Proportional Integral Derivative Control Scheme Research Articles

Dynamic modeling and optimization of an eight bar stamping mechanism based on RBF neural network PID control

Introduction: Modern industrial manufacturing often requires the eight-bar stamping mechanism to have high motion accuracy and stability. To meet these stringent requirements, traditional control techniques such as proportional-integral-derivative (PID) control need to be improved.Methods: In this study, radial basis function neural network is introduced to improve the traditional proportional integral derivative control technique. The improved proportional integral derivative technique is applied to the modeling and optimization of eight kinds of bar stamping mechanisms.Results: Comparing the improved control technology, the experiment showed that the peak time and adjustment time of the improved technology were 0.516 s and 1.038 s, respectively, which are better than the comparative control technology. In addition, in the comparative analysis of the eight bar stamping mechanism, the proposed architecture scored 9.3 points in operational efficiency, which is significantly greater than the comparative architecture.Discussion: The results show that the combination of PID control strategy and radial basis function neural network provides a powerful tool for dynamic modeling and optimization of eight-bar stamping mechanism. It not only provides enhanced motion accuracy and stability, but also brings significant practicality to industrial manufacturing. This integration opens up new possibilities for improving the performance of complex mechanical systems to meet the evolving needs of modern manufacturing.

Development of a novel monolithic compliant Lorentz-force-driven XY nanopositioning system

A novel monolithic compliant Lorentz-force-driven XY nanopositioning system (MCLNS) is designed, analyzed, and experimentally assessed with the aim of high-resolution positioning across a large workspace. A double-symmetric Lorentz-force actuator (DSLA) with the benefits of zero friction, high thrust, and large stroke is proposed to generate the actuation force. Correspondingly, a monolithic four-prismatic parallel compliant mechanism (4P-PCM) is exploited to transmit the actuation motion to the central platform and minimize the parasitic motion. The unique integration of four DSLAs and one 4P-PCM make the proposed MCLNS possess compact structure and stable performance. The characterization of the MCLNS is formulated by a specially established analytical model and validated by finite-element analysis simulation and experimental tests. Experimental studies show that the workspace of the MCLNS prototype is large than 0.87 × 0.87 mm2 and the positioning resolution of the MCLNS prototype is better than 9 nm. By means of a nonlinear forward proportional integral derivative control strategy, the maximum contouring error of the MCLNS is maintained within 2.7% while tracking a 1257 μm s−1 circular trajectory.

Multi-loop active disturbance rejection control and PID control strategy for poultry house based on GA, PSO and GWO algorithms

Maintaining the health and welfare of broilers, besides obtaining and optimizing good performance, are the main objectives of poultry production. In response, climate control remains the most guaranteed strategy for managing livestock successfully. Separate controlling temperature and humidity on the one hand; and contaminant gases on the other was a focus of several investigations. Thus, the particularity of this work which involves the study, analysis, and control of broiler livestock building while taking into account, at the same time, all the system's constituent variables (i.e., temperature, humidity, NH3 and CO2 concentration, air velocity, and differential pressure). In this paper, an Active Disturbance Rejection Control (ADRC) and Proportional Integral Derivative (PID) controllers were designed and combined with a multi-loop approach for a multi-inputs multi-outputs (MIMO) system. Then, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO) were used to obtain the optimal controllers' parameters employing the reward function, the Integrated Time Absolute Error (ITAE), according to the poultry system requirements. Simulation experiments were carried out using the Matlab Simulink toolbox to verify the effectiveness of all the proposed control methods with the two optimization algorithms regarding stabilization and tracking setpoints. Despite the introduction of several disturbances in the plant model, the PSO-ADRC controller still exhibits notable benefits in terms of rise time, overshoot, settling time, and good disturbance rejection, proving the robustness of the suggested control method.

Dissipative PID control for uncertain positive Roesser system under the try-once-discard protocol

This paper addresses the problem of dissipative proportional–integral–derivative (PID) control for the delayed positive Roesser system with interval uncertainties under the try-once-discard (TOD) protocol. To alleviate the undesired data congestion phenomenon in the shared communication network, the TOD protocol is introduced to regulate which sensor node could release its measurement at each transmission instant. An output-feedback-based PID controller is designed for the two-dimensional (2-D) system with TOD protocol. Based on the co-positive Lyapunov–Krasovskii function method, sufficient criteria in the linear programming form are attained to ensure the positivity, 2-D (ζ,η)-γ-dissipativity and robust asymptotic stability of the closed-loop system. Finally, an illustrative example is given to show effectiveness of the PID control scheme designed.

A Fuzzy Incremental Proportional Integral Derivative Control Strategy for Flywheel Energy Storage Machines in Autonomous Vehicles

A Fuzzy Incremental Proportional Integral Derivative Control Strategy for Flywheel Energy Storage Machines in Autonomous Vehicles

A mathematical model with fractional-order dynamics for the combined treatment of metastatic colorectal cancer

Colorectal cancer (CRC) poses a significant global public health challenge as its prevalence continues to increase. This study delves into the intricate dynamics of metastatic CRC by utilizing a novel fractional-order model. Through a comprehensive analysis of existing literature and clinical data, we introduce an innovative fractional-order model tailored to metastatic CRC. This model encapsulates key factors like tumor growth, immune response, and therapeutic interventions. Our findings underscore the crucial role of epithelial cells (E) within the tumor microenvironment, emphasizing their significance due to their high sensitivity. Additionally, the influence of adenomatous polyps (P) is noteworthy, given their potential to transform into cancerous entities. Remarkably, the concentration of inflammatory cells (C) significantly impacts the model, shedding light on the pivotal role of the immune response. We implement a clever fusion of feedback control and Proportional–Integral–Derivative (PID) controllers, enabling dynamic self-adjustment and precision. Our results indicate that achieving high efficacy in treating metastatic colorectal cancer necessitates a synergistic and simultaneous application of immunotherapy and surgery. Also, surgical intervention should exert a slightly higher intensity than immunotherapy, even when administered concurrently. The PID control strategy offers a promising method for fine-tuning concentrations over time. These investigations enable a thorough exploration of how fractional-order parameters influence tumor progression, interactions with the immune system, and treatment outcomes. We conduct sensitivity analysis to pinpoint crucial model parameters governing the system’s dynamic behavior. The insights gleaned from our study hold significant promise for advancing treatment protocols and personalized medicine tailored to CRC patients.

Design of Water Heater Temperature Control System using PID Control

This research delves into advanced control methodologies by investigating the intricate applications of Proportional-Integral-Derivative (PID) control for achieving precise and dependable temperature regulation within electric water heaters. The study delves into various control strategies, namely Proportional, Proportional-Integral, and Proportional-Integral-Derivative methodologies, to realize the pinnacle of stable and exacting temperature control. The Proportional Controller, operating with a Kp value of 10, stands out with its relentless performance, characterized by minimal overshoot and an inconsequential steady-state error. Implementing the Proportional-Integral Controller, synergizing Kp at 10 and Ki at 5, elevates system stability while deftly curbing any hint of overshoot. The dynamic interplay between the Kp, Ki, and Kd parameters in the Proportional-Integral-Derivative (PID) Controller unveils an intricate dance of precision and control. Notably, configurations involving Kp 10, Ki 5, and Kd 2 emerge as beacons of rapid stabilization, heightened precision, and masterful overshoot management, exemplified by a rise time of 119.3543 seconds, settling time of 162.6116 seconds, overshoot of 1.0299%, peak time of 216 seconds, and a commendably low steady-state error of 0.31. This extensive exploration bears testament to its instrumental role in optimizing PID control strategies, ushering in augmented efficacy and pinpoint accuracy in water temperature regulation across an expansive spectrum of applications. As a result, these findings pave the way for the evolution of control methodologies that transcend theoretical confines and manifest within practical scenarios with profound impact.

Power quality enhancement by using Z-DVR based series voltage compensation with black widow optimization technique

In distribution system, voltage quality issues are the most concerning disturbances influencing the power quality (PQ). As a result, to alleviate this PQ concerns such as sag, swell, fluctuation, interruption, and harmonics on the sensitive load, the series voltage compensator dynamic voltage restorer (DVR) is utilized. Furthermore, a Z-source inverter (ZSI) based DVR is proposed in this paper to improve the power system's voltage restoration properties. To compensate the voltage concerns which is occurs in passive and transmission components, the 3-φ Z-DVR inverter with proportional integral derivative (PID) controller tuned by black widow optimization (BWO). By short circuiting the legs of inverter in the ZSI, prepare the possibility of buck and boost in voltage and utilize the LC impedance grid which incorporated power source to inverter circuit. In addition, to obtain the injecting voltage, PID control scheme for ZSI based DVR is proposed in this paper. The proposed modelling and simulation of DVR is implemented in MATLAB/Simulink tool and the outcomes are analyzed. Furthermore, reduction in voltage concerns, and total harmonics distribution (THD) with BWO tuned PID controller is superior which is 1.01% when compared with existing methods such as Harris Hawks optimization (HHO) based PID, genetic algorithm (GA) based PID controller.

Dissipative Discrete PID Load Frequency Control for Restructured Wind Power Systems via Non-Fragile Design Approach

This article proposes a discrete proportional-integral-derivative (PID) load frequency control (LFC) scheme to investigate the dissipative analysis issue of restructured wind power systems via a non-fragile design approach. Firstly, by taking the different power-sharing rates of governors into full consideration, a unified model is constructed for interconnected power systems containing multiple governors. Secondly, unlike existing LFC schemes, a non-fragile discrete PID control scheme is designed, which has the performance of tolerating control gain fluctuation and relieving the huge computational burden. Further, by constructing a discrete-type Lyapunov–Krasovskii functional, improved stability criteria with a strict dissipative performance index are established. Finally, numerical examples are presented to demonstrate the effectiveness of the proposed control method.

An intelligent control method based on artificial neural network for numerical flight simulation of the basic finner projectile with pitching maneuver

In this paper, an intelligent control method applying on numerical virtual flight is proposed. The proposed algorithm is verified and evaluated by combining with the case of the basic finner projectile model and shows a good application prospect. Firstly, a numerical virtual flight simulation model based on overlapping dynamic mesh technology is constructed. In order to verify the accuracy of the dynamic grid technology and the calculation of unsteady flow, a numerical simulation of the basic finner projectile without control is carried out. The simulation results are in good agreement with the experiment data which shows that the algorithm used in this paper can also be used in the design and evaluation of the intelligent controller in the numerical virtual flight simulation. Secondly, combined with the real-time control requirements of aerodynamic, attitude and displacement parameters of the projectile during the flight process, the numerical simulations of the basic finner projectile’s pitch channel are carried out under the traditional PID(Proportional-Integral-Derivative) control strategy and the intelligent PID control strategy respectively. The intelligent PID controller based on BP(Back Propagation) neural network can realize online learning and self-optimization of control parameters according to the acquired real-time flight parameters. Compared with the traditional PID controller, the concerned control variable overshoot, rise time, transition time and steady state error and other performance indicators have been greatly improved, and the higher the learning efficiency or the inertia coefficient, the faster the system, the larger the overshoot, and the smaller the stability error. The intelligent control method applying on numerical virtual flight is capable of solving the complicated unsteady motion and flow with the intelligent PID control strategy and has a strong promotion to engineering application.

An adaptive control method for the covers on the south roof of Chinese solar greenhouses: A case study of insulation blankets

The Chinese solar greenhouse (CSG) enables farming activities in colder conditions and extends the harvest time. It is a crucial component of Chinese agricultural facilities. Rolling/unrolling the cover on the south roof is critical for modifying the greenhouse environment and improving the production efficiency of CSGs. However, since the structure of CSGs is constantly being updated, the existing winding equipment is inadequate because it causes deformation of covers. This study used as insulation blankets an example to proposed an adaptive control method of the rolling cover of CSGs. Deformation and force analysis showed that the fundamental reason for the deformation of the insulation blanket and the winding mechanism was the uneven load distribution in the length direction. A segmented winding mechanism and multi-motor scheme were used to reduce the deformation of the insulation blanket. A fuzzy proportional–integral–derivative (PID) control algorithm was developed to adjust the speed of the slave motors adaptively to roll/unroll the insulation blanket. The simulation results showed that the shorter winding mechanism resulted in lower torsional deformation. Experiments using a scale model demonstrated that the proposed double-motor scheme and fuzzy PID control method provided good performance for rolling/unrolling the insulation blanket. The double-motor scheme can significantly improve the operation efficiency of rolling insulation blankets. The running time of the double-motor scheme was 12.81% lower than that of the single-motor scheme, the average absolute position deviation was 41.95% lower, and the average absolute standard deviation was 44.51% lower. The proposed fuzzy PID control strategies enable the closed-loop control of the deceleration motor and the adjustment of the displacement deviation to reduce the deformation of the insulation blanket according to the feedback received from the slave motor. Unlike the conventional PID control, the fuzzy PID control automatically adjusts the system parameters to eliminate the system error. The control accuracy and stability of the fuzzy PID method have reached a good level, and the applicability is better than that of the conventional PID method. In the scale model experiments, the average position deviation remained within ±1 mm, and the average standard deviation was 1.32 mm. The proposed adaptive control method for the cover on the south roof of CSGs is highly suitable for practical applications. The study also provides application examples and theoretical references for the automation of rolling covers in greenhouses worldwide.

Robust cascade control strategy for trajectory tracking to decouple disturbances using 3-degree-of-freedom inertial stabilized platform and its experimental validation

Inertial stabilized platform (ISP) is a vital component in modern tracking system which can segregate unsettling influence, keep altitude reference and rapidly realize identification and tracking of the target. For accurate tracking, the platform should be able to continuously point towards the target in presence of disturbances as well as parametric uncertainties associated with system modelling which normally degrade system performance. To tackle these challenges, different kinds of control strategies have been reported to achieve desired performance. However, there is an inevitable design trade-off between tracking and disturbance rejection capability as control performance decreases with the increase in system robustness. To alleviate this problem, the present work proposes a robust two-loop cascade control strategy where genetic algorithm (GA) optimized proportional–integral–derivative (PID) in the outer-loop facilitates precision tracking of the target. In the inner loop, lower-order robust controller designed by approximate generalized time moment (AGTM)/approximate generalized Markov parameter (AGMP) model matching approach is used to retain the robustness characteristics of [Formula: see text] controller to mitigate disturbances and model parametric uncertainties. System performance is verified through simulation as well as hardware implementation on a laboratory-fabricated three-axis gimbal platform prototype. The results show 48% improvement in tracking performance and 39.69% improvement in the rejection time of step disturbance in comparison with conventional PID control strategy.

Fuzzy-PID-Based Atmosphere Packaging Gas Distribution System for Fresh Food

The regulation process of gas distribution systems for atmosphere packaging has the characteristics of being nonlinear time varying and having hysteric delay. When the conventional proportional-integral-derivative (PID) control algorithm is applied to this kind of system, it is difficult to set the parameters as the process is time consuming and has poor reliability. For these reasons, this paper designs a gas distribution system for fresh food atmosphere packaging based on a fuzzy PID controller. The step response method is used to construct the system’s mathematical model under the given conditions and to optimize the gas distribution control flow. A simulation experimental platform to compare between the fuzzy PID controller and a conventional PID controller is designed, and the effectiveness of the fuzzy PID control strategy is verified, which proves that it can improve the performance of the monitoring system. The system can realize the remote monitoring of the gas distribution processes through the use of a mobile phone communication network. The data transmission is reliable, the operation is convenient, and, at the same time, the overall efficiency is improved. The results of the system simulation and the gas distribution for atmosphere packaging show that the fuzzy PID algorithm has a faster gas distribution speed and good environmental adaptability as the controller of the gas distribution system. The results show that the stability time of the fuzzy PID controller is about 38 s, while the stability time of the conventional PID controller is about 85 s. The concentration error of fresh gases is ±0.25% floating, the accuracy is increased by 12 times, and the gas distribution speed is increased by about 50% when the system is stable.

A review of thermal management of proton exchange membrane fuel cell systems

Proton exchange membrane fuel cells (PEMFCs) have the advantages of long operation cycles, high energy efficiency, and no pollution of reaction products. Temperature is an important factor to ensure the operation of fuel cell systems. Too high temperature will cause irreversible damage to the proton exchange membrane, and too low temperature will greatly reduce the power generation efficiency of fuel cells. Therefore, the effective thermal management temperature control can ensure the stable operation of the system under steady state and dynamic variable load. It can also improve the reaction efficiency of the fuel cell system and prolong the life of the fuel cell. This paper mainly summarized the cooling mode and control strategy of PEMFCs based on thermal management system. The application of different cooling methods is further discussed. The characteristics of traditional proportional-integral-derivative (PID) control, fuzzy PID control, predictive control, adaptive control, and other common thermal management control strategies were described in detail. The research status of scholars in various countries were analyzed, respectively, and the cooling effects of different strategies are compared. Through the review and research on the temperature control of PEMFCs, it is found that the stable operation of the stack is inseparable from the coordination of reasonable cooling mode and control strategy.

PID Control of a Superheated Steam Temperature System Based on Integral Gain Scheduling

The high-quality operation of a superheated steam temperature (SST) system is a core fact of the safety, economy, and stability of thermal power units. How to improve the control performance of an SST system under large-varying operating conditions is becoming a research hotspot. To solve this challenge, this paper proposes a proportional integral derivative (PID) control strategy based on integral gain scheduling. Based on the introduction of the SST system and classical model under typical operating conditions, the control difficulties of the SST system are analyzed theoretically. Then, a PID control strategy, based on integral gain scheduling, is introduced for the cascade control structure, and the stability of the proposed control strategy is analyzed by calculating the PID stability region. Finally, the effectiveness of the proposed method is verified under nominal and uncertain conditions, where the proposed method could obtain satisfactory tracking and disturbance rejection control performance. Simulation results show the valuable application prospects of the proposed method.

Evaluation and Modeling of the Car Speed Control Process using a PID Controller

Car speed is an essential attribute for analysing the utility of a transport mode. The speed relationship between multiple modes of transport is of interest to traffic planners and operators. Nowadays, the cruise control system has become a common feature of modern cars. A car control system helps in providing comfortability to the driver while driving long-distance travel. Using a car control system, travelling on the highways has become easier than before because it reduces the mental and physical stress caused by regularly monitoring the speed of the car and frequently pressing the gas pedal to maintain the speed. This paper is aimed at modelling a car control system and examining its characteristics based on the PID control strategy. Proportional-Integral-Derivative (PID) controller provides a great way to stabilize systems. It has the ability to change the response of the system to be stable and reliable when it is used for controlling systems. This system is actualized with the help of MATLAB for simulation and control purposes. The paper showed that without the use of the PID controller, the speed was stable after 100 seconds, and when the controller was used and self-turned, the speed was approximately stable at 20 seconds, and this shows the effectiveness of using the PID controller.

Research on Trajectory Tracking Control of Underwater Vehicle Manipulator System Based on Model-Free Adaptive Control Method

In order to improve the trajectory tracking accuracy of an Underwater Vehicle Manipulator System (UVMS) under uncertain disturbance conditions of ocean current, a Model-free Adaptive Control (MFAC) method was used. Combined with Radial Basis Function Neural Networks (RBFNN), the RBFNN-MFAC method is proposed to improve the performance of the controller. A hydrodynamic model of UVMS was defined in the commercial software, Fluent, to calculate hydrodynamics disturbance, and the mechanism of the dynamic model of UVMS was defined in the commercial software, Adams, to simulate the motion of UVMS. The trajectory tracking performance with various control schemes, including PID (Proportional Integral Derivative), MFAC and RBFNN-MFAC, were analyzed with the Adams and Simulink joint simulation model. The results show that the position tracking accuracy and the speed tracking accuracy with the MFAC control scheme were 68.1% and 81.0% better, respectively, than those with PID control scheme. The position tracking accuracy and the speed tracking accuracy with the RBFNN-MFAC control scheme were 66.3% and 43.1% better, respectively, than those with the MFAC control scheme. The MFAC control scheme and the RBFNN-MFAC control scheme proposed in this paper exhibit good trajectory tracking performance without the precise dynamic model of UVMS, which is of great importance to applications in engineering.

Observer-based PID control for actuator-saturated systems under binary encoding scheme

In this paper, the observer-based proportional-integral-derivative (PID) control problem is investigated for a class of actuator-saturated systems affected by multiplicative noises under the binary encoding scheme (BES). The communication between the sensors and the observers is implemented via a shared network, in which the measurement signals are transmitted by the BES. During the transmission, random bit errors may occur in the bit string due to the channel noises. The aim of this paper is to design an observer-based PID controller such that the closed-loop system is exponentially mean-square ultimately bounded with the consideration of random bit errors, actuator saturations and multiplicative noises. Sufficient conditions are presented to guarantee the expected performance of the resulted tracking error, and the controller gain matrices are obtained by solving a set of matrix inequalities. Finally, the effectiveness of the proposed PID control scheme is verified by a simulation example.

Observer-Based PID Control Strategy for the Stabilization of Delayed High Order Systems with up to Three Unstable Poles

In this paper, a new method to manage the stabilization and control problems of n-dimensional linear systems plus dead time, which includes one, two, or three unstable poles, is proposed. The control methodology proposed in this work is an Observer-based Proportional-Integral-Derivative (PID) strategy, where an observer and a PID controller are used to relocate the original unstable open-loop poles to stabilize the resultant closed-loop system. The observer provides an adequate estimation of the delayed-free variables and the PID uses the delay-free variables estimated by the proposed observer. Also, step-tracking is achieved in the overall control scheme. Necessary and sufficient conditions are presented to ensure closed-loop stability based on the open loop parameters of the system. The observer-based PID strategy considers five to seven constant parameters to obtain a stable closed-loop system. A general procedure to implement the proposed control strategy is presented and its performance is evaluated by means of numerical simulations.

Research on Compound PID Control Strategy Based on Input Feedforward and Dynamic Compensation Applied in Noncircular Turning.

The fast tool servo (FTS) control strategy is the control core of high-speed noncircular turning. This method should ensure high-speed and precision positioning and have the corresponding anti-interference ability in the micro-stroke motion with dynamic changes of tool feed and load. Most of the previous FTS control studies used the repetitive control and speed feedforward control strategy, which achieved promising results under ideal machining conditions. However, this strategy showed some defects in the real-world complex and changeable working conditions such as time-varying cutting force, intermittent cutting and fluctuating machine spindle speed. This paper proposed and implemented a compound proportional integral derivative control strategy based on input feedforward and dynamic compensation in noncircular turning. This technique successfully met the motion requirements of the high responsiveness of micro-stroke in noncircular turning and overcame disturbances from complex time variations of the cutting force, intermittent cutting case of the product and fluctuations of machine spindle speed. According to the findings, the machining tracking error was less than ±2 µm. Experimental results demonstrated the excellent tracking performance and machining effect of this control strategy.