PID Parameters Research Articles

Pressure Based Control For A Variable Speed Diesel Engine Driven Pump Controller

Chemical cleaning is a process that utilizes chemical as a cleaning medium to remove unwanted contaminants. The chemical cleaning process may involve with the use of pump to circulate the chemical during cleaning process. The pump for the cleaning process can be driven by electrical or internal combustion engine. This paper presents the development of a variable speed diesel engine driven pump controller for chemical cleaning application. The controller utilize proportional control method as the control scheme. The variable speed diesel engine driven pump system includes a diesel engine coupled with centifugal pump, a controller, pressure sensor, and battery powerpacks. All the components are mounted on a skid platform for the ease of use as a system. Proportional control method were used in order to get the critical gain parameter to compute PID parameter gains using Ziegler Nichols tuning method

Feed Pump Pressure Control System Against Water Turbidity In Depth Filtration Process

This research discusses the feed pump pressure regulation system on water turbidity in the Depth Filtration process. The water purification system applies the depth filtration method by adjusting the speed of the feed pump based on the value of water turbidity. The sensors used are pressure transmitters which are used to measure the filter inlet and outlet pressures, as well as turbidity and conductivity sensors. To adjust the turbidity value of the water according to the clean water standard, the speed of the feed pump is controlled so that the water coming out of the filter outlet is in accordance with the clean water standard. In this system, PID control is applied using ciancone marlin tuning with PID parameters are Kc = 0.214779698, Ti = 0.39875, Td = 0.0625, with these parameters to reach the set point differential pressure requires an average rise time of 9.5 seconds, steady state 18.6 seconds, Settling time 11.8 seconds and over shoot = 2.55% and the value of water turbidity is 16.36 NTU.

Intelligent Control System in Desert Areas Based on Photovoltaic Microgrid Power Supply

With the advent of the global energy crisis, the use of sustainable green energy has become more and more widespread and the utilization rate of photovoltaic industry in high-altitude desert areas is getting higher and higher. This article mainly studies the intelligent control system in desert area based on photovoltaic microgrid power supply. The system uses shielded twisted pair to transmit signals, and electrostatic interference and electromagnetic induction interference are effectively suppressed. After ensuring that the encoder feedback is correct and the motor movement direction is consistent with the command direction and the safety of the movement stroke, the PID parameters of the motor are tuned in PAMCturningpro. For the performance test of this system, the design and implementation of the test plan should be carried out according to the concurrent support target and response time target proposed in the performance analysis of the system. Concurrent users use the LoadRunner tool to create the customer test machine to simulate the concurrent access and operation of the system. In each iteration process, the test results are recorded in the same way as the benchmark test and finally the system can still achieve the expected performance when the actual concurrency reaches the limit of 5007. The results show that the intelligent control system in this paper has the advantages of low cost, convenient operation, perfect function, high precision, stable and reliable operation, etc. and has good practical value.

Analysis of Proportional Integral Derivative Controller Parameters for CSTR

Continuous Stirred Tank Reactor (CSTR) plays a vital role and presents a various scope of researchers in the field of control and chemical engineering which exhibits of highly nonlinear behaviour and has wide operating ranges. Different control methods have been implemented on CSTR to control these parameters. Tragically, in the realcase, the behaviour of the CSTR is very different from that expected ideal CSTR which leads to the outcomes of the wrong product. However, it is a challenging task for every engineer to control the CSTR.PID controller has been proposed for adjust enhanced PID parameters in a CSTR operation utilizing a weighted mix of target capacities. Streamlining of PID controller parameters is the key objective of concoction and biochemical businesses. PID controllers have restricted the working scope of procedures with effective nonlinearity. This work considers some issues in CSTR and presents the efforts of existing researchers and it comes into view as an essential new method to adjust the control parameters. This work plans to investigate the various techniques in CSTR along with its solutions and these schemes have been surveyed in this work. This survey presents the comparison of various methods for optimizing parameters in CSTR are employed and compared with certain parameters.

Multi-Objective Optimization Based Multi-Objective Controller Tuning Method with Robust Stabilization of Fractional Calculus CSTR

In Continuous Stirred Tank Reactor (CSTR) have Fractional order PID with the nominal order PID controller has been used to Multi-Criteria Decision Making (MCDM) and EMO (Evolutionary Multi-objective Optimization) by adjustment of control parameters like Hybrid methods in Multi objective optimization. But, this Fractional order PID with the nominal PID controller has maximum performance estimation. Proposed research work focused the Flower Pollination Algorithm based on Multi objective optimization with Genetic evaluation and Fractional order PID with the nominal PID controller is provides CSTR results. When a flower is displayed to maximum variations in this practical state, the Genetic evaluation has been used to identify the variations. The FPID (Flower Pollination Integral Derivative) is used for tuning the parameters of a Fractional order PID with the nominal PID controller for each region to improve the multi-criteria decision making. FPID also denoted as Flower Optimization Integral Derivative (FOID). The Genetic evaluation scheduler has been combined with multiple local linear Fractional order PID with the nominal PID controller to check the stability of loop for entire regions with various levels of temperatures. MATLAB results demonstrate that the feasibility of using the proposed Fractional order PID with the nominal PID controller compared than the existing PID controller, and it shows the FOID attained better results.

Optimization of Multiparameters for Increased Yields of Cytochrome B5 in Bioreactors.

The production of recombinant proteins is gaining increasing importance as the market requests high quality proteins for several applications. However, several process parameters affect both the growth of cells and product yields. This study uses high throughput systems and statistical methods to assess the influence of fermentation conditions in lab-scale bioreactors. Using this methodology, it was possible to find the best conditions to produce cytochrome b5 with recombinant cells of Escherichia coli. Using partial least squares, the height-to-diameter ratio of the bioreactor, aeration rate, and PID controller parameters were found to contribute significantly to the final biomass and cytochrome concentrations. Hence, we could use this information to fine-tune the process parameters, which increased cytochrome production and yield several-fold. Using aeration of 1 vvm, a bioreactor with a height-to-ratio of 2.4 and tuned PID parameters, a production of 72.72 mg/L of cytochrome b5 in the culture media, and a maximum of product to biomass yield of 24.97 mg/g could be achieved.

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.

Genetic Algorithm–Based Robust Controller for an Inverted Pendulum Using Model Order Reduction

Abstract Robust stabilization is an important characterization to get improved in the control system to optimize the performance of the desired system. Most of the controllers available suffer from problems such as difficulty in the tuning process, sluggishness in response time, quick and global convergence, etc. This paper considered proportional-integral optimized with genetic algorithm (GA-PID)controller on inverted pendulum for the control of the angle position. A MATLAB script for a GA was developed to obtain optimum PID parameters that would keep the pendulum angle at equilibrium (i.e., returns the pendulum to the desired point as quickly as possible) by minimizing an objective function (integral time absolute error [ITAE]). Furthermore, obtained outcomes confirm the performance of holding on the upright position from the downward direction such that the angle of the pendulum is manipulated to control the inverted position in its erect position in a rapid manner. In the experimental analysis, the developed GA-based PID controller is compared with the conventional PID controller to evaluate the performance of the inverted pendulum. The obtained results show that the GA-based PID controller confirms the enhanced performance indexes by holding minimum settling time and peak overshoot on comparing with the conventional PID controller.

A New Estimation Method of the PID Controller In Automatic Train Operation Systems

PID controller plays an important role in Automatic Train Operation systems. Many researches have been done on the PID parameters estimation. However, the traditional models simplified the characteristics of the trains in different speeds and operation modes. It was difficult to overcome the problems with different kinds of algorithms based on the traditional models, especially the accuracy requirement of the stopping distance. In this paper, a new model of the PID controller was proposed based on the practical train operation stages. And the different response time delay was considered besides of the transmission time delay. With this new model, an Improved Fruit Fly Optimization Algorithm was applied. The tracking performance were greatly improved both on running distance and real time. The simulation results showed a better performance than the traditional methods.

PID Parameter Tuning of Self-propelled Antiaircraft Gun Servo System Based on Differential Evolution Algorithm

PID Parameter Tuning of Self-propelled Antiaircraft Gun Servo System Based on Differential Evolution Algorithm

Automatic Voltage Regulator (AVR) Optimization Based on PID Using the Hybrid Grey Wolf Optimization - Genetic Algorithm (HGWGA) Method

In the generator set (genset), the voltage stability system is affected by the excitation system controlled by control circuit called AVR (Automatic Voltage Regulator). One of the important components in the AVR system is the algorithm of the controller. The application of the PID control method has been widely used in the design of AVR controllers. This study applies the GWO-GA (Grey Wolf Optimization - Genetic Algorithm) hybrid method on PID parameters setting. The best transient automatic voltage regulator (AVR) response results were obtained when using the hybrid genetic algorithm - grey wolf optimization (HGAGW) method with a fitness score of 4.3039, the Grey wolf optimization (GWO) method with a fitness score of 4.5059, and the genetic algorithm (GA) method with a fitness score of 6.0214.

Obstacle avoidance dynamic control of manipulator based on space operator algebra

The traditional manipulator obstacle avoidance dynamics control method ignores the acceleration constraints and speed constraints of the joint obstacle avoidance, and judges the equivalent moment of inertia inaccurately, which leads to large fluctuations in the driving torque of the manipulator motor, and high maximum driving torque and acceleration peaks. Therefore, a dynamic control method of manipulator avoiding obstacles based on space operator algebra is proposed. Using the space recursion method, according to the dynamic space operator algebra system, the manipulator dynamics model is obtained, PID parameters are adjusted, and the model is controlled by three-loop closed-loop PID control to obtain the joint torque under different obstacle avoidance states, and calculate the torque feedforward. The channel transfer function enables the moment to act on the joints of the manipulator to achieve the equivalent moment of inertia control target, to identify and finely control the moment parameters, and to plan the obstacle avoidance trajectory of the manipulator. A parallel manipulator was selected for comparison experiments. The results show that the design method reduces the motor torque ripple, the maximum driving torque, and the acceleration peak in the motion trajectory plane, so that the manipulator has better motion smoothness, reduces motor energy loss, and improves dynamic performance.

Identification of PID parameters for system-specific nutrient mixing control for ISE-based hydroponic nutrient management

Identification of PID parameters for system-specific nutrient mixing control for ISE-based hydroponic nutrient management

Parallel Distribution Compensation PID Based On Takagi-Sugeno Fuzzy Model Applied On DC Motor

Most of the industrial controllers in use today utilize PID controllers. In this paper, a new Parallel Distribution Compensator PID'S controller at several operating points, under parameters variations and external disturbances for the DC motor drive system. The parameters of PID's controllers were obtained at each operating point based on harmony search optimization. An effective cost function was used to perform the offline optimization. Three optimal PID's controllers were attained for each operating point individually. The fuzzy Takagi-Sugeno (TS) can be defined as the suitable PID controller for the corresponding operating point. The simulation results provided that Parallel Distribution Takagi-Sugeno PID's controller can be updated the suitable PID controller at several operating points so, it has good dynamic response with different types of disturbances (sudden load, variable load, and speed tracking) compared to the fixed optimal PID controller. Also, it can switch the better PID controller at a suitable time.

Research on Intelligent Blending Method of Matcha Based on Improved PID Control Algorithm

Most of the existing Matcha blending is done manually, which is inefficient and leads to uneven tea products. To solve this problem, this paper proposes an intelligent blending method based on improved PID control algorithm. In this paper, considering the various factors that affect the quality of tea, without affecting the quality of the product, taking the lowest cost of the enterprise as the constraint goal, the basic combination model is constructed by using PID control algorithm. Since the selection of PID parameters will affect the output of the model, this paper introduces particle swarm optimization algorithm to optimize the PID controller parameters globally, so that the PID controller can achieve the ideal control index, and finally determine the optimal combination of Matcha. The experimental results show that the method proposed in this paper can effectively realize the intelligent blending of Matcha, and maximize the cost of tea factory, effectively improve the income of Matcha products, which is conducive to the further development of tea companies.

Adaptive fuzzy PID cross coupled control for multi-axis motion system based on sliding mode disturbance observation.

Multi-axis motion system is widely applied in commercial industrial machines such as precision CNC machine tools, Robot manipulator and laser cutting machines, etc. Contour accuracy plays a major role for the multi-axis servo motion system. The contour machining accuracy is related to the synthesis of single-axis position accuracy and multi-axis linkage accuracy. Only improving the single-axis tracking performance cannot effectively guarantee the machining accuracy of multi-axis system. The primary objective of this study was to design a contour control method to improve single-axis tracking accuracy and multi-axis contour accuracy. A control strategy that combines a sliding mode tracking controller, a disturbance observer and an adaptive fuzzy PID cross coupled controller is proposed. Sliding mode control is simple and has strong robustness to parameter changes and disturbance, which is especially suitable for control of such as non-linear multi-axis motion system. Besides, disturbance is inevitable in practical application, which degrades the motion accuracy. In order to eliminate the influence of external disturbance and uncertainty, disturbance observer is adopted to accurately estimate external disturbance and reduce the chattering phenomenon of sliding mode control, then improve the single-axis tracking accuracy. In order to further consider the coordination between different motion axes and improve the contour accuracy, the PID cross coupled control is used. Owing to conventional PID control cannot satisfy the multi-axis servo motion system with nonlinearity and uncertainty, an adaptive fuzzy method with on-line real-time PID parameters adjustment is proposed. The three-axis motion platform driven by PMLSM is used as the control object, to analysis the influence of disturbance observer on sliding mode control signal and analysis adaptive fuzzy PID cross coupled control performance respectively. The disturbance observer is used to observe the disturbance signal and estimate the disturbance well. The chattering of the sliding mode control signal is obviously improved. Next, compared with the conventional PID-CCC control, adaptive fuzzy PID- CCC control can significantly reduce the tracking error, the contour accuracy is also obviously improved. The disturbance observer can effectively eliminate the influence of external disturbance, reduce the chattering of sliding mode control, and ensure the single-axis accurate tracking. The self-adaptive fuzzy PID cross coupled controller can eliminate the influence of the dynamic characteristics mismatching and parameter difference of each axis, and improve contour accuracy. The simulation results clearly demonstrate the effectiveness of the proposed control method.

Optimum speed controller structure utilizing the MCA approach

In this paper, an optimal speed controller for dc motor is considered using a PID controller and tuned its parameters of gain to offer an optimal solution by using a modified camel algorithm MCA approach. The proposed MCA scheme was applied to solve the difficulty of getting the optimum gains of PID parameters. The MCA has good evolutionary speed with the simple construction of optimization depend on camel searching performance. The characteristics of the MCA algorithm were confirmed by optimizing the gains parameters of proportional, integral, derivative PID controller. The performance of PID-MCA is comparing with a classic PID controller enhanced with GA genetic algorithm optimization method to tune the gain parameters of the speed controller system. It was shown that the utilize of optimization processes indicated better performance for the MCA procedure in term of speed of execution and the size of memory compared with the GA method by applying computer simulations analysis. The proposed scheme has an efficient feature that includes the ease of implementation, good efficiency of computational performances with stable convergence characteristics. The results indicated that the proposed MCA scheme is a useful tool for search ability, produced efficient outcomes compared with the GA optimized method when applied in the proposed system.

Review of Control of MIMO System Using 1Degree of Freedom PID, 2Degree of Freedom PID and Fractional order PID Controller

The aim of this work is to style a speed controller of a DC motor by tuning PID controller. To urge an output with minimum errors, we selected PID parameters using bio-inspired optimization technique of Genetic Algorithm. The second order system is employed here for speed control. DC motor is interfaced with Arduino via Motor driver circuitry. Discrete Time Reduced Order GPIO with Genetic algorithm calculates parameter of PID controller and consistent with those parameters Arduino controls DC motor.

Control of PID parameters by iterative learning based on neural network

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Study on Temperature Control Strategy of Boiler Main Steam for Frequent Action of AGC Command in Power Grid

Traditional PID is widely used in the main steam temperature control system of thermal power unit Cascade control. Although this control scheme is easy to be debugged on site, it is impossible to solve the problem of large fluctuation and over temperature of steam temperature only by adjusting PID parameters due to the characteristics of variable parameters, large inertia and large time delay of main steam temperature control system. Especially when the AGC command of power grid fluctuates frequently, the conventional control strategy is difficult to deal with, resulting in the change of main steam temperature regulation quality Poor, affecting unit economy and safety. In this paper, the sub PID set value adaptive control logic and desuperheating water injection logic to prevent the main steam temperature overshoot are used to solve the problem of the quality deterioration of the main steam temperature regulation under the frequent fluctuation of AGC instructions.