Design Of Logic Controller Research Articles

Position Control of 3-DOF Underactuated Manipulators with Last Passive Joint Using Fuzzy Logic Control

Underactuated manipulator is one kind of second order nonholonomic dynamics systems. How to control this system is still an open problem. This paper proposes a fuzzy strategy to control three DOF underactuated manipulator with a last passive joint. Four measures are selected to construct the fuzzy logic controller. The four measures are divided into two classes; one class is concerning first link, another class concerning the second link. Four fuzzy logic processors are designed to deal with the measure errors, respectively. The four fuzzy logic processors are also divided into two classes according to the two measure classes. Then, the processed results from the four processors are composed to produce control signs to compensate the errors occurring in the manipulator motion. This method simplifies the design of the fuzzy logic controller. Finally, numerical simulation verifies the fuzzy controller.

LQR-퍼지논리제어기에 의한 2중 차량 구조 역진자 시스템의 제어

임의의 비선형 시스템을 제어하기 위한 새로운 방법의 제어 알고리즘이 널리 보고되고 있으며, 그 유용성을 입증하기 위한 제어 대상 시스템으로 역진자 시스템이 널리 활용되고 있다. 본 논문에서는 스프링으로 연결된 2개의 차량에 장착된 역진자를 제어하는 알고리즘을 제시한다. 여기서 두 개의 차량 중 하나는 구동용, 다른 하나는 역진자를 장착한 무구동용이다. 이를 위한 시스템 모델링을 제시하고, 퍼지논리제어 시스템 기반의 양질의 제어기 설계를 제안한다. 본 논문에서는 퍼지논리제어기의 입력변수로 사용될 6개의 변수를 2개로 축소하기 위하여 LQR(Linar Quadratic Regulator) 기법을 도입하며, 이를 통하여 퍼지논리제어기 설계의 복잡성을 줄일 수 있음을 보인다. 더욱이 개선된 2-입력 퍼지논리제어기의 제어 규칙표가 skew-symmetric의 특성을 가지는 성질로부터 다시 단일입력 퍼지논리제어기 설계를 제안한다. 제안한 방법의 유용성을 입증하기 위하여 시뮬레이션을 수행하며, 이를 통하여 제안한 방법의 우수성을 입증한다. Any new method for controlling a nonlinear system has widely been reported. An inverted pendulum system has typically been used as a target system for demonstrating its usefulness. In this paper, we propose an algorithm to control a flexible joint cart based inverted pendulum system. Two carts are connected with a spring and one is a driving cart and the other is no driving cart with a pole. We here present a system modeling and a good fuzzy logic based control algorithm. We also introduce LQR (Linar Quadratic Regulator) technique for reducing the number of control variables. By using this technique, the number of input variables for a fuzzy logic controller is become only two not six. So the computational complexity is largely reduced. Moreover, a two-input fuzzy logic controller has a control rule table with a skew-symmetric property. And it will lead the design of a single-input fuzzy logic controller. In order to demonstrate the usefulness of the proposed method and prove the superiority of the proposed method, some computer simulations are presented.

Decomposition of the fuzzy inference system for implementation in the FPGA structure

The paper presents the design and implementation of a digital rule-relational fuzzy logic controller. Classical and decomposed logical structures of fuzzy systems are discussed. The second allows a decrease in the hardware cost of the fuzzy system and in the computing time of the final result (fuzzy or crisp), especially when referring to relational systems. The physical architecture consists of IP modules implemented in an FPGA structure. The modules can be inserted into or removed from the project to get a desirable fuzzy logic controller configuration. The fuzzy inference system implemented in FPGA can operate with a much higher performance than software implementations on standard microcontrollers.

Fuzzy Logic Controlled Parallel Connected Synchronous Buck DC-DC Converter for Water Electrolysis

In this paper, a Fuzzy Logic Controlled parallel connected synchronous buck DC-DC converter for water electrolysis system is presented. General design of a fuzzy logic controller, based on Matlab/Simulink is performed. This design can be compared with Proportional Integrated Proportional Derivative controller. The complete control system has been developed, analyzed and validated by simulation study. Performances have then been evaluated in detail for different study conditions. The stability of converter has been analyzed different nonlinear electrolyses loads.

A hybrid optimization method with PSO and GA to automatically design Type-1 and Type-2 fuzzy logic controllers

In this paper we propose the use of a hybrid PSO-GA optimization method for automatic design of fuzzy logic controllers (FLC) to minimize the steady state error of a plant’s response. We test the optimal FLC obtained by the hybrid PSO-GA method using benchmark control plants. The bio-inspired and the evolutionary methods are used to find the parameters of the membership functions of the FLC to obtain the optimal controller. Simulation results are obtained to show the feasibility of the proposed approach. A comparison is also made among the proposed Hybrid PSO-GA, GA and PSO to determine if there is a significant difference in the results.

Transforming hierarchical concepts of GRAFCET into a suitable Petri net formalism

GRAphe Fonctionnel de Commande Etape Transition (GRAFCET) is a powerful graphical means for the specification of controllers in discrete event systems and an international standard since 1988. GRAFCET contributes to a more structural and model driven approach in the design of logic controllers but still lacks an exhaustive formal definition. As a step towards an exhaustive formal model of GRAFCET, some ambiguities of the standard's definitions have to be discussed with regard to means of hierarchical structuring, namely enclosing and forcing. Based on this discussion, the authors propose an extension of a formal model for GRAFCET as a control interpreted Petri net (CIPN).

Fuzzy logic control implementation considerations and complexity analyses

In this paper, a number of implementation and algorithmic options for fuzzy logic control applications are presented. The emphases are on the analyses of the computational load and memory requirements of all the processing stages of fuzzy logic control algorithms. Comparisons are made among commonly used techniques and recommendations are provided. The results could be used to guide the design of fuzzy logic controllers for an embedded or hardware implementation.

고신뢰도 안전등급 제어기기 개발

This paper presents the design of the Safety Programmable Logic Controller (SPLC) used in the Nuclear Power Plants, an analysis of a reliability for the SPLC using a markov model. The architecture of the SPLC is designed to have the multiple modular redundancy composed of the Dual Modular Redundancy(DMR) and the Triple Modular Redundancy(TMR). The operating system of the SPLC is designed to have the non-preemptive state based scheduler and the supervisory task managing the sequential scheduling, timing of tasks, diagnostic and security. The data communication of the SPLC is designed to have the deterministic state based protocol, and is designed to satisfy the effective transmission capacity of 20Mbps. Using Markov model, the reliability of SPLC is analyzed, and assessed. To have the reasonable reliability such as the mean time to failure (MTTF) more than 10,000 hours, the failure rate of each SPLC module should be less than 2 ×10<SUP>-5</SUP> /hour. When the fault coverage factor (FCF) is increased by 0.1 the MTTF is improved by about 4 months, thus to enhance the MTTF effectively, it is needed that the diagnostic ability of each SPLC module should be strengthened. Also as the result of comparison the SPLC and the existing safety grade PLCs, the reliability and MTTF of SPLC is up to 1.6-times and up to 22,000 hours better than the existing PLCs

A new method to minimize the chattering phenomenon in sliding mode control based on intelligent control for induction motor drives

This paper presents new method toward the design of hybrid control with sliding-mode (SMC) plus fuzzy logic control (FLC) for induction motors. As the variations of both control system parameters and operating conditions occur, the conventional control methods may not be satisfied further. Sliding mode control is robust with respect to both induction motor parameter variations and external disturbances. By embedding a fuzzy logic control into the sliding mode control, the chattering (torque-ripple) problem with varying parameters, which are the main disadvantage in sliding-mode control, can be suppressed, Simulation results of the proposed control theme present good dynamic and steady-state performances as compared to the classical SMC from aspects for torque-ripple minimization, the quick dynamic torque response and robustness to disturbance and variation of parameters.

Control of Single Axis Magnetic Levitation System Using Fuzzy Logic Control

This paper presents a fuzzy logic controller design for the stabilization of magnetic levitation system (Maglev 's).Additionally, the investigation on Linear Quadratic Regulator Controller (LQRC) also mentioned here. This paper presents the difference between the performance of fuzzy logic control (FLC) and LQRC for the same linear model of magnetic levitation system .A magnetic levitation is a nonlinear unstable system and the fuzzy logic controller brings the magnetic levitation system to a stable region by keeping a magnetic ball suspended in the air. The modeling of the system is simulated using Matlab Simulink and connected to Hilink platform and the maglev model of Zeltom company. This paper presents a comparison for both LQRC and FLC to control a ball suspended on the air. The performance results of simulation shows that the fuzzy logic controller had better performance than the LQR control.

Partial Reconfiguration in the Field of Logic Controllers Design

The paper presents method for logic controllers multi context implementation by means of partial reconfiguration. The UML state machine diagram specifies the behaviour of the logic controller. Multi context functionality is specified at the specification level as variants of the composite state. Each composite state, both orthogonal or compositional, describes specific functional requirement of the control process. The functional decomposition provided by composite states is required by the dynamic partial reconfiguration flow. The state machines specified by UML state machine diagrams are transformed into hierarchical configurable Petri nets (HCfgPN). HCfgPN are a Petri nets variant with the direct support of the exceptions handling mechanism. The paper presents placesoriented method for HCfgPN description in Verilog language. In the paper proposed methodology was illustrated by means of simple industrial control process.

Support Vector Regression Based 3-D Fuzzy Logic Controller Design for spatially distributed systems

This paper presents a data-driven based 3-D FLC design methodology using support vector regression (SVR) learning. The key technique is to relate spatial fuzzy basis functions of a 3-D FLC to kernel functions of a SVR and construct an equivalence relationship of a 3-D FLC and a SVR. Therefore, a 3-D FLC can be established using the learned results of a SVR. Utilizing the concept of reference function, 3-D membership functions can be generated through location transformation. Thus, we can have more choice for 3-D membership functions. The proposed method was applied to a catalytic packed-bed reactor and simulation results have verified its effectiveness.

A Design Fuzzy Logic Controller for a Permanent Magnet Wind Generator to Enhance the Dynamic Stability of Wind Farms

In this paper, a design fuzzy logic controller for a variable speed permanent magnet wind generator connected to a grid system through a LC-filter is proposed. A new current control method of grid side conversion is developed by integrating the fuzzy controller, in which both active and reactive power, delivered to a power grid system, is controlled effectively. The fuzzy logic controller is designed to adjust the gain parameters of the PI controllers under any operating conditions, so that the dynamic stability is enhanced. A new simple method, based on frequency response of the bode diagram, is proposed in the design of the fuzzy logic controller. To evaluate the controller system capabilities, simulation analyses are performed on a small wind farm model system including an induction wind generator connected to an infinite bus. The simulations have been performed using PSCAD/EMTDC. Simulation results show that the proposed control scheme is more effective for enhancing the stability of wind farms during temporary and permanent network disturbances and randomly fluctuating wind speed, compared with that of a conventional PI controller.

Multi-objective design of fuzzy logic controller in supply chain

Unlike commonly used methods, in this paper, we have introduced a new approach for designing fuzzy controllers. In this approach, we have simultaneously optimized both objective functions of a supply chain over a two-dimensional space. Then, we have obtained a spectrum of optimized points, each of which represents a set of optimal parameters which can be chosen by the manager according to the importance of objective functions. Our used supply chain model is a member of inventory and order-based production control system family, a generalization of the periodic review which is termed ‘Order-Up-To policy.’ An auto rule maker, based on non-dominated sorting genetic algorithm-II, has been applied to the experimental initial fuzzy rules. According to performance measurement, our results indicate the efficiency of the proposed approach.

Synthesized design of a fuzzy logic controller for an underactuated unicycle

In this paper, we propose synthesized design of a fuzzy logic controller (FLC) for control of an underactuated unicycle system. The FLC objective is velocity control of the wheel while keeping the pendulum upright, which is an unstable equilibrium. The synthesized design consists of three phases. First, the FLC structures including the number of rules, membership functions, inference and parametric relations are chosen based on heuristic knowledge about the unicycle. Second, on the basis of a linearized model and linear feedback, the FLC output parameters are determined quantitatively for stabilization of the unicycle. Third, the FLC output parameters are tuned using an iterative learning tuning (ILT) algorithm, which minimizes an objective function that specifies the desired unicycle performance. The rationale for the synthesized FLC design is full utilization of the available information, which is achieved by combining model-based and model-free designs, and hence improves the FLC performance. We minimize the number of FLC rules and fuzzy labels. Six rules are used for regulation or setpoint tasks, whereas 10 rules are used with extra integral control to eliminate steady-state errors induced by system uncertainties and disturbances. Only two fuzzy labels are adopted for each fuzzy variable. The ILT process consists of two phases, exploration for stabilization and exploitation for better performance. The effectiveness of the proposed FLC is validated using intensive simulations and comparisons.

Designing Type-1 and Type-2 Fuzzy Logic Controllers via Fuzzy Lyapunov Synthesis for nonsmooth mechanical systems

In this paper, Fuzzy Lyapunov Synthesis is extended to the design of Type-1 and Type-2 Fuzzy Logic Controllers for nonsmooth mechanical systems. The output regulation problem for a servomechanism with nonlinear backlash is proposed as a case of study. The problem at hand is to design a feedback controller so as to obtain the closed-loop system in which all trajectories are bounded and the load of the driver is regulated to a desired position while also attenuating the influence of external disturbances. The servomotor position is the only measurement available for feedback; the proposed extension is far from trivial because of the nonminimum phase properties of the system. Performance issues of the Type-1 and Type-2 Fuzzy Logic Regulators that were designed are illustrated in experimental studies.

Petri Net Based Specification in the Design of Logic Controllers with Exception Handling Mechanism

Petri Net Based Specification in the Design of Logic Controllers with Exception Handling Mechanism Hierarchical Petri nets beside UML state machine diagrams, sequentional function charts (SFC) and hierarchical concurrent state machines are common solution for specification of logic controllers. These specification formats provide both concurrency and modeling on multi levels of abstraction (hierarchic approach). But only state machine diagrams supports exceptions handling in direct way. Program model presented in form of state machine diagram may be later transformed into a program in the SFC language or transformed in the Petri Net and implemented in the FPGA structure. Similarity between SFC language and Petri Nets give us lot of tools for analysis such control system. Article presents new approach for exceptions handling in hierarchical Petri nets as formal specification for logic controllers. Proposed method of specification can be used independently or as a part of dual specification (correlated state machine diagram and hierarchical configurable Petri Net).

Design and implementation of a hybrid fuzzy logic controller for a quadrotor VTOL vehicle

Helicopters have generated considerable interest in both the control community due to their complex dynamics, and in military community because of their advantages over regular aerial vehicles. In this paper, we present the modeling and control of a four rotor vertical take-off and landing (VTOL) unmanned air vehicle known as quadrotor aircraft. This model has been generated using Newton-Euler equations. In order to control the helicopter, classical PD (proportional derivative) and Hybrid Fuzzy PD controllers have been designed. Although fuzzy control of various dynamical systems has been presented in literature, application of this technology to quadrotor helicopter control is quite new. A quadrotor helicopter has nonlinear characteristics where classical control methods are not adequate especially when there are time delays, disturbances and nonlinear vehicle dynamics. On the other hand, Fuzzy control is nonlinear and it is thus suitable for nonlinear system control. Matlab Simulink has been used to test, analyze and compare the performance of the controllers in simulations. For the evaluation of the autonomous flight controllers, some experiments were also performed. For this purpose, an experimental test stand has been designed and manufactured. This study showed that although, both of the classical PD and the Fuzzy PD controllers can control the system properly, the Fuzzy PD controllers performed slightly better than the classical PD controllers, and have benefits such as better disturbance rejection, ease of building the controllers.

Pitch Control of an Aircraft Using Artificial Intelligence

This paper presents the investigation into the design, simulation and analysis of two autopilots: a fuzzy Proportional-Integral-Derivative (PID) controller and, its hybrid with a PID controller for the control of pitch plane dynamics of an aircraft. The Mamdani-type fuzzy inference system is employed for the Fuzzy Inference System (FIS) in the fuzzy logic controller design. The dynamic modeling of system begins with a derivation of suitable mathematical model to describe the longitudinal motion of an aircraft. This research set the platform for thorough investigation into the various structures available for PID-FLC and its hybrids. Considering hardware implementation challenges and limitations, not all PID-FLC and its hybrid structures are viable. The PID-FLC is constructed as a parallel structure of a PD-FLC and a PI-FLC, with the output signal of the control loop, y serving as the input for the derivative parameter of the PD-FLC. The output of the PID-FLC is formed by algebraically adding the outputs of the two fuzzy control blocks as suggested in Guanrong et al., 2000. Also, the proposed hybrid fuzzy PID autopilot consists of the PID-FLC with a traditional PID controller structured by algebraically adding the outputs of the two control blocks. Result of simulation in MATLAB ® /Simulink ® shows that the proposed PID-FLC autopilot gave an unacceptable

Design and Implementation of an Effective Fuzzy Logic Controller based on Quantum Inspired Evolutionary Algorithm

This paper proposes a new approach based on quantum inspired evolutionary algorithm (QIEA) for effective selection and definition of fuzzy if-then control rules as well as the shapes of membership functions (MFs) to design fuzzy logic controllers (FLCs). The majority of works done on designing FLCs rely on the knowledge base derived from imprecise heuristic knowledge of experienced operators or persons. These traditional methods, however, are cumbersome to implement and very time consuming to evaluate. Our proposed approach is a self-learning adaptive method and decomposes a problem in such a way that leads to more effective knowledge acquisition and improved control performance with the FLCs. In order to verify the effectiveness of this self-learning adaptive method, a standard test-bed, the truck backer-upper problem, is considered as the test problem. During each generation, the rules are updated and the MFs’ parameters are altered using a complementary double mutation operator (CDMO) and a discrete crossover (DC). This paper also demonstrates the effect of different fuzzification and defuzzification methods on the response of the FLC. The center of gravity (COG) and modified COG are used as defuzzifier to analyze the results of the fuzzy controller. The experimental results show that the proposed approach with different fuzzification and MCOG to design FLCs performs better than the traditional methods with triangular fuzzification and COG in terms of required time to backing up the truck.