Fuzzy Logic Based PID Controller Research Articles

Design of a quasi‐oppositional FBI based fuzzy PIDF (1 + PI) controller for frequency regulation with renewable energy sources and energy storage elements

AbstractIntegration of renewable energy sources (RESs) in modern power system has put a great challenge on researchers and system engineers to satisfactorily operate the power system when it is subjected to various disturbances. Automatic generation control (AGC) plays a very essential role in modern power system to control the tie‐line power flows and system frequencies. This paper illustrates about optimal design and implementation of various controllers for AGC of a two‐area non‐reheat thermal power system with some supplementary generation from dish stirling solar thermal system and wind‐turbine system. In addition to the generating sources, some energy storage systems like capacitive energy storage and redox flow battery are integrated to improve the dynamic stability of the system. Various controllers like fuzzy logic based PID controller, PID controller with filter (PIDF) and fuzzy PIDF (1 + PI) controller are used as supplementary controllers of the AGC system. The proposed controllers are optimally designed by FBI algorithm and QO‐FBI algorithm. A step load of 1% (0.01 pu) is applied in area‐1 to analyze the performances of the proposed controllers. Investigation of the study includes undershoot, overshoot and settling time of frequency and tie‐line power deviations. The percentage improvement of QO‐FBI based FPIDF (1 + PI) controller with respect to ICA based FPIDF (1 + PI) controller is examined. It is noticed that, AGC system equipped with QO‐FBI based FPIDF (1 + PI) controller outperforms ICA‐FPIDF (1 + PI) controller in all aspects. The superiority of the QO‐FBI based FPIDF (1 + PI) controller is validated under parametric variation in system parameters. Sensitivity analysis is also carried out by varying the inputs to the intermittent renewable sources. Comparative performance analysis reveals that QO‐FBI based FPIDF (1 + PI) controller performs better in comparison with other proposed controllers and a recently proposed ICA based FPIDF (1 + PI) controller.

Design of a Fuzzy Based Pid Algorithm for Temperature Control of An Incubator

The incubator is an apparatus that is used to regulate environmental conditions such as temperature, humidity control in an enclosure. To maintain the temperature of the incubator is difficult and challenging. This research paper proposes the design of an incubator temperature control by using fuzzy based PID. The proposed model construct of two fuzzy logic based PID controllers to control the temperature. This paper principally focuses on the designing of new fuzzy self-tuning PID algorithm. The error and changing error rate are inputs of the fuzzy based PID controller. The PID parameters are outputs of the fuzzy based PID controller. A set of fuzzy rules is used to regulate the PID parameters. The simulation result shows that the rising time, settling time & overshoot had reduced compared to PID control.

HEADING CONTROL OF AUTOMATED GUIDED VEHICLES

With rapid developments in industry wide automation control systems, there have been numerous proposed design and control strategies as alternatives to conventional methods. This term paper deals with the same in the context of Automated Guided Vehicles (AGV’s) with a review of the current literature for proposed design improvements as well as trajectory control systems that can improve productivity and reduce conflicts compared to current methods. The results of these proposed methods are also compared in contrast to each other to obtain holistic view of the merits and demerits of the same. It is found that a fuzzy logic based PID control is a definite upgrade over conventional PID control systems and that the application of LIDAR and Camera based technologies can help enable free roaming AGV’s lending to increased robustness and flexibility. For a control system consisting of a single AGV and multiple processing stations, a genetic algorithm enhanced centralized fuzzy logic control system is the most optimal path planning algorithm whereas in the cases of multiple robots, a dynamic priority allocated free roaming AGVsystem with semi-decentralized control is found to be much more efficient at simultaneously solving paths and reducingconflicts with other robots in real time compared to the purely centralized systems.

Design and analysis of fuzzy PID controller with derivative filter for AGC in multi‐area interconnected power system

This study presents a comprehensive analytical study of a fuzzy proportional-integral-derivative (fuzzy-PID) controller with derivative filter (fuzzy-PIDF) for automatic generation control (AGC) in multi-area power system tuned by a novel hybrid local unimodal sampling-teaching learning based optimisation (LUS-TLBO) algorithm. The relevant advantage of this recommended controller is its high sensitivity to load perturbation. Initially a two area non-reheat type thermal system is considered and the gains of PIDF controller are tuned employing hybrid LUS-TLBO algorithm. The supremacy of PIDF controller is shown by comparing the results with some recently published articles. The study is further extended to design fuzzy logic based PID controller with derivative filter (fuzzy-PIDF) for AGC of the same power system employing hybrid LUS-TLBO algorithm. Supremacy of the proposed approach is shown by comparing the results with another recently published article. In addition, the work is also extended to deal with AGC issues in two area multi source hydro thermal power system using the proposed controller. Finally, it is seen that fuzzy-PIDF controller retains its supremacy over PID/PIDF/fuzzy-PID controllers. In addition to it, robustness analysis is carried out for the non-reheat two area thermal power systems by varying different parameters within the range of ±50%.

An Optimized and Improved STF-PID Speed Control of Throttle Controlled HEV

An improved self-tuning fuzzy proportional–integral–derivative (ISTF-PID), fuzzy logic-based PID (FPID) and optimal PID controllers for speed control of nonlinear hybrid electric vehicle (HEV) are proposed in this paper. The performances of HEV with ISTF-PID, FPID and optimal PID controllers are compared with the performance of HEV with existing self-tuning fuzzy PID and conventional PID controllers. The gains of PID, FPID and ISTF-PID controllers are tuned using multiobjective genetic algorithm. The performance specifications such as integral of the absolute error, integral of the square of error, peak overshoot, rise time and settling time are considered as objective function of GA and for performance analysis of HEV with designed controllers. The proposed control techniques are designed to achieve the variable speed, fuel economy, reduced pollution and improved efficiency under uncertain environment.

Development of Energy Management System for Micro-Grid with Photovoltaic and Battery system

Global environmental concerns and the ever increasing need of energy, coupled with steady progress in renewable energy technologies, are opening up new opportunities for utilization of renewable energy resources. Distributed electricity generation is a suitable option for sustainable development thanks to the load management benefits and the opportunity to provide electricity to remote areas. Solar energy being easy to harness, non-polluting and never ending is one of the best renewable energy sources for electricity generation in present and future time. Due to the random and intermittent nature of solar source, PV plants require the adoption of an energy storage and management system to compensate fluctuations and to meet the energy demand during night hours. This paper presents an efficient, economic and technical model for the design of a MPPT based grid connected PV with battery storage and management system. This system satisfies the energy demand through the PV based battery energy storage system. The aim is to present PV-BES system design and management strategy to maximize the system performance and economic profitability. PV-BES (photovoltaic based battery energy storage) system is operated in different modes to verify the system feasibility. In case of excess energy (mode 1), Li-ion batteries are charged using CC-CV mechanism effectively controlled by fuzzy logic based PID control system whereas during the time of insufficient power from PV system (mode 2), batteries are used as backup to compensate the power shortage at load and likewise other modes for different scenarios. This operational mode change in PV-BES system is implemented by State flow chart technique based on SOC, DC bus voltages and solar Irradiance. Performance of the proposed PV-BES system is verified by some simulations study. Simulation results showed that proposed system can overcome the disturbance of external environmental changes, and controls the energy flow in efficient and economical way.

Fuzzy Logic based PID Controller for pH Neutralization Process

automation of a Water treatment plant involves monitoring and control of various parameters like Temperature, Pressure, Level, Flow and Vibration in the plant. Process Control plays a major role in the automation industry. The intricacy of any control mechanism has only increased due to an unprecedented increase in the requirements, instrumentation and various control loops. Therefore a simple PID control mechanism is not a practical option for efficient control of any real - time process, let alone automation of an entire plant. This paper presents an improved version of the classic PID control mechanism that is the use of Fuzzy control logic along with the PID control for the pH neutralization process in a water treatment plant. The implementation of this procedure will be relevant for any multivariable process. General Terms Automation, Industrial multivariable process Keywordsater treatment plant, classic PID, Fuzzy logic control, pH neutralization process, multivariable process

Performance comparison of optimal fractional order hybrid fuzzy PID controllers for handling oscillatory fractional order processes with dead time

Fuzzy logic based PID controllers have been studied in this paper, considering several combinations of hybrid controllers by grouping the proportional, integral and derivative actions with fuzzy inferencing in different forms. Fractional order (FO) rate of error signal and FO integral of control signal have been used in the design of a family of decomposed hybrid FO fuzzy PID controllers. The input and output scaling factors (SF) along with the integro-differential operators are tuned with real coded genetic algorithm (GA) to produce optimum closed loop performance by simultaneous consideration of the control loop error index and the control signal. Three different classes of fractional order oscillatory processes with various levels of relative dominance between time constant and time delay have been used to test the comparative merits of the proposed family of hybrid fractional order fuzzy PID controllers. Performance comparison of the different FO fuzzy PID controller structures has been done in terms of optimal set-point tracking, load disturbance rejection and minimal variation of manipulated variable or smaller actuator requirement etc. In addition, multi-objective Non-dominated Sorting Genetic Algorithm (NSGA-II) has been used to study the Pareto optimal trade-offs between the set point tracking and control signal, and the set point tracking and load disturbance performance for each of the controller structure to handle the three different types of processes.

Tuning of an optimal fuzzy PID controller with stochastic algorithms for networked control systems with random time delay

An optimal PID and an optimal fuzzy PID have been tuned by minimizing the Integral of Time multiplied Absolute Error (ITAE) and squared controller output for a networked control system (NCS). The tuning is attempted for a higher order and a time delay system using two stochastic algorithms viz. the Genetic Algorithm (GA) and two variants of Particle Swarm Optimization (PSO) and the closed loop performances are compared. The paper shows that random variation in network delay can be handled efficiently with fuzzy logic based PID controllers over conventional PID controllers.

Optimal fuzzy logic-based PID controller for load–frequency control including superconducting magnetic energy storage units

This paper proposes a new optimal fuzzy logic-based-proportional-integral-derivative (FLPID) controller for load frequency control (LFC) including superconducting magnetic energy storage (SMES) units. Conventionally, the membership functions and control rules of fuzzy logic control are obtained by trial and error method or experiences of designers. To overcome this problem, the multiple tabu search (MTS) algorithm is applied to simultaneously tune PID gains, membership functions and control rules of FLPID controller to minimize frequency deviations of the system against load disturbances. The MTS algorithm introduces additional techniques for improvement of search process such as initialization, adaptive search, multiple searches, crossover and restarting process. Simulation results explicitly show that the performance of the optimum FLPID controller is superior to the conventional PID controller and the non-optimum FLPID controller in terms of the overshoot, settling time and robustness against variations of system parameters.

Modeling and control of the magnetic suspension system

Abstract A fuzzy logic based controller applied to a simple magnetic suspension is presented in this paper. The simple electromagnet-ball system and the contactless optical position measurement system are developed as a physical model of the magnetic suspension. A nonlinear mathematical model is presented and linearized. This model has been used to design a discrete linear PID controller with optimal parameters. The physical real-time model was constructed in order to compare the performance of the linear discrete PID controller and the proposed fuzzy logic based PID controller. The decomposed fuzzy PID controller has proportional, integral, and derivative separate parts which are tuned independently. When testing it becomes clear that the decomposed fuzzy PID controller gives better performance over a typical operational range than a traditional linear PID controller.