internal core processing speed of at least 200 MHz, featuring two 8-bit inputs and one 12-bit output, with up to seven trapezoidal shape membership functions per input and a rule base of up to 49 rules. The proposed architecture was implemented in a field programmable gate array chip with the use of a very high-speed integrated-circuits hardware description language and advanced synthesis and place and route tools.

06/00078 Design of an intelligents fuzzy logic controller for anuclear research reactor: Adda, F. et al. Progress in Nuclear Energy, 2005, 46, (3–4), 328–347

06/00078 Design of an intelligents fuzzy logic controller for anuclear research reactor: Adda, F. et al. Progress in Nuclear Energy, 2005, 46, (3–4), 328–347

Automatic design of fuzzy logic controller using a genetic algorithm for collision-free, time-optimal navigation of a car-like robot

A fuzzy logic controller (FLC), intended to plan and control the motion of a car-like robot during its navigation among several moving obstacles, is designed automatically using a genetic algorithm (GA). The FLC is expressed by utilizing the structur

Design of fuzzy logic controller for smart base isolation system using genetic algorithm

Several recent works investigate the performance of smart base isolation systems and show that they can reduce base drifts without accompanying increases in acceleration that are seen with conventional passive isolation systems. To date, many viable smart base isolation systems have been proposed. In this study, a novel friction pendulum system (FPS) and an MR damper are employed as the isolator and supplemental damping device, respectively, of the smart base isolation system. A fuzzy logic controller (FLC) is used to modulate the MR damper because the FLC has an inherent robustness and ability to handle non-linearities and uncertainties. A genetic algorithm (GA) is used for optimization of the FLC. The main purpose of employing a GA is to determine appropriate fuzzy control rules as well to adjust parameters of the membership functions. To this end, a GA with a local improvement mechanism is applied. This method is efficient in improving local portions of chromosomes. Neuro-fuzzy models are used to represent dynamic behavior of the MR damper and FPS. The effectiveness of the proposed method for optimal design of the FLC is judged based on computed responses to several historical earthquakes. It has been shown that the proposed method can find optimal fuzzy rules and the GA-optimized FLC outperforms not only a passive control strategy but also a human-designed FLC and a conventional semi-active control algorithm.

Methods of measuring the size and complexity of PLC programs in different logic control design methodologies

Currently there is a wide variety of logic control design methodologies used in industrial logic design. These methodologies include ladder diagrams, function block dia- grams, sequential function charts, and flow charts, but driven by a desire for verifiability, academics are developing additional logic control design methodologies, such as modular finite state machines and Petri nets. Using these, important properties of programs can be verified and some logic can be generated auto- matically from a part plan. The main contribution of this paper is to define methods for measuring programs written in different methodologies, so that the performance of the methodologies can be compared. We demonstrate these methods of measurement using four program samples that perform similar functions on the same ma- chine, written in four logic control design methodologies: ladder diagrams, Petri nets, signal interpreted Petri nets and modular finite state machines.