Digital Proportional-integral-derivative Research Articles

Low Cost PID Controller for Student Digital Control Laboratory Based on Arduino or STM32 Modules

In the teaching process, it is important that students do not carry out exercises only by computer simulations, but also that they carry out research in real time. In times of distance learning during the COVID-19 pandemic, it would be necessary to find a solution so that the students can perform such exercises individually at home. Therefore, it has become necessary to develop cheap and simple modules of digital controllers along with analog objects with adjustable order and time constants. This paper describes a low-cost proportional–integral–derivative (PID) controller for teaching students control techniques and analog control objects in real time. The PID controller is based on the cheap and widely available microcontroller modules Arduino or STM32. The advantage of this solution is that the algorithm of the digital PID controller is calculated every constant period of time. Both the solutions presented in the paper have been successfully tested by students in practice during remote learning during the COVID-19 pandemic.

A Compound Control Algorithm for Height Following of Laser Cutting Head

A composite algorithm combined with fuzzy proportional-integral-derivative (PID) control and acceleration closed-loop control is proposed to address the defects of slow response speed, strong oscillation, and long adjustment time of the current height following control system for a laser cutting head. The fuzzy PID control can satisfy the different requirements for the control parameters in each stage of the height follow-up adjustment process for the laser cutting head via the adaptive adjustment of the PID parameters. Accordingly, the height following error can be attenuated to the set positioning accuracy range. The acceleration closed-loop control can improve the acceleration and deceleration performance of the system through the positive and negative feedback regulation of the motion acceleration of the laser cutting head to achieve high-speed servo. An experimental bench of height follow-up control system for laser fabrication is developed to verify the effectiveness of the algorithm. Through experimental verification, compared with the conventional digital PID incremental algorithm, this composite control algorithm can accelerate the response speed of height follow-up control system for the laser cutting head, improve the dynamic performance of the system, and realize fast and precise servo control of laser cutting head height under the premise of ensuring positioning accuracy. The proposed algorithm is expected to lay a foundation for the development of the new intelligent laser processing system.

Control of the temperature in the hot liquid tank by using a digital PID controller considering the random errors of the thermometer indications

A digital PID (Proportional-Integral-Derivative) controller to maintain a constant hot water temperature in the tank was proposed. The thermometer's indications are subject to random errors. The water temperature is determined by solving the inverse problem for a thermometer in the form of a solid cylinder inside which the temperature is measured. The water temperature is determined using a first or second-order thermometer model. The use of differential quotients to calculate the first or second derivative after time causes the controller to be unstable. To increase the stability of the PID system operation, digital filters were used to eliminate the influence of random disturbances of the temperature indicated by the thermometer. This ensures stable, much faster, and more accurate operation of the controller. The operation of the PID controller with the proposed technique for determining the medium temperature was illustrated by using the example of an electric storage heater in which the water temperature should be equal to the pre-set temperature. The novelty of the presented PID control system is the determination of the fluid temperature based on the solution of the inverse problem of heat conduction formulated for a thermometer. As a result, the speed and accuracy of the PID controller are significantly improved.

Magnetic tweezers with magnetic flux density feedback control.

In this work, we present a single-pole magnetic tweezers (MT) device designed for integration with substrate deformation tracking microscopy and/or traction force microscopy experiments intended to explore extracellular matrix rheology and human epidermal keratinocyte mechanobiology. Assembled from commercially available off-the-shelf electronics hardware and software, the MT device is amenable to replication in the basic biology laboratory. In contrast to conventional solenoid current-controlled MT devices, operation of this instrument is based on real-time feedback control of the magnetic flux density emanating from the blunt end of the needle core using a cascade control scheme and a digital proportional-integral-derivative (PID) controller. Algorithms that compensate for a spatially non-uniform remnant magnetization of the needle core that develops during actuation are implemented into the feedback control scheme. Through optimization of PID gain scheduling, the MT device exhibits magnetization and demagnetization response times of less than 100ms without overshoot over a wide range of magnetic flux density setpoints. Compared to current-based control, magnetic flux density-based control allows for more accurate and precise magnetic actuation forces by compensating for temperature increases within the needle core due to heat generated by the applied solenoid currents. Near field calibrations validate the ability of the MT device to actuate 4.5 μm-diameter superparamagnetic beads with forces up to 25 nN with maximum relative uncertainties of ±30% for beads positioned between 2.5 and 40 µm from the needle tip.

DIGITAL CONTROL OF A CLOSED LOOP BUCK CONVERTER

The primary focus for the R&D in this area so far has been to figure out the best approach for evaluating and designing the DC-DC converter and perhaps the most appropriate control technique is being applied in different DC-DC converter circuits. Depending on power handling capacity as well as high-frequency switching, certain switching devices are chosen. This paper discusses the deployment of the digital PID controllers in the DC-DC converters. In an attempt to get a quicker response, voltage mode control has been used. Digital controllers started replacing traditional analog controllers more and more. Better immunity to changes in the environment which includes temperature and degradation of components, improved versatility by modifying the software, increasing advanced control methods, and decreased number of the components are the key benefits of the digital control against the analog control. A structured and concise strategy for designing a digitally operated close-loop Dc / Dc buck converter is discussed in this paper beginning with the Buck converter and giving the set of certain performance specification, implementations of the digital Proportional-IntegralDerivative(PID) controller is made. It addresses in depth all the appropriate DSP hardware and/or software methods and approaches needed to implement a controller. In order to illustrate the efficacy of the model, the dynamic response as well as the steady-state performance of controller is provided. The experimental outcomes fit well with the model of simulation. During the implementations of Switch Mode Power Supply (SMPS), application of dsPIC provides new perspectives towards affordable and versatile approaches of digital control.

Real-time feedback control system for ADITYA-U horizontal plasma position stabilisation

The ADITYA-U tokamak (R0 = 0.75 m, a = 0.25 m) is designed to shape plasma column in both single and double null diverter configurations. It is quite well known that sustaining a shaped plasma in tokamak requires very good plasma column position control, both horizontal and vertical. An FPGA-based proportional–integral–derivative (PID) control system has been designed and operated to achieve horizontal plasma position control in ADITYA-U tokamak. The complete system has been rigorously tested with sample signals before implementing to the ADITYA-U plasma discharges. The control system is integrated and time-synchronized with the plasma discharge operation of ADITYA –U. Furthermore, the system has been trained to take appropriate actions during the disruption or plasma failure in the tokamak operation. Detailed experimental results have been obtained by the operation of the digital PID controller. The complete design, installation, operation, tuning of the system along with all the relevant testing and operating experience of the digital PID controller for real-time horizontal plasma position control is presented in the paper.

Design of digital pulse width modulator architecture with digital PID controller for DC-DC converter using FPGA

A digital pulse width modulation architecture (DPWM) along with digital proportional integral derivative (PID) controller to control the DC-DC converter is presented in this paper. Difference between the actual output voltage and the reference voltage is calculated as error value. The look up table is created for PID controller to store the duty cycle ratio and the error value of power converters. Multipliers used in conventional algorithms are replaced by look up tables in the proposed work that enable the compact and low power implementation of digital controllers. DPWM architecture is developed with gray logic against the binary logic used in traditional DPWM architectures. Usage of gray counter also leads to low power consumption in the DPWM architecture. The proposed architecture is designed using Verilog hardware language and realized using field programmable gate array. PWM signals with varying duty cycle percentage can be derived from the proposed architecture. The generated PWM signal can control the switching condition of power converter to regulate the output voltage. Duty cycle percentage ranging from 16 to 96% can be developed with the proposed architecture. Simulation and experimental results of the architecture validate the proposed architecture. PWM signal with maximum operating frequency of 59.49 MHz and 60.22 MHz for SPARTAN 3A and SPARTAN 3E respectively can be generated with the proposed architecture.

Design of DC-DC Buck Converter for Smartphone Applications Based on FPGA Digital Voltage Controller

This paper presents an enhancement of the output performance of a linear buck converter system for the mobile (smartphone) devices using an adaptive digital Proportional–Integral–Derivative (PID) controller with off-line swarm optimization algorithm. The work focuses on improving the use of using single-input single-output (SISO) digital Field Programmable Gate Array (FPGA)-PID to control the linear buck converter system. The goal of the proposed adaptive SISO-FPGA-PID voltage-tracking controller is to rapidly and precisely identify the optimal voltage control action (optimal on-off duration time) that is used to control the buck converter output voltage level in order to avoid the troubleshooting hardware problem issues on mobile devices. The Particle Swarm Optimization (PSO) algorithms are used to find and tune the three weights of the SISO-FPGA-PID controller. The numerical simulation results and the experimental work using Spartan-3E xc3s500e-4fg320 board with Verilog hardware description language (HDL) show that the proposed controller is more accurate in terms of voltage error and the number of function evolutions are of high reduction. As well as to generate a smooth voltage control response without voltage oscillation in the output by investigating under mobile applications variations such as using Bluetooth, WI-FI, and CPU operating voltage when these results are compared with other controllers.

An Adaptive Digital Neural Network-Like-PID Control Law Design for Fuel Cell System Based on FPGA Technique

This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH2) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fuel cell system and to achieve the stability of the desired output voltage of fuel cell. The numerical simulation results (MATLAB) package along with the schematic design experimental work using Spartan-3E xc3s500e-4fg320 board with the Xilinx development tool Integrated Software Environment (ISE) version 14.7 and using Verilog hardware description language for design testing are illustrated the performance enhancement of the proposed an adaptive intelligent FPGA-PID-NN controller in terms of error voltage reduction and generating optimal value of the hydrogen partial pressure action (PH2) without oscillation in the output and no saturation state when these results are compared with other controllers.

Influence of the Thermometer Inertia on the Quality of Temperature Control in a Hot Liquid Tank Heated with Electric Energy

This paper presents the medium temperature monitoring system based on digital proportional–integral–derivative (PID) control. For industrial thermometers with a complex structure used for measuring the temperature of the fluid under high pressure, the accuracy of the first-order model is inadequate. A second-order differential equation was applied to describe a dynamic response of a temperature sensor placed in a heavy thermowell (industrial thermometer). The quality of the water temperature control system in the tank was assessed when measuring the water temperature with a jacketed thermocouple and a thermometer in an industrial casing. A thermometer of a new design with a small time constant was also used to measure temperature. The quality of water temperature control in the hot water storage tank was evaluated using a classic industrial thermometer and a new design thermometer. In both cases, there was a K-type sheathed thermocouple inside the thermowell. Reductions in the time constant of the new thermometer are achieved by means of a steel casing with a small diameter hole inside which the thermocouple is precisely fitted. The time constants of the thermometers were determined experimentally with a jump in water temperature. A digital controller was designed to maintain the preset temperature in an electrically heated hot water tank. The function of the regulator was to adjust the power of the electrical heater to maintain a constant temperature of the liquid in the tank.

Digital PID Control Law Design for Fuel Cell Model Based on FPGA Emulator System

This paper proposes an off-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. The aim of this research is to obtain the best hydrogen partial pressure (PH2) value using FPGA emulator to design and implement a digital PID controller that track the fuel cell output voltage during a variable load current applied. The off-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID controller parameters that improve the dynamic behavior of the closed loop digital control fuel cell system and to achieve the stability of the desired output voltage of fuel cell. The numerical simulation results (MATLAB) package and FPGA emulator experimental work show the performance of the proposed FPGA-PID controller in terms of voltage error reduction and generating optimal value of the (PH2) control action without oscillation in the output and no saturation state when these results are compared with other control methodology.

Tuning of Digital PID Controllers Using Particle Swarm Optimization Algorithm for a CAN-Based DC Motor Subject to Stochastic Delays

In this article, we investigate the tuning problem of digital proportional-integral-derivative (PID) parameters for a dc motor controlled via the controller area network (CAN). First, the model of the dc motor is presented with its parameters being identified with experimental data. By studying the CAN network characteristics, we obtain the CAN-induced delays related to the load rate and the priorities. Then, considering the system model, the network properties, and the digital PID controller, the tuning problem of PID parameters for the CAN-based dc motor is transformed into a design problem of a static-output-feedback controller for a time-delayed system. To solve this problem, particle swarm optimization algorithm and linear-quadratic-regulator method are adopted by incorporating the sufficient condition of time-varying delay system. Finally, the effectiveness of the proposed PID tuning strategy is validated by experimental results.

Robust AVR design for the synchronous generator

Conventional automatic voltage regulator (AVR) schemes use thyristor-based rectifiers in which the generator field voltage is varied by changing the thyristor's firing angle. The conventional AVR has been known to cause voltage sags and extended under-voltages, especially under fault conditions. Several control schemes such as digital proportional–integral–derivative (PID) controllers, adaptive control schemes, and intelligent control schemes have been proposed in the literature. However, these schemes increase the complexity of the system. This work proposes a DC−DC converter-based AVR as an alternative to the rectifier-controlled AVR. The DC−DC converter is arranged in step-down (buck-type) configuration. The DC−DC converter uses metal-oxide-semiconductor field-effect transistor/insulated-gate bipolar transistors and has a faster response than the thyristors, thereby resulting in faster and precise control of the generator field voltage. The DC−DC converter is connected to the field circuit of the generator, and the terminal voltage of the generator is regulated by a PI controller by varying the converter duty cycle to control the generator field voltage. Simulation and experimental investigation has shown that the proposed scheme exhibits a better transient response and is robust under DC input voltage variation and generator load changes.

Design of Digital PID Controller Based on FPGA

PID controller has been widely used in many different areas such as power systems, drives control, automotive mechatronics, aerospace, process control, and robotics. Recently, FPGA (field programmable gate array) has become an alternative solution for the realization of digital control algorithm systems. In this paper FPGA-based incremental PID (Proportional, Integral, Derivative) controller is designed and simulated. After the analysis of PID control algorithm, VerilogHDL language is used to design the software programs. Simulation results show the effectiveness and feasibility of the proposed method.

Self-Tuning Robust Fuzzy Controller Design Based on Multi-Objective Particle Swarm Optimization Adaptation Mechanism

In this paper, an adaptive fuzzy controller design methodology via multi-objective particle swarm optimization (MOPSO) based on robust stability criterion is proposed. The plant to be controlled is modeled from its input–output experimental data considering a Takagi–Sugeno (TS) fuzzy nonlinear autoregressive with exogenous input model, by using the fuzzy C-means clustering algorithm (antecedent parameters estimation) and the weighted recursive least squares (WRLS) algorithm (consequent parameters estimation). An adaptation mechanism as MOPSO problem for online tuning of a fuzzy model based digital proportional-integral-derivative (PID) controller parameters, based on the gain and phase margins specifications, is formulated. Experimental results for adaptive fuzzy digital PID control of a thermal plant with time-varying delay are presented to illustrate the efficiency and applicability of the proposed methodology.

Design of a decoupled AP1000 reactor core control system using digital proportional–integral–derivative (PID) control based on a quasi-diagonal recurrent neural network (QDRNN)

The control system of the AP1000 reactor core uses the mechanical shim (MSHIM) strategy, which includes a power control subsystem and an axial power distribution control subsystem. To address the strong coupling between the two subsystems, an interlock between the two subsystems is used, which can only alleviate but not eliminate the coupling. Therefore, sometimes the axial offset (AO) cannot be controlled tightly, and the flexibility of load-following operation is limited. Thus, the decoupling of the original AP1000 reactor core control system is the focus of this paper. First, a two-node disperse dynamic model is established for the AP1000 reactor core to use PID control. Then, a digital PID control system based on a quasi-diagonal recurrent neural network (QDRNN) is designed to decouple the original system. Finally, the decoupling of the control system is verified by the step signal and load-following condition. The results show that the designed control system can decouple the original system as expected and the AO can be controlled much more tightly. Moreover, the flexibility of the load following is increased.

Dependable Control for Wireless Distributed Control Systems

The use of wireless communications for real-time control applications poses several problems related to the comparatively low reliability of the communication channels. This paper is concerned with adaptive and predictive application-level strategies for ameliorating the effects of packet losses and burst errors in industrial sampled-data Distributed Control Systems (DCSs), which are implemented via one or more wireless and/or wired links, possibly spanning multiple hops. The paper describes an adaptive compensator that reconstructs the best estimates (in a least squares sense) of a sequence of one or more missing sensor node data packets in the controller node. At each sample time, the controller node calculates the current control, and a prediction of future controls to apply over a short time horizon; these controls are forwarded to the actuator node every sample time step. A simple design method for a digital Proportional Integral Derivative (PID)-like adaptive controller is also described for use in the controller node. Together these mechanisms give robustness to packet losses around the control loop; in addition, the majority of the computational overhead resides in the controller node. An implementation of the proposed techniques is applied to a case study using a Hardware in the Loop (HIL) test facility, and favorable results (in terms of both performance and computational overheads) are found when compared to an existing robust control method for a DCS experiencing artificially induced burst errors.

Optimized Digital Proportional Integral Derivative Controller for Heating and Cooling Injection Molding System

Proportional integral derivative (PID) control is one of the conventional control strategies. Industrial PID control has many options, tools, and parameters for dealing with the wide spectrum of difficulties and opportunities in manufacturing plants. It has a simple control structure that is easy to understand and relatively easy to tune. Injection mold is warming up to the idea of cycling the tool surface temperature during the molding cycle rather than keeping it constant. This “heating and cooling” process has rapidly gained popularity abroad. However, it has discovered that raising the mold wall temperature above the resin’s glass-transition or crystalline melting temperature during the filling stage is followed by rapid cooling and improved product performance in applications from automotive to packaging to optics. In previous studies, optimization methods were mainly selected on the basis of the subjective experience. Appropriate techniques are necessary to optimize the cooling channels for the injection mold. In this study, a digital signal processor (DSP)-based PID control system is applied to injection molding machines. The main aim of this study is to optimize the control of the proposed structure, including a digital PID control method with a DSP chip in the injection molding machine.

Digital current control of a three‐phase four‐leg voltage source inverter by using p – q – r theory

In this study, balanced/unbalanced linear/non-linear current control in three-phase four-leg voltage source inverter (VSI) is carried out by using modified p - q - r method instead of the classical p - q - r method, digital proportional integral derivative (PID) control rule and three-dimensional (3D) space vector pulse width modulation (3D SVPWM). For this purpose, three-phase four-leg power inverter and PWM signal generation circuits are designed and modelled separately. Even if the power source voltage is unsymmetrical, the proposed modified p - q - r method leads to measurement and to generating the instantaneous harmonic and reactive components of load current accurately. The performance of the classical p - q - r theory under non-ideal mains voltages is improved and the accuracy of the proposed modified p - q - r theory is demonstrated both through simulation and real-time application. Each phase of the three-phase four-leg VSI modelled directly in abc reference frame is decoupled from each other This simplifies the digital PID controller design significantly. Modelling of the whole system, modified p - q - r measurement and digital PID design steps are given in detail. Real-time experimental results for the designed three-phase four-leg VSI in stand-alone mode are compared with the simulation results.

Application of SDGM to Digital PID and Performance Comparison with Analog PID Controller

Now -a-days PID (proportional-integral-derivative) controller is used in every type of small or large industries. For this the digital PID controller is so popular. But it is necessary to design and tune the PID controller in a proper method for applying the plant. The paper represents a method of tuning a digital proportional-integral-derivative (PID) controller. The name of the method is Steepest Gradient Descent Method (SDGM). It is an iterative method. The SDGM method is very simple, easy to use and each iteration is very fast. It is also a guaranteed method to find the minima through numerous times of iterations as long as it exists. By applying this optimization method PID controller is tuned both of digital and analog process. In the paper by applying the method of some plant the comparison result of analog and digital are shown. From the comparison it is found that the digital scheme is preferable than analog scheme. Index Terms—PID controller, SDGM. I. INTRODUCTION The fi rst controllers with proportional, integral, and derivative (PID) feedback control action became commercially available during the 1930s. The 1940s saw widespread acceptance in industry of pneumatic PID controllers, and their electronic counterparts entered the market in the 1950s. Digital hardware has been routinely used since the 1980s with significant impact on process control. Even several decades after three-mode controllers were introduced; the vast majority of controllers used in the chemical process industry are based on PI/PID models (1). The popularity of these controllers has led to research on tuning methods, resulting in hundreds of publications on this topic. Ziegler-Nichols tuning relations and Cohen-Coon tuning rules are among the earliest published methods. Tuning relations based on error criteria are more recent model-based tuning rules, which offer improvements over earlier tuning methods. Tuning rules also exist for unstable processes as well as for tuning in the presence of plant model mismatch (2). Despite the numerous approaches available for controller tuning, surveys indicate that poorly tuned control loops are abundant in industry. In general, the gain scheduling of the PID controllers is an optimization problem. The method of steepest descent (SDGM) is also known as The Gradient Descent, which is basically an optimization algorithm to find the local minimum of a function. By applying the SDGM to the PID controller, the controller is tuned and applied to some conventional plant then the digital and analog results are compared to the paper.