Design Of Logic Controller Research Articles

Single-chip fuzzy logic controller design and an application on a permanent magnet dc motor

This paper describes a low-cost single-chip PI-type fuzzy logic controller design and an application on a permanent magnet dc motor drive. The presented controller application calculates the duty cycle of the PWM chopper drive and can be used to dc–dc converters as well. The self-tuning capability makes the controller robust and all the tasks are carried out by a single chip reducing the cost of the system and so program code optimization is achieved. A simple, but effective algorithm is developed to calculate numerical values instead of linguistic rules. In this way, external memory usage is eliminated. The contribution of this paper is to present the feasibility of a high-performance non-linear fuzzy logic controller which can be implemented by using a general purpose microcontroller without modified fuzzy methods. The developed fuzzy logic controller was simulated in MATLAB/SIMULINK. The theoretical and experimental results indicate that the implemented fuzzy logic controller has a high performance for real-time control over a wide range of operating conditions.

Design of Mamdani fuzzy logic controllers with rule base minimisation using genetic algorithm

This paper presents a design procedure for Mamdani fuzzy logic controller including rule base minimisation. The rules are modelled with binary weights on which constraints are imposed in order to ensure consistency. A genetic algorithm is used for finding stabilising controllers that minimise the number of rules. The cost function includes a stability/performance coefficient which insures that stable, performance satisfying controllers are given the highest possible fitness. The number of fuzzy sets for the input and the control variables are set by the user and the design procedure is concerned only with the rule base and the distribution of the fuzzy sets in the universes of discourses. Two examples were studied: the control of the pole and cart system and the control of the concentration in CSTR. In both cases, the fuzzy sets were isosceles triangles evenly distributed, in the universe of discourses.

Implementation Issues of a Fuzzy-Logic-Based Three-Phase Active Rectifier Employing Only Voltage Sensors

Switch-mode rectifiers are becoming more and more interesting in those applications where bidirectional power flow, power-factor correction, and electromagnetic interference reduction are required. Typical active rectifiers include current or voltage sensors, however, in order to obtain low-cost systems, their number should be reduced. In this paper, a current-sensorless active rectifier with feedforward fuzzy logic control is presented and discussed. The mathematical description of the system and the design of the fuzzy logic controller are introduced and analyzed; moreover the implementation on a SH7047 microcontroller is presented with emphasis on the most significant implementation issues. Experimental results are reported and discussed.

A Fuzzy Logic Controller Design and Simulation for a Sawmill Bucking System

This paper presents an alternative efficient solution to the sawmill bucking problem using a fuzzy logic controller/optimizer. Bucking is one of the first production stations where stems coming from the forests are analyzed and processed in a sawmill. A length and diameter measurement system provides an operator with stem information so he/she can make a decision on what blocks should be cut. Traditional bucking solutions are based on the operator's experience, the data provided by the length and diameter measurement system and the visual inspection on the shape (sweep and taper) of the stem. The decisions of the operator are not exact but good enough or appropriate. The operator's decisions have a common goal: to recover the most wood out of every tree stem. Fuzzy logic controller decisions, if appropriate, try to simulate the best common sense decisions that a human will make after evaluating a set of data. Fuzzy logic control systems, as is already known, are designed with the intention of replacing an expert human operator with an automated ruled-based system.

Closed-Loop Matrix Based Model of Discrete Event Systems for Machine Logic Control Design

This paper deals with modeling, dynamic description, and control of discrete event systems (DES) for production systems and machines control logic design. The control logic of such systems is considered as DES, which is then modeled by a matrix representation of Petri net graph. The dynamics of a DES is described by a well known algebraic Petri net next-state equation and a novel logical firing event selecting equation. The control of the DES dynamics is introduced by logical signals, which represent conditions for occurrence of events. Such a presentation enables closed-loop modeling of DES, which is important for simulation of the systems and analysis of their performance before the target system is actually built. The proposed method is illustrated with a cutting machine application. Using the proposed method, the correct functionality as well as faults response can be simulated with Matlab/Simulink.

Robust nonlinear flight control of a high-performance aircraft

This paper considers probabilistic robust control of nonlinear uncertain systems. A combination of stochastic robustness and dynamic inversion is proposed for general systems that have a feedback-linearizable nominal system. In this paper, the stochastic robust nonlinear control approach is applied to a highly nonlinear complex aircraft model, the high-incidence research model (HIRM). The model addresses a high-angle-of-attack enhanced manual control problem. The aim of the flight control system is to give good handling qualities across the specified flight envelope without the use of gain scheduling and also to provide robustness to modeling uncertainties. The proposed stochastic robust nonlinear control explores the direct design of nonlinear flight control logic. Therefore, the final design accounts for all significant nonlinearities in the aircraft's high-fidelity simulation model. The controller parameters are designed to minimize the probability of violating design specifications, which provides the design with good robustness in stability and performance subject to modeling uncertainties. The present design compares favorably with earlier controllers that were generated for a benchmark design competition.

Design of an intelligent fuzzy logic controller for a nuclear research reactor

The main objective of this paper is to design an intelligent controller system based on the concepts of fuzzy logic. This latter will be used to control the power of a nuclear reactor. The principle of this controller is based on rules established from experiments used with a classical controller and from the knowledge and the expertise of the operators of the reactor. This intelligent controller could be used in parallel with the actual system, which is semiautomatic, as a decision aided system to assist the operators in the control room.

An Approach to Fuxxy Control for a Class of Nonolinear Systems: Stability and Design Issues

AbstractIn order to ensure the stability of a fuzzy control system for a class of nonlinear systems, a stability criterion is derived from Lyapunov’s direct method. In this article, instead of linearizing the nonlinear system around several operating points and using a T-S fuzzy model to represent the plant, the authors use the technique of feedback linearization as a part of the control action on the consequent (conclusion) parts of the fuzzy rules. So, linear system in a new coordinate will be generated associated with each fuzzy subsystem, and if these linear systems are stable under common Lyapunov function, then the corresponding nonlinear system is stable. Based on the stability criterion, a fuzzy logic controller design method will be proposed. The proposed design acts as multivariables state feedback in order to stabilize the nonlinear system in systematic manner. Finally, a numerical example is given to illustrate the concept of the proposed controller with comparison with state feedback controller.

MATLAB-based GUIs for fuzzy logic controller design and applications to PMDC motor and AVR control

An attractive and instructive approach for teaching basis of fuzzy logic-based controller design steps and effects of properties of the controller to control system by using MATLAB environment is presented in this paper. All design stages are developed in MATLAB's graphical user interface (GUI). Source codes used for both controller and to define systems to be controlled are written in separated script files using MATLAB language. Maximum and minimum values of the parameters that belong to membership functions (MFs) and rule base table are determined by using step responses and error graphics of the systems. Two different examples are given to demonstrate the usefulness of the developed tool and to visualize effect of changes of fuzzy logic-based controller parameters. © 2005 Wiley Periodicals, Inc. Comput Appl Eng Educ 13: 10–25, 2005; Published online in Wiley InterScience (www.interscience.wiley.com); DOI 10.1002/cae.20026

An Approach to Fuzzy Control for a Class of Nonlinear Systems: Stability and Design Issues

In order to ensure the stability of a fuzzy control system for a class of nonlinear systems, a stability criterion is derived from Lyapunov’s direct method. In this article, instead of linearizing the nonlinear system around several operating points and using a T-S fuzzy model to represent the plant, the authors use the technique of feedback linearization as a part of the control action on the consequent (conclusion) parts of the fuzzy rules. So, linear system in a new coordinate will be generated associated with each fuzzy subsystem, and if these linear systems are stable under common Lyapunov function, then the corresponding nonlinear system is stable. Based on the stability criterion, a fuzzy logic controller design method will be proposed. The proposed design acts as multivariables state feedback in order to stabilize the nonlinear system in systematic manner. Finally, a numerical example is given to illustrate the concept of the proposed controller with comparison with state feedback controller.

Assessment of on-chip wire-length distribution models

Ultralarge-scale integrated (ULSI) chip design data is needed for an assessment of existing on-chip wirelength distribution models. Data extracted from modern chips such as high-performance microprocessors provide information about actual wire length requirements in ULSI chip designs. These requirements are compared with wirelength estimates obtained by evaluating existing models as functions of Rent's parameters that are extracted from the designs. This brief assesses the extent to which existing models estimate wirelength requirements in 100 ASIC-like control logic designs in the 1.3-GHz POWER4 microprocessor. For each design, physical design characteristics and wirelength requirements are measured and compared with model estimates. Lack of agreement between the data and models is observed for most designs, and possible reasons for the lack of agreement are discussed.

04/02562 The control of indoor thermal comfort conditions: introducing a fuzzy adaptive controller: Calvino, F. et al. Energy and Buildings, 2004, 36, (2), 97–102

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.

Verification of a cruise control system using counterexample-guided search

Formal verification has been identified by the research community as a useful step in logic controller design since it reveals algorithmically whether the controller in conjunction with the controlled plant satisfies given design specifications. If it is necessary, however, to model the continuous/hybrid behavior of the plant, the verification is a computationally expensive task. This paper shows for the example of a cruise control system that the recently proposed approach of counterexample-guided verification can reduce the computational costs considerably. The method generates a sequence of abstractions, for which those behaviors (the counterexamples) are identified that potentially violate the specifications. The paper presents a tailor-made sequence of validation methods that aim at checking the existence of these behaviors for the hybrid model of the controlled plant with as small computational costs as possible.

A Web-based programmable logic controller laboratory for manufacturing engineering education

This study presents the design and development of a Web-based programmable logic controller (PLC) system architecture that supports “hands-on” laboratory exercises in automated manufacturing systems control area for distance education. The system architecture allows remote users to access and control a PLC-based table-top manufacturing system via the Internet. A Web site has been designed and developed that facilitates interactivity and supports PLC programming and control. The architecture has been tested and implemented in the course Emgt 334 Computer Integrated Manufacturing Systems at the Integrated Systems Facility (ISF) in the Engineering Management Department at the University of Missouri-Rolla during Fall 2001. This study shows that software tools available in the market can be integrated to develop a fairly complex, yet effective, learning environment for distance education. The architecture presented in this paper is not dependent on specific PLC hardware or software configuration, it represents a generic infrastructure.

Automatic design of fuzzy logic controller using a genetic algorithm—to predict power requirement and surface finish in grinding

We have developed a method for automatic design of fuzzy logic controller (FLC) using a genetic algorithm (GA). The performance of an FLC depends on its knowledge base (KB), which consists of membership function distributions (also known as data base) and rule base. To design a proper KB of the FLC, the designer should have a thorough knowledge of the process to be controlled. Sometimes, it becomes difficult to gather knowledge of the process beforehand. Thus, designing the proper KB of an FLC is not an easy task. In this paper, a new approach for designing the KB of an FLC (using a GA) is proposed and its effectiveness is compared to a previous approach based on GA-fuzzy combination for making predictions of power requirement and surface finish in grinding (a machining process to obtain smooth surface on the work).

KOMPSAT-1 Telemetry를 활용한 반작용휠 모델링

위성의 성공적인 임무 수행을 위한 자세 안정화와 성능요구조건을 만족하기 위해서 반작용휠 제어로직의 설계가 중요하다. 실제 위성궤도 상에서 발생하는 여러 가지 불확실성으로 인해 지상실험을 통해 획득한 모델 파라미터 값들만으로 제어로직을 설계하는데 한계가 있다. 그러므로 위성이 궤도상에 있을 때의 반작용휠 입력 및 출력 데이터를 이용하여 모델 파라미터를 보정하고 자세제어기에 반영하는 것이 요구된다. 본 논문에서는 다목적실용위성의 Telemetry 데이터를 활용한 시스템인식 (System Identification)을 수행하였고, 이를 통한 반작용휠의 모델 파라미터를 추출한다. 또한, 반작용휠을 모델링 하고 또한 제어기설계에 사용된 모델 파라미터를 추출하여 지상실험 데이터와 비교분석한다. The design of reaction wheel control logic is critical to achieve the spacecraft attitude stabilization and performance requirements for the successful mission. Due to various uncertainties on orbit there exist limitation to obtain the model parameters through the ground tests and to design the associated control logic. Thus, the model parameter correction using on-orbit data is essential to the control performance on orbit. This paper performs the system identification using KOMPSAT-1 telemetry data and extracts the model parameters of the reaction wheel. Moreover, the reaction wheel is remodeled and compared with the ground test results.

Fuzzy Logic Control of the End-Point Vibration in an Experimental Flexible Beam

This paper is concerned with the design and implementation of a fuzzy logic controller (FLC) to control the end-point vibration in a single flexible beam mounted on a two-degrees-of-freedom platform. The angular position of the hub and the signal from a strain gage mounted on the beam are used as the two inputs to the FLC. In order to add more damping, the strain gage signal is combined with the hub angular velocity represented by the output of a tachometer attached to the motor shaft. We discuss how to build the rule base for the flexible beam based on the relation between the angular displacement of the hub and the end-point deflection, as well as the effect of different scaling gains on the performance of the FLC. We present several experimental results showing the effectiveness of the FLC in reducing the end-point vibration of the flexible beam.

Design of robust fuzzy-logic control systems by multi-objective evolutionary methods with hardware in the loop

Evolutionary development of a fuzzy-logic controller is described and is evaluated in the context of hardware in the loop. It had been found previously that a robust speed controller could be designed for a DC motor motion control platform via off-line fuzzy logic controller design. However to achieve the desired performance, the controller required manual tuning on-line. This paper investigates the automatic design of a fuzzy logic controller directly onto hardware. An optimiser which modifies the fuzzy membership functions, rule base and defuzzification algorithms is considered. A multi-objective evolutionary algorithm is applied to the task of controller development, while an objective function ranks the system response to find the Pareto-optimal set of controllers. Disturbances are introduced during each evaluation at run-time in order to produce robust performance. The performance of the controller is compared experimentally with the fuzzy logic controller which has been designed off-line, and a standard PID controller which has been tuned online. The on-line optimised fuzzy controller is shown to be robust, possessing excellent steady-state and dynamic characteristics, demonstrating the performance possibilities of this type of approach to controller design.

Fuzzy Logic Control of the End-Point Vibration in an Experimental Flexible Beam

This paper is concerned with the design and implementation of a fuzzy logic controller (FLC) to control the end-point vibration in a single flexible beam mounted on a two-degrees-of-freedom platform. The angular position of the hub and the signal from a strain gage mounted on the beam are used as the two inputs to the FLC. In order to add more damping, the strain gage signal is combined with the hub angular velocity represented by the output of a tachometer attached to the motor shaft. We discuss how to build the rule base for the flexible beam based on the relation between the angular displacement of the hub and the end-point deflection, as well as the effect of different scaling gains on the performance of the FLC. We present several experimental results showing the effectiveness of the FLC in reducing the end-point vibration of the flexible beam.

Design of a multi‐layer fuzzy logic controller using pole assignment for bipedal walking at varying speeds

When a biped robot detects obstacles along its path, it will reduce its walking speed to change direction for obstacle avoidance. It is essential for a biped robot to be able to vary its speed during walking. To control biped robots with variable walking speed capability, a Multi‐Layer Fuzzy Logic Controller (MLFLC) is developed using the pole assignment technique in this paper. This method extends the previous result, that a switching surface, whose parameters are scaling factors, exists in a Multi‐Layer Fuzzy Logic Controller (Tu et al., 2000). In this study, the poles of a closed‐loop control system are derived relative to the switching surface parameters, i.e. the normalized scaling factors. Therefore, after choosing the appropriate poles, scaling factors are determined and then a Multi‐Layer Fuzzy Logic Controller is designed. This design has two important features: (1) simplifying Fuzzy Logic Controller (FLC) design to select only the scaling factors; (2) pursuing the system performance requirement, based on the pole assignment. A three‐link biped robot is used as the illustrative example. Simulation results are included.