PID Regulator Research Articles

Cross Regulation Reduced Optimal Multivariable Controller Design for Single Inductor DC-DC Converters

Single Inductor (SI) converters with the advantage of using one inductor for any number of inputs/outputs find wide applications in portable electronic gadgets and electrical vehicles. SI converters can be used in Single Input Multiple Output (SIMO) and Multiple Input Multiple Output (MIMO) configurations but they need controllers to achieve good transient and steady state responses, to improve the stability against load and line disturbances and to reduce cross regulation. Cross regulation is the change in an output voltage due to change in the load current at another output and it is an added constraint in SI converters. In this paper, Single Input Dual Output (SIDO) and Dual Input Dual Output (DIDO) converters with applications capable of handling high load current working in Continuous Conduction Mode (CCM) of operation are taken under study. Conventional multivariable PID and optimal Linear Quadratic Regulator (LQR) controllers are developed and their performances are compared for the above configurations to meet the desired objectives. Generalized mathematical models for SIMO and MIMO are developed and a Genetic Algorithm (GA) is used to find the parameters of a multivariable PID controller and the weighting matrices of optimal LQR where the objective function includes cross regulation as a constraint. The simulated responses reveal that LQR controller performs well for both the systems over multivariable PID controller and they are validated by hardware prototype model with the help of DT9834® Data Acquisition Module (DAQ). The methodologies used here generate a fresh dimension for the case of such converters in practical applications.

Analysis, Mathematical Model and Simulation Tests of the Unmanned Aerial Vehicle Control System

The subject of this paper is to analyze, create a dynamic mathematical model and, on this basis, conduct simulation tests of the control system used in unmanned aerial vehicles. The key objective of the work is to develop a mathematical model of a control system based on the conducted studies of P, PI and PID regulators. The summary of this article are selected simulation tests of the proposed unmanned aerial vehicle (UAV) control system based on the analysis performed, the mathematical model developed for the dynamic control system and based on them, drawing practical conclusions.

Genetic Algorithm and Simulation for Selecting PID-Controllers Parameters in the Walking Robot

Walking robot dynamic stabilization is a growing field of research as such robots are being constructed for various applications in human environment. The dynamic stabilization systems for such robots are often highly non-linear with the additional demand for rapid change of model mass parameters to meet the design requirements. The article centres round the problem of mechanical modelling of a walking robot and identifying the robot dynamic stabilization system parameters using the genetic algorithm approach. The stabilization system supposed in the paper is based on inverted pendulum model with paired gyroscopic units with limited kinetic momenta, that shapes out the optimization problem. The proposed control system includes a cascade of two PID regulators, the optimal parameters of which are identified using the genetic algorithm approach. The authors give the short description of the approach and suggest the fitness function suitable for this application. The computational experiment is then conducted, and the optimal parameters set is obtained. The disadvantages of the genetic algorithm solver in Simulink environment are pointed out with the approaches to their partial elimination.

Adaptive Wind Turbine PID Controller Tuner Algorithm with Elements of Artificial Intelligence

The vast majority of automatic control systems (ACS) currently in operation use the PID algorithm. However, there are still many problems in the adjustment of PID regulators parameters that provide the required quality of control. In this connection, it is proposed to use for this task an algorithm with two reference models for self-tuning of automatic control systems, in which continuous processes that accumulate information about the dynamics of the controlled object are implemented, it is used for determining optimal values of tunable parameters, assessing the performance of ACS in the course of mathematical modeling and automatic change of the ACS adjustment factors, in the case of approaching the performance of ACS to the limits of admissible values of the criterions quality, defined in the specifications.

Use embedded DSP blocks to implement a PID regulator

The article explores the possibility of using digital signal processing units DSP48xx embedded in the Xilinx devices of FPGA devices of Xilinx to implement PID regulators. Examples of its practical implementation are provided.

Development of Temperature Process Control Method Using Smith Predictor

The analysis of a problem of development of control systems for objects with big time delay is carried out in this work. For such objects it is difficult to provide high-quality control, because the control is carried on the last status of object’s output. The main setup methods of PID regulators have been examined. Based on this analysis the technique of complete synthesis of the regulator of higher level is given in order to regulate building’s heating system. This work offers a new method of object’s control with distributed delay. As the test bed for the offered structure of control the valve of hot water supply in a heat-node is used. Using the test bed the stability of the system with time delay have been studied, which is controlled by the PID-regulator assisted by Smith Predictor used to compensate the dead time.

Open-loop-based Island-mode Voltage Control Method for Single-phase Grid-tied Inverter with Minimized LC Filter

This paper proposes an island-mode voltage control method by using an open-loop control applying a high-gain disturbance observer (DOB) for a single-phase inverter with a low capacitance output filter. The output voltage is distorted with the low capacitance by the conventional method which consists of a PID regulator for an automatic voltage regulator (AVR) and a PI regulator for an automatic current regulator (ACR). In order to compensate the output voltage distortion, the high-gain DOB for the output voltage is applied in the open-loop-based voltage control. DOB is implemented into a field-programmable gate array (FPGA) with high-speed sampling. In the LC filter of a 1-kW prototype, the impedance of the inductor is minimized to 1.0% of the normalized inverter impedance, whereas the admittance of the capacitor is reduced to 0.25% of the normalized inverter admittance. By the proposed method, the inverter output voltage total harmonic distortion (THD) is reduced by 82.4% even with the diode rectifier load compared to the conventional voltage control, whereas the constant output voltage is achieved regardless of any conditions of load.

Sertain Problematic Aspects of Fuzzy PID Regulation

In recent years in view of the fact that the interest in the technologies of artificial intelligence in control systems by technical objects and technological processes are aroused, that fuzzy controllers find use more often. The given regulators carry out the process of the development of controlling actions on the basis of fuzzy logic, the application of which provides the design of control systems capable of functioning in conditions of incompleteness and fuzziness of knowledge about the dynamics of the control object. Fuzzy regulators have opened a new direction in the area of automatic control and according to many experts have a promising future. The given paper analyzes the dynamic characteristics and algorithmic singularities of fuzzy PID-regulation systems, compares the quality of clear and fuzzy regulation. The conducted analysis allows to state the absence of any real advantages of fuzzy regulators in comparison with classic clear regulators. Moreover, it is possible to distinguish a number of problematic aspects of fuzzy regulation methodology, important for practical automation:fuzzy control algorithms are much more complex than traditional clear regulation algorithms;the thesis about the advantages of fuzzy regulators seems to be reasonable, since each such regulator can be replaced by a more efficient and structurally less complex clear regulator;the thesis that on the basis of fuzzy approach it is possible to synthesize working systems of regulation without a priori knowledge and pre-project inspection of dynamic properties of objects of regulation is disputable.fuzzy approach is purely empirical and does not allow to solve the problems of stability, dynamic quality and robustness of the synthesized regulation systems at the theoretical level;fuzzy control algorithms are not applicable to complex dynamic objects. In particular, it concerns multi-connected objects of regulation and objects with delay;the methodology of fuzzy regulation does not allow to solve the important issues of optimization of regulation processes for engineering practice.

A Model Predictive Control for Renewable Energy Based AC Microgrids Without Any PID Regulators

This letter presents a novel model predictive control strategy without involving any proportional-integral-differential regulators for practical renewable energy based ac microgrids. The proposed method consists of a model predictive power control (MPPC) scheme and a model predictive voltage control (MPVC) scheme. By controlling the bidirectional buck-boost converters of the battery energy storage systems based on the MPPC algorithm, the fluctuating output from the renewable energy sources can be smoothed, while stable dc-bus voltages can be maintained as the inverters' inputs. Then, the parallel inverters are controlled by using a combination of the MPVC scheme and the droop method to ensure stable ac voltage output and proper power sharing. Compared with the traditional cascade control, the proposed method is simpler and shows better performance, which is validated in simulation on MATLAB/Simulink and on real-time laboratory platform.

Simulation of the emotional states using a biomimetic structure

This paper presents the control of biomimetic structures, using the PID regulation algorithm and the Arduino ATMEGA microcontroller. By controlling of the Chimpanzee Alive biomimetic structure, the following emotional states can be obtained: joy, sadness and anger. The biomimetic structure has 8 DC motors that control the following elements: eyebrows, eyelids, nose, mouth, eyes and neck. These emotional states are obtained by requiring reference to the position of the eyerbrows, eyelids and mouth. An expressive state of the human face is mainly duet of the effective position of the eyebrows, eyelids and mouth.

Automatic Tuner for PID Controllers with Elements of Artificial Intelligence

The vast majority of automatic control systems (ACS) currently in operation use the PID algorithm. However, there are still many problems in the adjustment of PID regulators parameters that provide the required quality of control. In this connection, it is proposed to use for this task an algorithm with two reference models for self-tuning of automatic control systems, in which continuous processes that accumulate information about the dynamics of the controlled object are implemented. It is used for determining optimal values of tunable parameters, assessing the performance of ACS in the course of mathematical modeling and automatic change of the ACS adjustment factors, in the case of approaching the performance of ACS to the limits of admissible values of the criterions quality, defined in the specifications.

FUZZY SUPERVISOR FOR PID CONTROLLER

Introduction: PID regulators are an important industrial automation tool. However, the traditional ways of their customization involve experiments with the plant, reducing the control system efficiency when the operating conditions change. To solve this problem, you have to use an adaptation loop which automatically changes the regulator parameters when the quality indicators deteriorate. Purpose: Developing a structure and an algorithm for a fuzzy supervisor of a PID controller in order to improve the operation quality in the context of uncontrolled changes in the plant parameters. Results: We propose two options for organizing a fuzzy supervisor. The first option involves continuous changing of the controller parameters based on the information about the current control error. The supervisor is trained offline with the help of a genetic algorithm. This approach makes the application universal, but the resulting structure is a black box. The second option is using transient process quality estimates; it can be used when the input signal periodically changes. The controller parameters are changed using fuzzy rules with clear semantics. It is shown that systems with a fuzzy supervisor can reduce the overshoot or static error which both can occur when the control object parameters change. The system operation was simulated using MatLab Simulink. Practical relevance: The use of PID controllers with fuzzy supervisors can be useful in the design of control systems for a wide range of dynamic plants.

Computational optimization and implementation of control system for mechatronic treadmill with body weight support system

The purpose of this paper is to present a novel mechatronic system for gait re-education which consists of a body weight support system (BWS system) and a treadmill. This publication covers mainly issues related to the design and optimization process of a control algorithm dedicated for the unloading system. The proposed control system is based on a fuzzy logic controller coupled with a PID regulator. The optimization of parameters for regulators has been conducted based on numerical simulations in which a hybrid optimization method combining a genetic algorithm with a gradient algorithm has been used. The developed control system has been tested experimentally.

ADAPTIVE NEURAL NETWORK PID CONTROLLER

The problem of constructing an adaptive PID controller based on the Hopfield neural network for a linear dynamic plant of the second order is considered. A description of the plant in the form of a discrete transfer function is used, the coefficients of which are determined with the help of a neural network that minimizes the discrepancy between the outputs of the plant and the model. The neural network processes the current and delayed input and output signals of the plant, forming an output for estimating the coefficients of the model. Another neural network determines the PID regulator coefficients at which the dynamics of the system approach the dynamics of the reference process. The calculation of weights and displacements of neurons in Hopfield networks used for identification and control is based on the construction of Lyapunov functions. The proposed methodology can be used to organize adaptive control of a wide class of linear dynamic systems with variable parameters. The results of the simulation in the article show the effectiveness of the proposed method.

Practical Design of RC Approximants of Constant Phase Elements and Their Implementation in Fractional-Order PID Regulators Using CMOS Voltage Differencing Current Conveyors

This paper brings a practical and straightforward view on the design of circuit elements described by fractional-order dynamics known as the constant phase element (CPE) and their implementation in a novel structure of a PIαDβ (or PIλDμ in some literature) regulator based on fabricated CMOS voltage differencing current conveyors. Comparison of presented topology with known solutions indicates significant improvements regarding overall simplification, simpler electronic controllability of time constants, and having all passive elements in grounded form. Step-by-step design of the CPE as well as the PIαDβ regulator is supported by experiments with active devices fabricated using the C07 I2T100 0.7 μm CMOS process (ON Semiconductor). Laboratory tests in frequency and time domain confirm the correct operation of the designed application and the accuracy of the derived results in comparison with the theoretical expectations.

AUTOMATIC CONTROL FORMATION OF THE ULTRASONIC OSCILLATIONS INTENSITY IN THE FLOTATION PROCESS

Purpose. The method development of adaptive control of the high-energy ultrasound intensity and frequency, which are formed by means of an ultrasonic phased array. Methodology. The problem of automatic control automation for the ultrasonic oscillations intensity in flotation process using the PID controller, Lyapunov's and gradient methods based on the adaptive control system with a reference model, self-tuning regulator based on the Kaczmarz projection iteration method is considered. The method of adaptive control of the high-energy ultrasound intensity at a given point in space, which is generated by an ultrasonic phased array based on the successive orthogonal projection of the approximation on a hyperplane is developed. Findings. The computer simulation results of the ultrasonic exposure on the pulp flow using adaptive and PID regulators with a given intensity and time of the transient process with a linearly increasing pulp flow rate are shown. The developed method is implemented in software and allows to maintain the desired intensity of ultrasound exposure at a given point of flotation machine space with high accuracy. Originality of the work lies in the fact that a method of adaptive control of the intensity of high-energy ultrasound at a given point in space, formed by using an ultrasonic phased array based on a sequential orthogonal design of the approximation on the hyperplane, has been developed, with error not exceeding 1.2%. Рractical value consists in the development of algorithms and programs for adaptive control of the parameters of the gas phase of the pulp in the process of flotation.

Digital PID controller for pneumatic and hydraulic systems

In the development of technological systems with pneumatic or hydraulic drive, the use of automated means for their control is required. At present, automated control tools built with the help of logic controllers are widely used. The logical controller allows to solve a wide variety of tasks with minimal costs, both in terms of cost and time spent for developing the system. So the logic controller ensures the speed of systems with pneumatic or hydraulic drive up to 1 ms or less. With the use of digital automated controls, questions related to the synthesis of PID regulators and the stability of systems with pneumatic / hydraulic drive in the time domain arise. The purpose of this work was the creation and practical implementation of a digital PID controller for controlling the pneumatic / hydraulic system to provide practical recommendations for its use in engineering. The article presents a block diagram of analog and digital control systems with a proportional pneumatic distributor. The implementation of analog and digital PID-controller and optimization of its parameters by an integral criterion is presented. Comparison of analog and digital systems with the PID controller introduced into their composition is made. The quality of these systems is suggested to be estimated in the time domain by the time of the transient process and the maximum dynamic error. Practical recommendations for determining the sampling time of digital systems with a PID controller are given. An example of the developed digital automatic control system for tracking pneumatic drive is shown, its structural diagram, the general view of the control device with the logic controller and the graphic operator interface, which makes it easy to configure the automated control tool and monitor its state. The scientific novelty of the results presented in the article was that the task of investigating the dynamics of a pneumatic / hydraulic distributor with an electric control in the time domain was solved using a mathematical model that included a digital PID controller and a comparison of the results of modeling a digital system with analogue was made, and practical recommendations for determining the sampling time were given.

Gray Wolf optimization method for automatic ventilation systems of clean accessories

The manufacturing processes complication leads to cost increasing of equipment service and maintenance costs. An important role in overcoming these factors is played by modern automatic control systems, regulators optimization and adaptation of control systems to changing conditions. Today, the actual problem remains the adjustment and optimization of automatic control systems, especially complex structures.The article researches the population optimization algorithm "Gray wolf" as applied to the search for optimal PID-controller settings. A cascade automatic control system with two PID regulators optimized for a minimum of integral IAE, ISE quality criteria, as well as control time is considered. The advantage of the method under investigation is shown in a comparing with the Hook-Jeeves zero-order optimization method. The mathematical modeling of the automatic control system of air temperature in a clean room with the “Grey wolf” optimization method is performed. Attention is focused on the convenience of using the method, since it does not require an accurate setting of the initial parameters of the regulators. This eliminates the need for an a priori knowledge of the customizable system dynamics by the user. The commissioning of control parameters optimizing systems will help to increase the efficiency of the equipment in conditions of variable operating modes. The recommended area of the method used is the complex structures of automatic control systems, where the search for optimal settings by classical methods is difficult or does not exist.

Selection of settings of PID regulators for quadrocopter with the use of optimization methods in the Wolfram MATHEMATICA software

The article presents the method of modeling the dynamics of a quadrocopter and presents a method for the selection of PID regulators. The quadrocopter's dynamics were derived based on the Lagrange equations of the second type. In the form of graphs, the simulation results were presented for the settings selected using the optimization method using the Wolfram Mathematica package

Реєстрація параметрів автоматизованого програмно-апаратного комплексу медичного призначення

The main modules of the control unit of the automated software and hardware complex for carrying out medical diagnostic procedures, namely interval normobaric hypoxic training are considered. There are described methods for collecting and processing data in real time during training with measu-ring instruments for determining the composition of a gas hypoxic mixture (an oxygen sensor and a carbon dioxide sensor) and the state of the respiratory system (the air volume flow sensor) and hemodyna-mics (pulse oximeter) of the human. The following practical and scientific results have been obtained. A method for maintaining a given concentration of the respiratory mixture and controlling the compressor using a modified PID regulator is implemented. Taking into account the special features of the subject domain, the differential component of the PID regulator is defined as a function of the minute volume of breathing.The existing algorithms of frequency filtration are studied and comparison of different types of software filters is made. The possibility of their use in the system of hypoxic training is analyzed. For the subsystem of pulsoximetry the Butterworth 2nd order program filter has been selected. So it does not require significant computing resources and uses signal values only up to the last two iterations.The system of hardware timers and interrupts has been used. The functional purpose and modes of operation of which can be programmed to provide real-time work and solve problems of varying complexity and with different priorities. The created complex with the examined software was tested and recommended by the Ministry of Health to use in medical and sports institutions.