Design Of Logic Controller Research Articles

Design and development of brain emotional learning based adaptive membership functions for type-2 fuzzy systems

This paper presents the design and development of Brain Emotional Learning based adaptive Type-2 Fuzzy Systems for control of dynamical systems. The BEL controller belongs to the class of bio inspired controllers, as its architecture is based on limbic system of human brain and is capable of providing solutions for complex real time problems. In this work, dynamics of Brain Emotional Learning are used for the adaptation of membership functions in the design of Type-2 Fuzzy Logic Controllers. The stability of the overall system is analysed through Lyapunov Yakubovich’s criteria. The proposed approach is validated on the benchmark system such as inverted pendulum, CSTR and Ship heading control through simulation and in real-time environment using OPAL RT OP5600.

Two-Layer Parallel Fuzzy Logic Controller Design for Semiactive Suspension System with a Full Car Model

This paper presents research results on semiactive suspension using a fuzzy logic controller. Firstly, a full car model is built with 7 degrees of freedom using a semiactive suspension system at all four wheels. The dynamic equations are converted to the state space representation to facilitate control design and improve accuracy in simulation design. Then, a two-layer parallel fuzzy logic controller is designed with 49 and 25 rules for two fuzzy inference systems. In this way, the fuzzy logic controller is able to respond to a wide operating range of the system and the output force is smoother. Finally, the evaluation results are performed in the frequency and time domains with a real random road profile, and they showed that the root mean square value of the signals when using a semiactive suspension system with the proposed fuzzy logic controller decreased by over 25% compared to the passive suspension system. This clearly demonstrates the effectiveness of the proposed controller in improving the ride comfort, the road holding and ensuring the suspension travel of cars.

Design of a novel mixed interval type-2 fuzzy logic controller for 2-DOF robot manipulator with payload

This paper investigates a novel coupling-based mixed interval type-2 fuzzy logic controller (MIT2FLC) for trajectory tracking problems of highly nonlinear and complex robot manipulator plants. The major impediment for these types of plants is coupling between the robotic links at the time of operation. In addition, the performances of these plants are adversely affected by parameter uncertainties, random noise and external disturbances. Therefore, the MIT2FLC approach with an additional degree of freedom in the membership functions is proposed to efficiently deal with the problem of uncertainty and provide robust performance. The Grey wolf optimization (GWO) is implemented to calculate the optimal parameters of the proposed controller. For checking the performance, the MIT2FLC approach is compared with its type-1 fuzzy counterparts, namely mixed type-1 fuzzy logic controller (MT1FLC), type-1 fuzzy logic controller (T1FLC) and PID controllers. Robustness analysis of the proposed controller is investigated for external disturbances, varying system parameters, and random noise.

Simulation and Modeling of Different Types of MPPT Techniques Based on PV System

This paper endeavored to analyze the performance of several maximum power point tracking (MPPT) strategies for use with PV installations. Methods like "perturb and observe," "incremental conductance," and "fuzzy logic controller" are evaluated here. Using the simulation program MATLAB/Simulink, we modeled a PV module and DC/DC boost converter and tested them with a variety of MPPT implementations. This research examines three distinct methods for calculating MPPT output: the traditional Perturb and Observe approach, the incremental conductance method, and the fuzzy logic controller. It is evident that when compared to the conventional P&O controller and the incremental conductance approach, the tracking speed achieved by the fuzzy logic controller is more consistent and faster. However, P&O controller's operating point keeps changing around the maximum power point even in steady state operation, which is a major drawback. In this study, we focus on the fuzzy logic controller design and contrast it with the incremental conductance controller and the P&O controller. This algorithm was used to record the daily peak power use. In this setup, a DC-DC converter and fuzzy logic controller work together to keep the PV system's output power at its maximum. MATLAB/SIMULINK is used for all simulations.

LQR+I and Fuzzy Logic Controller Design for DC Motor Position Control

Sabit mıknatıslı Doğru Akım (DA) motorları kontrol eğitimi uygulamalarında sıklıkla tercih edilmektedir. Kapalı çevrim DA motor kontrol uygulamaları için farklı birçok metot geliştirilmiştir. Geliştirilen metotların en önemli hedefi kontrolcü performansında yüksek başarım elde edebilmektir. Bu çalışmada, bir DA motorun açısal konum kontrolü, integratör ilave edilmiş doğrusal karesel regülatör (LQR+I) ve bulanık mantık kontrol (FLC) yöntemleri kullanılarak tasarlanmış ve öncelikle simülasyon ortamında daha sonra gerçek zamanda başarılı bir şekilde test edilmiştir. Model tabanlı LQR ve model tabanlı olmayan FLC kontrol yöntemleri deneysel bir sistem üzerinde uygulanmış ve elde edilen sonuçlar karşılaştırılmıştır. Kontrol algoritması hızlı kontrol prototipleme tekniği ile Waijung kütüphanesi kullanılarak hazırlanmış ve STM32F4 Discovery kiti aracılığıyla sistemde testler gerçekleştirilmiştir. Kontrolcü performanslarının daha net ortaya çıkması için gerçek zamanlı farklı referans sinyalleri sisteme uygulanmış, bu sinyaller sonucunda ise her iki kontrolcü de başarılı sonuçlar elde etmiştir.

Enhanced Control Designs to Abate Frequency Oscillations in Compensated Power System

The interconnection of transmission, distribution, and generation lines has established a structure for the power system that is intricate. Uncertainties in the active power flow are caused by changes in load and a growing dependence on renewable energy sources. The study presented in this paper employs several controlling strategies to reduce frequency variations in series-compensated two-area power systems. Future power systems will require the incorporation of flexible AC transmission system (FACTS) devices, since the necessity for compensation in the power system is unavoidable. Therefore, a static synchronous series compensator (SSSC) is installed in both areas of our study to make it realistic and futuristic. This makes it easier to comprehend how series compensation works in a load–frequency model. With the integration of electrical vehicles (EVs) and solar photovoltaic (PV) systems, several control strategies are presented to reduce the frequency oscillations in this power system. Particle swarm optimization (PSO) is used to obtain the best PI control. To improve results, this work also covers the design of fuzzy logic control. In addition, the adoption of neural network control architecture is proposed for even better outcomes. The outcomes clearly show how well the proposed control techniques succeeded.

Design of type-2 fuzzy logic controller in a smart home energy management system with a combination of renewable energy and an electric vehicle

Home energy management is one of the most important parts of a smart home that manages the efficient use of energy in the smart home. This paper aims to design two type-2 fuzzy logic controllers in the demand-side energy management system. For this purpose, a combination of renewable energy sources, such as fuel cells, photovoltaic solar panels, vertical axis wind turbines with a helical savonius rotor, and an electric vehicle and energy storage system along with an external grid are utilized to supply the electricity usage of home appliances in a smart home. By using the proposed method, higher quality, more economical, and environmentally friendly energy can be accomplished. To this end, the outputs of the proposed controllers are defined to make appropriate decisions about the generated energy, how to supply energy for own consumption, and controllable loads. The number and distribution of membership functions of type-2 fuzzy logic controllers are selected according to the measured real input data over a year in Tehran, Iran. To demonstrate the effectiveness of the proposed method it is simulated by MATLAB/Simulink software, which indicates that the proposed system causes the smart home to receive 49.186 kWh less electricity energy from the grid to supply daily power for home appliances and therefore can weekly consume approximately 343.95 kWh less electricity energy from the grid. it is shown that after applying the proposed strategy, electricity costs were reduced by 71.5%, and the peak-to-average ratio was reduced by 64.6%.

Design of a Saving-Energy Fuzzy Logic Controller for a Differential Drive Robot Based on an Optimization

In the problem of designing a Fuzzy Logic Controller (FLC) for robots in general and a Differential Drive Robot (DDR) in particular, the determination of the parameters of Membership Functions (MFs) and Fuzzy Rules (FRs) is a difficult, complicated, and time-consuming problem because this is mainly based on heuristics and the knowledge of experts. Therefore, this paper provides a new method to efficiently design an FLC for the DDR by using the Genetic Algorithm (GA). Here, the GA is used to generate and optimize both the parameters of MFs and the FRs according to the minimum kinetic energy loss criterion. For this purpose, a program is created in Google Colab® by using the Python language with the help of the “Pymoo” library to not only automatically generate all the suboptimal parameters of MFs and the suboptimal FRs but also the simulate and evaluate different used FLCs. This program is published as an open-source code so that all readers can browse, view, run, and modify the code themselves to design their FLC. The simulation results have shown that the designed FLC is much better than other used FLCs in terms of the minimum kinetic energy loss while other control performances are still good.

Use of Artificial Neural Networks in the Design of Adaptive Fuzzy Logic Controllers in the manufacturing of Prosthetic Knees

This paper presents real-time parameter updates that help to make adaptive machining process robust to changes in exogenous operating conditions. This work supports the commercial imperative for a customizable ‘batch size of one’ implant that does not unreasonably affect operating costs like tool life. A Neural Network (NN) is presented for use within a Computer Numerical Control (CNC) manufacturing cell to determine real-time tool offset adjustments in knee prostheses. This study integrates additional sensor inputs from the CNC cell, including improved force monitoring data for critical tools used in the machining of a Tibial component. The resulting time series force model is used to compare classification performance on Random Forest (RF) and Bi-directional Long Short Term Memory (BiLSTM) Neural Networks. In relation to network training performance, pre-processing improvements are reported for the RF algorithm using a time series data conversion process step. For the case of the BiLSTM model, 2D time series data is converted to a 3D array using a novel projection technique. The accuracy of both of methods is assessed in real-time using tool offset control applied using an adaptive fuzzy logic law. In this use case it has been observed that a RF approach exhibits less overfitting than its BiLSTM counterpart and therefore is a better choice for the dynamic computation of the tool offset height, the actuator output.

Modeling and Simulation of Electric Thrust Reverser Actuator Control Based on Simulink

According to the structural characteristics and working principle of the electric actuator system of the aircraft thrust reverser, the mathematical control model of the thrust reverser actuator is proposed for a certain type of electric thrust reverser actuator system. The model is established and simulated by the modular modeling method based on Simulink software. The actuator’s load force, transmission, displacement, and velocity relationship are analyzed. The simulation results show that the model can simulate the deployment and stow of the actuator under different conditions and provide a platform for the control logic design, force analysis, and fault diagnosis of the electric thrust reverse actuator system.

Energy Savings for Air Conditioning System Using Fuzzy Logic Controller Design for Northeastern Nigeria

Efficient air cooling in an air conditioning system minimizes power consumption. The air conditioning system is considered one of the home appliances in which a massive amount of electrical energy is recorded, especially in the urban area. In this work, the fuzzy logic controller is designed to save energy for northeastern Nigeria using six and two input and output parameters respectively. The input parameters consist of the temperature of the user, temperature difference, number of occupants, time of the day, dew point temperature, and weather conditions. The output parameters consist of compressor speed and operation mode. The controller performance was simulated. The controller is designed in such a way that it can control the compressor speed leading to energy savings, and the operation mode to optimize humidity conditions, and when the room gets hot, it switches to air conditioning. The simulated result showed that a good percentage of electrical power could be saved when fuzzy logic is utilized

Design of Robust Fuzzy Logic Controller Based on Gradient Descent Algorithm with Parallel-Resonance Type Fault Current Limiter for Grid-Tied PV System

This article demonstrates a new topology for optimization of the electrical variables and enhancement of low-voltage-ride-through (LVRT) capacity of a grid-tied photovoltaic system (PS) during asymmetrical faults. The proposed topology comprises a fuzzy-logic controller (FLC) based on gradient descent (GD) optimization in association with parallel-resonance-type fault current limiter (PRFCL) as an LVRT circuitry. Gradient descent is an iterative process to minimize the objective function by updating the variable in the opposite direction of the gradient of the objective function. The PRFCL optimizes the fault variables, specifically preventing voltage sag without any transitional spikes. A 100-kW detailed model of grid-tied PS is used in MATLAB/Simulink to analyze the response of the proposed topology at the point of common coupling (PCC) and PV side variables. A keen comparative study of the conventionally adopted proportional-integral (PI) controller in association with crowbar circuitry is carried out for the justification of the proposed topology. The simulation findings of the proposed topology authenticate the optimal response of variables in terms of stability, robustness, smoothness, and fault tolerance at both the grid side and the PV side.

An adaptive fuzzy logic controller for intelligent drying

A systematic approach to the design of an adaptive fuzzy logic controller (AFLC) for intelligent drying with a computer vision system (CVS) in a feedback loop is proposed. Developed AFLC is based on an artificial neural network (ANN), geno-fuzzy algorithm, and multi-objective fuzzy cost function. Fuzzy sets for the moisture content and product quality are automatically generated by using principal component analysis (PCA) and fuzzy clustering. In addition, the concept of fuzzy time is introduced to optimize the duration of each control step. The fuzzy rule base for the controller was constructed through a two-stage process of (i) warming-up based on simulation and optimization (offline) and (ii) fine-tuning during real-time drying (online). The application of AFLC for shrimp drying showed advantages of the unsupervised fuzzy logic control, such as decreased drying time, less quality degradation, and smaller energy consumption.

A circle chaos random search strategy particle swarm optimization with its application

As a popular optimization, particle swarm optimization has attracted many researcher's attention and also been successfully applied to solve many real world problems. As adopting the strategy of history experience, the convergence rate of PSO is faster than other evolutionary algorithms. But the individuals of PSO are easily be trapped into local optimum, which causes the algorithm could not guaranty confidence of the final results. In this paper, for further enhance the global search ability of PSO, based on comparing different chaos based random strategies, we propose a circle chaos based mutation strategy into PSO algorithm. First, compared with other operators, since the circle chaos based operator could generate more even results, we propose the circle operator based random strategy to balance the global and local search of our PSO algorithm. Second, for attracting individuals to precisely search in a promising region, a new historic experience based elite array is proposed to lead the search direction of population. Then the algorithm could achieve more precise results. For further proving the effectiveness of our algorithm, we apply the algorithm into PID fuzzy logic controller design. Compared with other EA algorithms, the experimental results demonstrate our methods achieve better performance on convergence rate and precise of results.

Fuzzy Logic Control Design and Implementation with DC-DC Boost Converter

Being an electrical switch, this converter transforms an uncontrolled input DC voltage into a regulated one to get a desired output voltage. The MOSFET works in the circuit boost-converter as an electronic switch that closes and opens several times. The current passing through the inductor determines the modes operation of the boost-converter circuit. We proposed the new fuzzy control circuit (maximum power point (MPP) circuit using Fuzzy Logic Control (FLC) algorithm) was designed after replacing the DC source with a photovoltaic (PV) array and the duty cycle (constant) with the FLC and keeping the circuit components same except for the Pulses Width Modulation (PWM) of frequency 3800 Hz. In the full circuit, they controlled the MPP of the PV array through a boost converter and FLC., the relationship between the power and voltage of the PV array was drawn to access the MPP at fixed constant solar irradiance and temperature. The value of the solar irradiance altered during the day from low (in the morning) to high (with a peak at the noon) before being reduced to very low at the sunset. The proves that the FLC algorithm works efficiently to make the power of the PV cell always at the maximum value (MPP). The stability of the PV cell voltage and its current change also proves that it operates according to the specifications of the P-V and I-V characteristics of the PV cell referred to earlier the output voltage was increased because we used a step-up converter (boost converter with FLC). The achievement system is showed to be efficient and robust in improving solar charging and rectifying capacity.

Application of a Tactile Sensor for the Gait Phase Classification for an Exoskeleton

This paper presents the design and implementation of fuzzy logic control for human walking using lab-developed sensors and the second lower limb robotic exoskeleton (LLRE-II) to detect gait phases. A piezoresistive tactile sensor (PRTS) was developed and used to measure the foot pressure to predict human walking behavior. The proposed sensor with grid structures was then fabricated using polymer composites of multi-walled carbon nanotubes (MWCNTs) combined with polydimethylsiloxane (PDMS). The doping ratio and design of the grid structure of the sensors were optimized to achieve a good sensing range. The foot reactive forces measured by the four sensors were calculated and converted to force ratio factors to improve the performance of gait phase detection by the fuzzy logic control. Based on the sensor tests, the most stable doping ratio was fixed as 7 wt%, and the ratio of the grid structure (line width:line spacing:thickness) was 1:1:1. Sensors were set in the soles of the shoes on the foot pads of the exoskeleton, and the foot reactive forces were captured for analysis. The performance of the proposed algorithm for gait phase detection was verified experimentally. The results indicated that both regular and irregular walking could be detected by the proposed method.

Fuzzy Logic Controller Design for First Order Time Delay Systems

Abstract: In this paper, a Fuzzy Logic Controller for reducing the time delay (Dead time) is designed. The main purpose of this work is to build a unique FLC which controls the time delay occurring in industries. In most of the industries for controlling time delay PI and PID controllers are used, but when they are compared to FLC the performance parameters such as response time, overshoot is less and accurate in fuzzy. Even it is showed that FLC reduces the Steady state error. Overall, it shows that effect of Fuzziness is more accurate than that of PI and PID controllers.

Design of optimized interval type-2 fuzzy logic controller based on the continuity, monotonicity, and smoothness properties for a cart-pole inverted pendulum system

In this study, an interval type-2 fuzzy logic controller design method is proposed and validated on the real-time under-actuated nonlinear inverted pendulum system for swing-up and stabilization control problems. The swing-up algorithm is designed to give a faster response and the stabilization controller is designed based on continuity, monotonicity, and smoothness theorems for worst and best cases using the Mamdani fuzzy inference system in order to show the effectiveness of the proposed method. Outstanding type reduction methods are analyzed for the stabilization controller based on the design approach to determine the best type reduction algorithm for the effective and robust control performance. Real-time experiments are conducted to investigate the capability of the proposed controller in terms of adaptation performance and robustness ability. The controller also is able to handle structured and unstructured uncertainties such as measurement noise, external payload, undesirable internal/external disturbances, and parameter uncertainties. The results show that the proposed method clearly improves the control performance of the system in six experimental tasks conducted.

Design and Implementation of Programmable Logic Controller Based Automatic Transfer Switch

A PLC-based automatic transfer switch (ATS) may improve production in the industry efficiency and also the household power connection. It's an electrical switch that may be used to change the load when the main power is failing to supply electricity. Manually controlled transfer switches exist. In this scenario, a switch must be thrown by an operator to take manual control of the system. Some, on the other hand, are activated automatically when the main power source fails. When a major source of electricity is no longer functioning, power from a new or used generator can be either manually or automatically transferred when utilize a transfer switch for transferring control to the on-side application. Using a programmable logic controller (PLC), we describe the implementation and design of an automatic transfer switch (ATS). The primary function of a transfer switch is to divert electricity from the main grid to a standby power supply. Single-phase and three-phase circuit breakers, Siemens Logo PLC, relays, and indicator lights are used in this system. This portable and economic system would be helpful to every domestic, industrial, factory, and academic institution.

Design and Implementation of Programmable Logic Controller Based Automatic Transfer Switch

A PLC-based automatic transfer switch (ATS) may improve production in the industry efficiency and also the household power connection. It's an electrical switch that may be used to change the load when the main power is failing to supply electricity. Manually controlled transfer switches exist. In this scenario, a switch must be thrown by an operator to take manual control of the system. Some, on the other hand, are activated automatically when the main power source fails. When a major source of electricity is no longer functioning, power from a new or used generator can be either manually or automatically transferred when utilize a transfer switch for transferring control to the on- side application. Using a programmable logic controller (PLC), we describe the implementation and design of an automatic transfer switch (ATS). The primary function of a transfer switch is to divert electricity from the main grid to a standby power supply. Single-phase and three-phase circuit breakers, Siemens Logo PLC, relays, and indicator lights are used in this system. This portable and economic system would be helpful to every domestic, industrial, factory, and academic institution.