Design Of Logic Controller Research Articles

Automating the Design of Asynchronous Logic Control for AMS Electronics

Analog and mixed signal (AMS) electronics becomes increasingly complex and needs to be digitally enhanced by its own control circuitry. The RTL synthesis flow routinely used for digital logic is, however, optimized for synchronous data processing and produces inefficient control for AMS. In this paper, we demonstrate the evident benefits of asynchronous circuits in the context of AMS systems, and propose an asynchronous design for analog electronics (A4A) flow for their specification, synthesis, and formal verification. A library of specialized analog-to-asynchronous (A2A) components is developed for interfacing analog and asynchronous worlds. A4A flow is automated in the Workcraft framework and evaluated using a multiphase buck converter case study, where A2A components are employed to sanitize analog sensor readings. Timing analysis of asynchronous buck control shows improved response time: 4× reaction to high-load and 7× to under-voltage condition, compared with a 333 MHz clocked controller (to achieve a similar response time, a clocked controller would require ~3 GHz frequency). The simulation results of a 4-phase asynchronous buck demonstrate improved voltage ripple and peak current -16% and 12% reduction, respectively. These benefits lead to the higher efficiency of power conversion, and can be traded off for the cost of analog components, e.g., coils. Moreover, the use of the proposed design flow and tools helps to improve design productivity and overall robustness of AMS circuits.

Design and Performance Analysis of AC Drive Using Hybrid Controller

This paper presents the vector control induction motor drive using fuzzy logic controller, PID and hybrid controller for improving the performance of motor speed and load torque. Design of hybrid fuzzy logic controller for vector control three-phase induction motor drive is implemented with MATLAB/Simulink environment in the terms of rise-time, over-shoot, under-shoot and settling time. Simulation results show that hybrid controller produces better performance in terms of rise-time, over-shoot, under-shoot and settling time as compared PID controller.

Optimization control for the looper’s height on continuous pickling titanium plates and strips by microwave heating

Optimal control for design of fuzzy logic controller for by tuning traditional PID parameters-based control strategy was proposed to control the looper’s height on continuous pickling titanium plates and strips with an instability and random noise process. The parameters relations between fuzzy controller and PID controller are deeply analyzed. Then the whole output of the fuzzy controller which consists of two sub-controllers, the PI controller and the PD controller is designed using parameters of PID controller tuned by Ziegler-Nichols method. The fuzzy controller is compared with traditional PID by simulation and real engineering application. The results indicate that the dynamic control performances of the looper’s height are much better by using fuzzy control strategy. The fuzzy controller is not only the designed simplify, but also the strong effectiveness and feasibility.

Optimized Fuzzy Logic Controller for Responsive Charging of Electric Vehicles

Abstract This paper contributes to the theme of intelligent integration of energy storage and the control of prosumer resources. The paper illustrates the use of a zero-order Sugeno fuzzy model to perform bidirectional real power control from an electric vehicle (EV), i.e., vehicle to grid (V2G) and grid to vehicle (G2V). The paper proposes an initial design of the fuzzy logic controller (FLC) following which the FLC is optimized using genetic algorithm (GA) for better performance under varying charging speed requirements of the user and better efficiency. A perturb and observe (P&O) algorithm based reactive power control is also proposed for voltage support through these EV chargers. The designed FLC can not only respond to grid conditions based on the time of use (TOU) but also to users charging speed requirements. Also, the initial design of an FLC may not suit a particular user’s requirement but can be optimized to meet the requirements.

Advisory Temporal Logic Inference and Controller Design for Semiautonomous Robots

In this paper, we present a method to learn (infer) and refine a set of advices from the trajectories generated in the successful and failed attempts in a task or game, in the form of advisory signal temporal logic (STL) formulas. Each advice consists of an advisory motion STL formula that characterizes the spatial–temporal pattern of the motion as a feature of success and an advisory selection STL formula as a criterion for the environment to select the advice. For the inference of advisory STL formulas, we provide a theoretical framework of perfect classification with a labeled set of trajectories with different time lengths. We design an advisory controller that can drive the robots to satisfy an advisory motion STL formula based on the advice selected according to the advisory selection STL formula. The advisory controller can advise or guide the human operators or the robots for better performance with the shared autonomy between the human operator and the controller. We provide two case studies to test the effectiveness of the advisory controller, one with a Baxter-On-Wheels simulator and the other with two quadrotors in an experimental testbed in iteratively improving the success rates of completing the tasks with the help of the designed advisory controller. Note to Practitioners —The method described in this paper can be used to obtain knowledge or patterns of the environment based on the trajectories generated by the human operators/demonstrators and utilize the obtained knowledge or patterns for improving the performance of the future operators. The obtained information is the logical statements about the waypoints or subgoals to be reached, and obstacles or dangerous regions to be avoided during certain time intervals, when the environment satisfies certain conditions also expressed in the form of logical statements. The methodology of inferring knowledge from data and designing advisory controllers for guiding or helping future practices is potentially useful in many applications where the dynamic mathematical model of the external environment is unknown.

Hardware-in-the-loop simulation and implementation of a fuzzy logic controller with FPGA: case study of a magnetic levitation system

This paper presents the design and implementation of a fuzzy logic controller using Very High Speed Integrated Circuit Hardware Description Language (VHDL) on a field programmable gate array (FPGA). First, a Sugeno-type fuzzy logic controller with five triangular and trapezoidal membership functions for two inputs and with nine singleton membership functions for one output is examined. The proposed structure is tested with second- and third-order system model using FPGA-in-the-loop simulation via a MATLAB/Simulink environment. Then, for different kinds of fuzzy logic controllers, a new look-up table (LUT) and interpolation-based controller implementation is proposed to eliminate the computational complexity of the primarily designed structure. As a case study, a magnetic levitation system is controlled with an adaptive neuro-fuzzy inference system (ANFIS) trained fuzzy logic controller, then it is simulated and implemented using a LUT-based controller. Finally, we provide a comparison of results.

RETRACTED ARTICLE: FPGA logic design method based on multi resolution image real time acquisition system

Medical imaging techniques are mostly generated by human tissue echoes and received by the transducer which is converted to electrical signals, after amplification, extraction, processing, and then signals are converted by the digital scan converter for standard video signal, finally displayed by the display. We propose a scheme of real-time and multi resolution image acquisition system by FPGA control logic design based on the real-time data acquisition, beam forming, processing, acquisition and transmission to ARM embedded video signal processing system with high real-time requirements, so we choose FPGA and SRAM real-time acquisition system which can meet the above requirements in speed and capacity. According to the problems encountered in the process of high speed acquisition, a reasonable timing optimization and RTL level synthesis is designed. The experimental results show that the design and implementation of the image acquisition system is not only stable, but also significantly improve the overall performance of the image processing system.

Design of a supervisory fuzzy logic controller for monitoring the inflow and purging of gas through lift bags for a safe and viable salvaging operation

This paper presents a mathematical model and numerical time-domain approach to simulate the dynamics of a sunken ship/vessel being raised from seafloor by buoyancy (gas-inflating) systems in a form which is suitable for integrating control techniques to ensure hydrodynamic stability for a safe and viable salvaging operation. According to the two-degree-of-freedom equations of rigid-body vessel motion in diving plane, a conventional sliding mode controller is designed as the primary controller to regulate flow rate of filling gas inside the lift bags and a PID controller is designed as the secondary controller for regulating the purging of gas through the valves fitted on lift bags. Then a supervisory fuzzy logic controller is designed to monitor or switch between the primary and secondary controllers based on the buoyancy requirement. From the simulation studies, it is found that the supervisory fuzzy logic controller is capable to maintain hydrodynamic stability by suitably defining the linguistic fuzzy rules, which is created based on the author's experience in conducting numerical simulation using primary and secondary controllers.

Fuzzy Logic Control Design in Hybrid Energy Storage System Super-Capacitor Battery for Electric Vehicle

HESS is a suitable technology when applied to electric cars. One application is in SUV (Sport Utility Vehicle) car. The use of Supercapacitors can reduce the excess of load on the battery. Uneven soil contours cause current spike and drop in battery voltage which can reduce battery lifetime. This journal presents a simulated study of HESS batteries and Supercapacitors in SUV cars. Fuzzy-based energy management strategies and threshold control are introduced. The simulation study shows the difference between the control using the number of climb data and not, and the Fuzzy control response to the demand load. The simulation results mention the reduction of the maximum current and the battery voltage drop according to the load. The total energy ratio used between the two controls is also presented.

Improvement of Energy Efficiency Using a Multi-Input Fuzzy Logic Controller in a Stone Cutting Machine

Abstract Block cutter machines (BCMs) are commonly used in the manufacturing of natural stones. Although the energy consumption of the BCM is affected by the rotation speed of the blade, depth of cut, and traverse speed, these parameters are generally fixed. Unfortunately, stones are not homogeneous materials, and this has a negative impact on the energy consumption of the BCM because of the fixed parameters. The main goal of our study was the development of a multi input single output (MISO) fuzzy logic controller (FLC) design to improve the energy efficiency of the BCM. In this study, two MISO FLCs (two- and three-input) were designed to adjust the traverse speed and these controllers were applied in the laboratory-scale model of the BCM. The designed FLCs are tested with cutting experiments on three different stones. The experiments showed that, with the continuous adjustment of the traverse speed during the cutting process, the FLCs increase energy efficiency. The three-input FLC provided more energy saving than with the two-input FLC. Also, multiple regression analysis was performed in order to determine the combined effects of the most dominant rock properties on specific energy for three different control methods.

Special Issue on the Power of Fuzzy—Dedicated to the Father of Fuzzy Logic

On September 6, 2017, we lost a great researcher, Prof. Lotfi A. Zadeh, the one who introduced one of the most important mathematical concepts that gets a good rapport with reality. “Fuzzy Sets” was the paper he published in 1965. Many researchers and practitioners of mathematics, science, engineering, medicine, and economics found it fascinating. In Japan, consumer electronics incorporating ambiguity in human thought and behavior became popular. As these products became big topics, the term “fuzzy” also became popular in the 1990s. This set of papers offers a sample of the expanding development of fuzzy logic and soft computing. One review paper is written by Prof. Takeshi Yamakawa, an internationally famous fuzzy researcher of fuzzy hardware systems. Four of these papers were selected through a peer review process. One, “Design of Fuzzy Logic Controller and its Distinctive Features” by Prof. Takeshi Yamakawa, describes the design of a fuzzy logic controller and its application to controlling mouse-platform stabilization. The distinctive features of fuzzy logic control are also discussed. The first original paper, “MMMs-Induced Possibilistic Fuzzy Co-Clustering and its Characteristics” by Ubukata et al., describes an NPCCMM scheme by considering variable cluster volumes and the fuzziness degree of item memberships to investigate the specific aspects of fuzzy rather than probabilistic nature in co-clustering tasks. The second original paper, “Inner Evaluation of Writing in a Foreign Language Based on Expert Judgment for Correction” by Entani et al., proposes a method of numerically deriving each writer’s writing preference from an expert’s initial evaluation. Third, “A 3-Dimensional Fuzzy Linguistic Evaluation Model” by Suprasongsin et al., describes a new model for determining criteria weights in group decision-making problems, a model based on the concept of probabilistic linguistic terms. The fourth original paper, “Natural Language Generation Using Monte Carlo Tree Search” by Kumagai et al., proposes a method for generating simulation-based natural language. The method accounts for both building a correct syntactic structure and reflecting the given situational information as input in the sentences generated. We appreciate Prof. Takeshi Yamakawa for the excellent review of fuzzy controllers. We also thank all of the authors who submitted original articles and all of the reviewers who offered their valuable comments and suggestions.

Design of Fuzzy Logic Controller and its Distinctive Feature

Prof. Lotfi A. Zadeh, who created a new approach to describe a knowledge of a human expert with a natural language, passed away on September 6, 2017. His significant accomplishment was to create a novel artificial intelligence (AI) which exhibits the knowledge of human experts in natural linguistic terms. This system is structured and clear in two points of why a result is obtained and how it is done. The system contrasts with AI systems based on neural networks or deep learning. In this paper, the design of a fuzzy logic controller and its application to controlling of the mouse-platform stabilization are described. In addition, the distinctive features of fuzzy logic control are discussed. The author wants to offer this paper on the altar of Prof. Zadeh.

Design Verification for Control Logic in Nuclear Power Plant

The control function for process, heating, ventilation, and air conditioning, and electrical systems in nuclear power plant (NPP) are represented by control logic diagram. To develop distributed control system (DCS), the designer and supplier should complete the activities of control logic configuration, testing, and verification, which are based on control logic diagram. Design verification is an effective method to ensure the correctness of control logic design. This paper represents a system, which is capable of implementing control logic design verification automatically for NPP instrumentation and control (I&C) system, as well as an overview of the procedure and some examples by using this system. With the design data (including control requirements and control logic diagrams in computer-readable format) and simulation technology, this system automatically performs design verification based on different rules and confirms the design outputs meet the inputs—the control requirements of plant's systems. Finally, a conclusion about the design verification system and future scenarios is given.

Adaptive Type-2 Fuzzy Logic Control Applied to the Inverted Pendulum on a Cart Problem

This paper introduces the design of an adaptive interval type-2 fuzzy logic controller and its implementation on a pendulum-cart system. It includes the theoretical foundations of: type-2 fuzzy logic system, input-output linearization control, fuzzy systems for functions approximation and adaptive systems. Type-2 fuzzy controllers provide an approach for using wide variety of opinions in control design. The above allows minimizing the effect of uncertainties in the rule base of fuzzy logic systems. These types of controllers provide greater flexibility in the application of human knowledge during the design of control systems in contrast to traditional controllers employing type-1 fuzzy logic. We propose to compare an adaptive interval type-2 fuzzy logic controller with its corresponding adaptive type-1 fuzzy logic controller. These controllers are tested in real-time on an inverted pendulum on a cart experimental prototype under the presence of parametric uncertainties in the mass of the pendulum. Five performance indexes are computed to compare both controllers, showing that type-2 fuzzy systems can help to improve the response of type-1 fuzzy systems. Copyright © 2018 Praise Worthy Prize - All rights reserved.

Design and implementation of adaptive control logic for cart-inverted pendulum system

In this article, an adaptive control logic is proposed to serve as a supervisory control system sufficient to curb the adverse effects due to modelling uncertainties and external disturbances. The control logic belongs to the class of adaptive control methodologies. The attractive attribute of this technique is that only the superior features of each individual candidate controller are obtained by applying appropriate weight to these controllers. In order to prove its effectiveness and applicability, the benchmark problem for stabilization of cart-inverted pendulum system is carried out using this technique. The system performance is tried against that with each individual candidate controllers existing techniques. In addition, the simulation-based analysis is strengthened by analysing the performance of a real-time cart-inverted pendulum system setup, stabilized using the proposed control logic.

Design of PI and Fuzzy Logic Controllers for Distribution Static Compensator

<span>This paper presents study of distribution static compensator (D-STATCOM) for compensation of reactive power, harmonic distortion mitigation and load balancing in three phase three wire nonlinear load distribution system. The proposed control algorithm is developed based on synchronous reference frame theory using PI and FUZZY logic controller. The obtained reference current signal from control algorithm is compared in hysteresis band current controller for better switching of D-STATCOM. The performance of DSTATCOM with PI and fuzzy logic controller is also analysed and compared for DC voltage regulation and harmonic distortion mitigation .The proposed method is provided effective compensation for reactive power, harmonic distortion mitigation and load voltage balancing. The simulation results are obtained using MATLAB/SIMULINK soft ware.</span>

PID and Fuzzy Logic Controller Design for Balancing Robot Stabilization

This paper addresses the problem of position control and stabilization for the two wheeled balancing robot. A mathematical model is derived based on the robot’s position and tilt angle and a fuzzy logic control is proposed for the balancing robot control. The fuzzy logic controller performance is compared with a conventional PID controller to show the difference between them. Both controllers were tested on the balancing robot in simulation using MATLAB software and the results were put together for a comparative point of view. The simulations shows a relative advantage for the fuzzy logic controller over the conventional PID controller especially in reducing the time required for stabilization which takes about 2 seconds and almost without overshoot while in the PID case the robot will have about 10% overshoot in position and about 20 degrees in tilt angle.

Single axis control of ball position in magnetic levitation system using fuzzy logic control

This paper presents the design and real time implementation of Fuzzy logic control(FLC) for the control of the position of a ferromagnetic ball by manipulating the current flowing in an electromagnet that changes the magnetic field acting on the ball. This system is highly nonlinear and open loop unstable. Many un-measurable disturbances are also acting on the system, making the control of it highly complex but interesting for any researcher in control system domain. First the system is modelled using the fundamental laws, which gives a nonlinear equation. The nonlinear model is then linearized at an operating point. Fuzzy logic controller is designed after studying the system in closed loop under PID control action. The controller is then implemented in real time using Simulink real time environment. The controller is tuned manually to get a stable and robust performance. The set point tracking performance of FLC and PID controllers were compared and analyzed.

Design of Multi-Context Reconfigurable Logic Controllers Implemented in FPGA Devices Oriented for Further Partial Reconfiguration

Reconfigurable systems have been recently used in many domains. Although the concept of multi-context logic controllers is relatively new, it may be noticed that the subject is receiving a lot of attention, especially in the industry. The work constitutes a stepping stone in design of reconfigurable logic controllers towards bridging the gap between Petri nets, their decomposition, formal verification and implementation with the use of FPGA structures with the possibility of further partial reconfiguration. The paper proposes a new design concept of reconfigurable logic controllers, implemented with the FPGA device. A logic controller is formally described by a Petri net and decomposed into separate sequential modules. Optional versions (contexts) of the selected module may be prepared additionally. Depending on the needs, a particular module can be replaced by either version (context) with the use of the partial reconfiguration technique. To avoid formal errors and mistakes, the proposed design path is supported by formal verification with the model checking methods based on the rule-based logical model. The proposed design concept has been verified experimentally with the application of Xilinx FPGA devices.

Ant Colony Optimization Based Type-2 Fuzzy Force-Position Control for Backhoe Excavator Robot

This paper proposes the design and simulation of Interval Type-2 Fuzzy Logic Control using MATLAB/Simulink to control the position of the bucket of the backhoe excavator robot during digging operations. In order to reach accurate position responses with minimum overshoot and minimum steady state error, Ant Colony Optimization (ACO) algorithm is used to tune the gains of the position and force parts for the force-position controllers to obtain the best position responses. The joints are actuated by the electro-hydraulic actuators. The force-position control incorporating two-Mamdani type-Proportional-Derivative-Interval Type-2 Fuzzy Logic Controllers for position control and 3-Proportional-Derivative Controllers for force control. The nonlinearity and uncertainty in the model that inherit in the electro hydraulic actuator system are also studied. The nonlinearity includes oil leakage and frictions in the joints. The friction model is represented as a Modified LuGre friction model in actuators. The excavator robot joints are subjected to Coulomb, viscous and stribeck friction. The uncertainty is represented by the variation of bulk modulus. It can be shown from the results that the ACO obtain the best gains of the controllers which enhances the position responses within the range of (19, 23 %) compared with the controllers tuned manually.