Coefficients Of PID Controller Research Articles

Adaptive PID sliding mode controller application to position control of hydraulic system

This study proposes a sliding mode controller combined with the direct parameter adjustment method of proportional–integral–derivative (SMCPID) to control a hydraulic cylinder system. A simulation model using a hydraulic cylinder and a damper is set up to verify the results and accuracy of the proposed controller. In the SMCPID controller, a PID controller is used to generate a control signal combined with the sliding plane to stabilize and sustain the sliding mode. Due to the hydraulic system's nonlinear nature, the PID controller's coefficients need to be calculated and adapted according to an adaptive law. The SMCPID controller has been tested and compared with other controllers such as the PID controller, fuzzy controller combined with PID, and fuzzy controller combined with adaptive PID in controlling the position of the cylinder axis for different target paths. Simulation results are performed to verify and analyze the effectiveness of the proposed controller.

Improving the Power Output of a Partially Shaded Photovoltaic Array through a Hybrid Magic Square Configuration with Differential Evolution based Adaptive P&O MPPT Method

Abstract A partially shaded photovoltaic (PV) array's characteristic curve is convoluted due to disparity in irradiance levels between shaded and unshaded PV panels, resulting in power mismatch losses. This work presents a new hybrid approach combining the Magic Square (MS) array configuration and Differential Evolution based adaptive perturb and observe (DEAPO) MPPT methodology to overcome the abovementioned problem. The proposed hybrid methodology is implemented in two steps: first, repositioning the PV panels as per the MS configuration to decrease the power losses of partial shading. In MS configuration, the concentrated shadow on a single row or column can spread over to the entire PV array equally without any physical or electrical switching of PV panels. Second, the DEAPO MPPT method is developed to find the global peak power point on the PV characteristic curve. PID controller coefficients are optimized by DE to enhance the tracking speed and convergence of the adaptive P&O MPPT. The simulation study of this work has been implemented using PV arrays in MATLAB/SIMULINK environment and the real-time validation is done through a 5 kW PV array. The proficiency of the proposed hybrid approach is tested by creating various non-uniform and uniform shading patterns on the PV array. The simulation and experimental results prove that the proposed hybrid approach increases the power output by 19% and 20% higher than the existing Total Cross Tie (TCT) configuration under non-uniform and uniform shading cases respectively.

Efficient PID Control Design for Frequency Regulation in an Independent Microgrid Based on the Hybrid PSO-GSA Algorithm

Microgrids are a part of the power system that consists of one or more units of distributed generation and are expected to remain in operation after being disconnected from the system. Since they rely on overlying networks, frequency control is very important for network-independent operation. Some of the most common problems in independently operating microgrids are frequency sustainability and its fluctuations. The main purpose of this study is to control the frequency of a microgrid in island mode in different scenarios. The objective function is defined based on time and changes in the system frequency. Thus, the variable parameters of the PID controller are transformed into an optimization problem and are solved through the hybrid PSO-GSA algorithm. The study considers four scenarios: (a) a microgrid dynamic model and optimal PID controller coefficients; (b) variable velocity disturbance applied to the studied system in order to observe power changes and the microgrid frequency; (c) stepped load changes applied to the studied system; and (d) the proposed methods on the standard test function. Simulations under different operating conditions are performed, indicating improvements in the stability of microgrid frequency fluctuations by means of the proposed control method.

Autonomous 6-DOF Manipulator Operation for Moving Target by a Capture and Placement Control System.

The robot control technology combined with a machine vision system provides a feasible method for the autonomous operation of moving target. However, designing an effective visual servo control system is a great challenge. For the autonomous operation of the objects moving on the pipeline, this article is dedicated to developing a capture and placement control system for the six degrees of freedom (6-DOF) manipulator equipped with an eye-in-hand camera. Firstly, a path planning strategy of online capture and offline placement is proposed for real-time capture and efficient placement. Subsequently, to achieve the fast, stable, and robust capture for a moving target, a position-based visual servo (PBVS) controller is developed by combining estimated velocity feedforward and refined PID control. Feedforward control is designed using the estimated velocity by a proposed motion estimation method for high response speed. PID control is refined by dead zone constraint to reduce the manipulator’s jitter caused by the frequent adjustment of manipulator control system. Besides, the proportional, integral, and differential coefficients of PID controller are adaptively tuned by fuzzy control to reject the noise, disturbance, and dynamic variation in the capture process. Finally, validation experiments are performed on the constructed ROS–Gazebo simulation platform, demonstrating the effectiveness of the developed control system.

Design of HHO-PID Controllers for Load Angle of Power Plant Synchronous Generators

Accurate analysis of load angle stability of the synchronous generator depends on considering mechanical parameters in addition to electrical parameters in synchronous generator modeling, which leads to increasing state-space variables and model complexity and ultimately reduces the accuracy and performance of conventional controllers. Therefore, an intelligent controller is required for the stable and reliable operation of the synchronous load angle generator. With this approach in this paper, first considering the electrical and mechanical parameters, a complete 14-order model of the synchronous generator is obtained. Then, a PID controller based on the Harris optimization algorithm is proposed to stabilize the load angle of the synchronous generator. The HHO optimization algorithm is a population-based optimization technique that optimizes PID controller coefficients. The effectiveness of the new HHO technique in optimizing the controller PID coefficients over known optimization techniques such as GA-PID and Modified GA-PID has been confirmed using simulation results. The simulation results show that the proposed controller has a higher performance in load angle stability compared to the sliding mode and fuzzy-PID controllers.

РОЗРОБКА ПРОГРАМНОГО ЗАБЕЗПЕЧЕННЯ ДЛЯ ІНФОРМАЦІЙНО-УПРАВЛЯЮЧОЇ СИСТЕМИ ВИРОЩУВАННЯМ АРСЕНІДУ ГАЛІЮ ДЛЯ ПОРУВАТИХ ПІДКЛАДОК

Purpose. The article discusses the features of improving the technology of growing gallium arsenide ingots for the production of substrates that are intended for applying a porous film. Such porous gallium arsenide is used to manufacture gas sensors with improved technical parameters. Such sensors are highly sensitive and can operate at room temperature without the use of heating systems. To improve the technology of growing gallium arsenide ingots, the paper proposes the development of software for an information-control system for growing ingots. The features of the technological process of growing gallium arsenide ingots are considered in detail and the main parameters that directly affect the process are analyzed. Based on the analysis, the requirements for the operation algorithm of the information and control system have been developed. Methodology. The developed algorithm allows organizing the system operation in three modes; Technologist mode, operator mode, adjuster mode. Each mode has its own privileges and its own limitations. In addition, the algorithm allows organizing control and output of information from the following subsystems: heater control subsystem, crucible control subsystem, seed control subsystem, weight sensor control subsystem, as well as storing information in the database. Results. Software has been developed that implements this algorithm. The technologist mode is designed to form the growth profile of ingots. The technologist can choose one of the existing profiles previously recorded with reference to the ingot brand, or create a new profile in case of launching a new batch of products. The profile allows you to bind changes in technological parameters to the length of the ingot. In the "Operator" mode, the system displays current information about the technological process and allows you to organize work in automatic or manual mode. Manual mode is designed to adjust the process parameters in case of emergency situations. In the “Adjuster” mode, it is possible to configure the control system depending on specific requirements, change the PID controller coefficients, and configure input and output signals. Originality. The proposed program differs from the existing ones in that it allows you to freely configure the control system for the growth of gallium arsenide ingots, in particular, to change the parameters with reference to the length of the grown ingot or to the diameter of the ingot. Change the parameters of the inputs and outputs of the controllers. Practical value. The developed system makes it possible to improve the quality of gallium arsenide ingots by eliminating the human factor, which often leads to process parameters going beyond acceptable values, to increase the repeatability of ingot parameters, and to obtain better substrates for manufacturing gas sensors. The proposed software can be used for the system of growing silicon ingots in the electronics industry. Figures 4, references 14.

Data-Driven Control for Proton Exchange Membrane Fuel Cells: Method and Application

A data-driven optimal control method for an air supply system in proton exchange membrane fuel cells (PEMFCs) is proposed with the aim of improving the PEMFC net output power and operational efficiency. Moreover, a marginal utility-based double-delay deep deterministic policy gradient (MU-4DPG) algorithm is proposed as a an offline tuner for the PID controller. The coefficients of the PID controller are rectified and optimized during training in order to enhance the controller’s performance. The design of the algorithm draws on the concept of marginal effects in Economics, in that the algorithm continuously switches between different forms of exploration noise during training so as to increase the diversity of samples, improve exploration efficiency and avoid Q-value overfitting, and ultimately improve the robustness of the algorithm. As detailed below, the effectiveness of the control method has been experimentally demonstrated.

Tuning of PID Controller Coefficients for AVR Systems by SA Algorithm

As a real time process, in tuning the coefficients of PID controllers in AVRs, accuracy vs. speed is an important issue. Considering complexity of the problem and real systems requirements, various methods, including exact methods and approximation algorithms, have been implemented for this purpose. Since the conventional methods based on meta-heuristic algorithms solving this problem, generally use population-based algorithms such as GA and PSO, this paper aims to investigate the efficiency and performance of single- solution based metaheuristics to solve this problem. So Simulated Annealing (SA) algorithm is proposed, and implemented for optimizing PID coefficients. In addition, an extension of SA is presented improving the search strategy based on neighborhood adjustment. The results indicate that the proposed algorithms as single based metaheuristics, have a good or even better performance vs. population based metaheuristics, in spite of simplicity in implementation and less computation requirements. This fact implies that the landscape complexity of these problems does not necessarily require population-based algorithms. The presented method is also applied to multiple objective functions regarding different time response criteria in output voltage and leads to better results in less time.

Tuning of PID Controller Coefficients for AVR Systems by SA Algorithm

As a real time process, in tuning the coefficients of PID controllers in AVRs, accuracy vs. speed is an important issue. Considering complexity of the problem and real systems requirements, various methods, including exact methods and approximation algorithms, have been implemented for this purpose. Since the conventional methods based on meta-heuristic algorithms solving this problem, generally use population-based algorithms such as GA and PSO, this paper aims to investigate the efficiency and performance of single- solution based metaheuristics to solve this problem. So Simulated Annealing (SA) algorithm is proposed, and implemented for optimizing PID coefficients. In addition, an extension of SA is presented improving the search strategy based on neighborhood adjustment. The results indicate that the proposed algorithms as single based metaheuristics, have a good or even better performance vs. population based metaheuristics, in spite of simplicity in implementation and less computation requirements. This fact implies that the landscape complexity of these problems does not necessarily require population-based algorithms. The presented method is also applied to multiple objective functions regarding different time response criteria in output voltage and leads to better results in less time.

Модель униполярного электродвигателя на основе высокотемпературных сверхпроводников

The electromechanical model for analyzing a homopolar electric motor with a magnetic system made using second-generation high-temperature superconductors (HTSC 2G) is described. Homopolar electric motors made with a disk-shaped rotor have the simplest design of their magnetic system and heavy-current contact. Owing to the use of HTSC 2G conductors for producing constant magnetic field in the rotor area, it becomes possible to achieve a higher current density in the windings, thereby increasing the motor power capacity. Due to the HTSC ability to operate at the liquid nitrogen temperature (77 K), it becomes possible to have a simpler cryostat design in comparison with magnetic systems based on low-temperature superconductors. For large-capacity homopolar motors, the use of liquid metal contacts for supplying current to the rotating rotor seems to be the most promising design solution. The advantage of motors of this type is that their torque depends linearly on the rotor current. The homopolar motor operation governed by a proportional-integral-differentiating (PID) controller was simulated using the SciLab Xcos software. The application of the analysis model for selecting the optimal PID-controller coefficients is demonstrated. The electric motor dynamic operation modes are analyzed. The numerical simulation results are compared with the previously obtained experimental data.

ALGORITHM OF ADJUSTMENT OF SUB-REGULATOR COEFFICIENTS WITH FUZZY LOGIC METHODS USING

The fuzzy PID tuning algorithm of proportional, integral, and derivative terms based on the fuzzy logic has been developed in the article. The fuzzy logic focuses on logic-linguistic models of representation of knowledges and it is the effective technology for creation of intellectual control systems of complex dynamic objects in the incomplete conditions.
 It has been researched that the fuzzy tuning algorithm of the basic coefficients for the PID controller сompared with the tuning algorithm based on the trial and error method, improved the quality of the of the transient process, namely reduces the overshoot and the settling time. Another advantage of the fuzzy PID tuning algorithm is that the PID controller coefficients can change their values ​​in accordance with changing conditions of operation control object, which improves the adaptive properties of the automatic control system.
 The structure of the automatic control system based on the fuzzy PID controller has been developed, the main components of which are the fuzzy PID controller and the transfer function of the control object. The fuzzy PID controller consists of the following main components: the fazzyfication unit, the rule base and the defazzyfication unit. This structure of the automatic control system does not require special means of identifying the parameters of the turboshaft engine and its implementation using modern microcontrollers is quite simple and affordable.
 The fuzzy PID tuning algorithm has been tested with using the parameters of the turboshaft engine ДГ90Л2 with power 16MW of the compressor 16 ГЦ2-395/53-76С of Dolyna linear production administration of gas transmittal pipelines.

Development of a control system with fuzzy tuning of values for the actuation setpoint

The article discusses the disadvantages of using fuzzy logic to correct the value of the PID controller coefficients in control systems. The disadvantages are related to the actuation setpoint, which knowingly doesn‘t provide optimal control during its implementation at the control object. It is proposed to use a fuzzy tuning of values for the actuation setpoint in the control system circuit based on the deviation between the measured values of the input action at the control object and the values accepted in the calculation by the mathematical model. Fuzzy tuning of values for the actuation setpoint provides that the control objects achieve the desired indicators without re-solving the optimization problem. The effectiveness of the proposed approach is demonstrated by the example of developing a control system for the electroplating process.

Influence of wind disturbances on the accuracy of flight algorithm and multicopter stabilization

The problem of wind disturbances influence reducing on the accuracy of multicopter stabilization by developing a stabilization system capable of compensating for these disturbances is considered.A mathematical model is developed and a multicopter control algorithm is proposed to compensate for the effects of wind disturbances. It is based on adaptation of the PID controller coefficients in the process of operation, most effectively affecting the multicopter response.A stabilization system has been developed to provide compensation for current disturbances. The stabilization system algorithm, taking into account the readings of a wind speed meter, is implemented on a microcontroller.Studies of the simulation management system using the Matlab software have been carried out. Flight tests have confirmed the effectiveness of the synthesized adaptive PID controller.

Fuzzy Decentralized Controller Design with Internet of Things for Urban Trains

Due to the dynamic structure and physical constraints that exist in controlling the urban train system, the physical parameters of the urban train model are constantly changing, and therefore a static controller cannot fully control all of the control objectives to be defined. In this paper, a new method of using a PID controller based on fuzzy control with considering the uncertainty of the weight of the dynamic model of the system is presented for managing the dynamical model of the urban train. The primary objective of this research work is to provide a structure that simultaneously, in addition to guaranteeing the stability of the Kharitonov polynomials, the dynamic model of the sample system also automatically adjusts and controls the proposed controller control parameters. In order to introduce model uncertainties into the controller design calculations, Kharitonov polynomials related to the open loop conversion function are first extracted. Then the feedback loop is constructed with a parallel PID controller, and by rewriting the closed-loop conversion function equations, we obtain the set of all closed-loop system transformation functions, in which the model's indices are also considered. Subsequently, by examining the stability ranges of all closed-loop functions, the values obtained for the proportional, integral, and derivative parameters of the PID controller are obtained for its robust performance. Finally, a fuzzy-based structure is proposed for intelligent operation and online adjustment of proposed PID controller coefficients. Further, this research work outlines twolevel Internet of Things (IoT) sensor network that compliments the proposed mathematical model by providing real-time model parameters using the sensory information.

Graphical Robust PID Tuning of TITO Processes

In this paper, PID controller for Decentralized TITO process is tuned using graphical approach. Ideal decoupler is used to decouple TITO system and then each decoupled system is approximated to FOPDT model. The Graphical method uses boundaries determined by the loci of stability and frequency domain characteristics such as Gain, and Phase margin etc. common region of these loci gives the values of the PID controller coefficients. The results are validated using MATLAB and the simulated results are presented for Coupled tank system.

Fractional-Order PID Motion Control for AUV Using Cloud-Model-Based Quantum Genetic Algorithm

Aiming to improve the performance of motion for autonomous underwater vehicle (AUV), a fractional-order PID strategy is proposed. It is a more generalized form for the conventional integer-order PID controller, keeping its simplicity and utilizing the generalized derivative and integral control actions. The fractional-order PID controller has been successfully applied to heading control, diving control and path-following system of AUV on sea trial. In addition, the fractional-order closed-loop system has proven to be stable. By comparing simulations and experiments, the satisfactory performance, such as overshoot, settling time and steady-state error, has been achieved. The cloud-model-based quantum genetic algorithm (CQGA) is employed to tune coefficients of fractional-order PID controller. The quantum bits and quantum superposition states avoid the pressure of selection and maintain the diversity of population in chromosome coding. Due to the randomness and stability tendency of cloud droplets, the cloud crossover operator and the cloud mutation operator can effectively overcome the shortcomings of premature and slow searching speed. Numerical simulations show that the CQGA is more efficient to find the optimal coefficients of fractional-order PID controller than GA.

Load Frequency Control in Microgrids Based on a Stochastic Noninteger Controller

In this paper, an adaptive multiobjective fractional-order fuzzy proportional–integral–derivative controller is proposed for the load frequency control (LFC) of islanded microgrids (MGs), while benefiting from the assets of electric vehicles (EVs) in this respect. Although the use of battery energy storage systems (BESS) can solve the unbalance effects between the load and supply of an isolated MG, their high cost and tendency toward degradation are restrictive factors, which call for the use of alternative power balancing options. In recent years, the concept of utilizing the BESSs of EVs, also known as vehicle-to-grid (V2G) concept, for frequency support of MGs has attracted a lot of attention. In order to allow the V2G controller operate optimally under a wide range of operation conditions caused by the intermittent behavior of renewable energy resources, a new multiobjective fractional-order control strategy for the EVs in V2G scenarios is proposed in this paper. Moreover, since the performance of the controller depends on its parameters, optimization of these parameters can play a significant role in promoting the output performance of the LFC control; hence, a modified black hole optimization algorithm is utilized for the adaptive tuning of the noninteger fuzzy PID controller coefficients. The performance of the proposed LFC is evaluated by using real world wind and solar radiation data. Finally, the extensive studies and hardware-in-the-loop simulations are presented to prove that the proposed controller tracks frequency with lower deviation and fluctuation and is more robust in comparison with the prior-art controllers used in all the case studies.

Adjustment of PID controller in fiber-optic gyro feedback loop

Functioning of closed-loop FOG is presented. Block diagram of FOG control system is given, and sources of nonlinear distortions of its components are described. A method to analyze the closed-loop FOG control system is proposed for adjustment of PID controller that does not require complex and high precision test equipment. Control target function is set, and coefficients of PID controller are selected optimal for this target function and certain FOG sample.

Determining PID controller coefficients for the moving motor of a welder robot using fuzzy logic

In this paper, a fuzzy algorithm was used for determining the coefficients of a PID controller using an online method. The plant used in this system is a welder robot, which is used for welding oil and gas pipelines. This robot rest on the pipe and weld it by moving around. The speed is adjusted using a motor moving the robot around the pipe. A digital controller also used for implementation. In this research, in order to choose the rules the skills transmit method and that how the PID response is required has been used. In this paper, the type of algorithms that continuously assigns PID coefficients using an online method depending on the characteristics of the system which is based on fuzzy logic was used. First, the rules associated to each output in relation to inputs are depicted in it. Using the mentioned method, simulation results and then implementation results were obtained and discussed.

АДАПТИВНИЙ ПРОПОРЦІЙНО-ІНТЕГРАЛЬНО-ДИФЕРЕНЦІАЛЬНИЙ РЕГУЛЯТОР У РОБОТИЗОВАНИХ СИСТЕМАХ

The purpose of the submitted master's thesis is the implementation of a system for automatic tuning of the PID controller coefficients, which is used in robotic systems. The main task of the work is to determine the factors influencing the stability of the system, which are controlled by the PID controller and to solve the issue of adjusting the coefficients when these factors change. Analysis and construction of a system for automatic adjustment of coefficients. Finding ways to get data from feedback and regulate this data. Creation of a real prototype of a control system based on a microcontroller and implementation of software for the operation of a system capable of autonomously adjusting PID coefficients in real time. In the work, the influence of external and internal factors on the stability of the system was investigated, the necessary feedback was chosen to receive data to the microcontroller, and the software for the operation of the system was created. This work can be used in industry and prototyping for fast and high-quality adjustment of the PID controller coefficients.