Proportional, Integral And Differential Research Articles

Research on Diesel Engine Speed Control Based on Improved Salp Algorithm

To better regulate the speed of diesel engines and optimize the speed overshoot and fast response, a speed control method combining the improved salp swarm algorithm (ISSA) with the proportional integral and differential (PID) controller was proposed. A real-time simulation model for a high-pressure common rail diesel engine was established. Addressing the challenges of the salp swarm algorithm (SSA), such as uneven population distribution and its tendency to become trapped in local optima, logistic-tent chaotic mapping, adaptive parameters was introduced, as well as adaptive dynamic inertia weights, elite strategy, and a dynamic inverse strategy. These enhancements bolstered the algorithm’s precision and efficiency in both global and local searches. Using the enhanced SSA, the parameters of the PID controller for the diesel engine model was optimized. The results indicated that the ISSA offers superior parameter identification precision, strengthening speed control stability. During sudden changes in speed and load, the overshoot decreased by an average of more than 30.3% and more than 8.6%, respectively. Moreover, the settling time decreased by an average of more than 0.76 s and 1.52 s, respectively, significantly enhancing the quality of diesel engine speed control.

Disturbance Rejection-Based Optimal PID Controllers for New 6ISO AVR Systems

In the literature, different approaches that are employed in designing automatic voltage regulators (AVRs) usually model the AVR as a single-input-single-output system, where the input is the generator reference voltage, and the output is the generator voltage. Alternately, it could be thought of as a double-input, single-output system, with the excitation voltage change serving as the additional input. In this paper, unlike in the existing literature, we designed the AVR system as a sextuple-input single-output (6ISO) system. The inputs in the model include the generator reference voltage, regulator signal change, exciter signal change, amplifier signal change, generator output signal change, and the sensor signal change. We also compared the generator voltage responses for various structural configurations and regulator parameter choices reported in the literature. The effectiveness of numerous controllers is investigated; the proportional, integral and differential (PID) controller, the PID with second-order derivative (PIDD2) controller, and the fractional order PID (FOPID) controller are the most prevalent types of controllers. The findings reveal that the regulator signal change and the generator output signal change significantly impact the generator voltage. Based on these findings, we propose a new approach to design the regulator parameter to enhance the response to generator reference voltage changes. This approach takes into consideration changes in the generator reference voltage as well as the regulator signal. We calculate the regulator settings using a cutting-edge hybrid technique called the Particle Swarm Optimization African Vultures Optimization algorithm (PSO–AVOA). The effectiveness of the regulator design technique and the proposed optimization algorithm are demonstrated.

Genetic Algorithm-Based Mach Number Control of Multi-Mode Wind Tunnel Flow Fields

There are unfavorable conditions such as constantly changing working conditions and frequent disturbances that affect Mach number control in wind tunnel flow fields. As the proportional, integral and differential (PID) parameters need to be re-tuned for each working conditions of a wind tunnel, the operational costs of wind tunnels are very high. Therefore, to lower these costs, a genetic algorithm was utilized to tune the PID parameters to achieve Mach number control of a multi-mode wind tunnel flow field. In this paper, firstly, models for the multi-mode wind tunnel were established; secondly, a PID control system was designed based on the genetic algorithm and the control effects of the proposed PID control system were verified by simulations and were compared with the effects of a PSO tuning PID control system.

Feedback PID Controller-Based Closed-Loop Fast Charging of Lithium-Ion Batteries Using Constant-Temperature–Constant-Voltage Method

Lithium-ion batteries are the most used technology in portable electronic devices. High energy density and high power per mass battery unit make it preferable over other batteries. The existing constant-temperature and constant-voltage charging technique (CT–CV), with a closed loop, lacks a detailed design of control circuits, which can increase charging speed. This article addresses this research gap in a novel way by implementing a simpler feedback proportional integral and differential (PID) control to a closed-loop CT–CV charging circuit. Voltage-mode control (VMC) and average current-mode control (ACM) methods were implemented to maintain the battery voltage, current, and temperature at safe limits. As per simulation results, 23% faster charging is achieved by implementing VMC and almost 50% faster charging is attained by employing the ACM technique in the PID controller. Our proposed control strategy is validated experimentally, which yields up to 25% faster charging of a battery than the reference battery.

Modelling and control of solar thermal power generation network in smart grid

The thermal storage system is an essential part of the trough solar thermal power generation system. Due to the strong randomness, intermittency, and volatility of solar energy resources, to further improve the system?s overall reliability to meet the needs of variable operating conditions, the paper optimizes the control strategy of the trough solar heat storage system. Taking the molten salt heat storage medium in the oil/salt heat exchanger, the core equipment of the heat storage system, as the critical research object, the article adopts proportional, integral, and differential (PID) control theories. It builds the system in the MATLAB/Simulink simulation environment mathematical model. We use the critical proportionality method to determine many critical parameters in the control system, tune the proportional coefficient, integral time, and other physical quantities in the PID controller, and analyze the proportional control, proportional-integral control, PID controls the respective dynamic response characteristics of these three different control systems. The simulation and comparative analysis results show that: compared with the other two control methods, PID control can effectively weaken the heat storage system oscillation caused by external disturbance, its dynamic response speed is faster, the adjustment time is shorter, and it can meet the requirements of operational stability. The paper adopts PID control, which reduces the control difficulty of the trough solar heat storage system and improves the adaptability to changes in external meteorological resources. The research results have particular guiding significance at the academic and engineering levels.

Idvc Based Hysteresis Controller For Three-Phase Induction Motor Drive

Induction Motor is the most commonly used motor in industrial applications due to its characteristics like self-starting, reliable and easy speed control. The objective of the proposed system is to provide efficient speed control with lesser current harmonics. The Indirect Vector Control (IVDC) method is been presented for speed control of induction motor due to its high dynamic and low drift property. Though there were many classical methods for speed control like Ward-Leonard method etc.; in later years, power electronics circuits were preferred due to its high efficiency, reliability and accuracy. But the presence of static converter in drive circuits results in harmonics, giving in high feedback complexity. Therefore, the Hysteresis controller with conventional Proportional Integral and Differential (PID) control for speed and PI controller for flux is used to control the current harmonics at the point of common coupling. The simulation for speed control in squirrel-cage induction motor is carried out using the MATLAB/Simulink and the parameters like torque, speed, current and Total Harmonic Distortion are analyzed to show optimal response of drive system.

A digital readout interface for a surface micromachined MEMS accelerometer with a novel loop compensator

This paper proposes a novel digital readout interface for capacitive MEMS accelerometer. The digitalization is fulfilled by incorporating a 1-bit [Formula: see text] (sigma-delta) modulator into the closed servo loop. It both realizes a direct digital output efficiently and linearizes the electrostatic feedback force. To maintain the stability and improve loop linearity, a discrete-time proportional integral and differential (PID) compensator is used. It improves the in-band gain, enhances quantization noise suppressing ability and maintain the high-frequency phase margin at the same time. Thus the linearity and noise performance are improved. The whole chip is fabricated using 0.35 [Formula: see text]m CMOS-BCD technology. Test results show that, the linearity is better than 0.1% and the noise floor is as low as 1 [Formula: see text]g/[Formula: see text].

하이브리드 강화학습을 이용한 무인기 자율주행

Autonomous UAV (Unmanned Aerial Vehicle) is an ideal platform for navigation in complex and remote environments like inspection, mapping, monitoring and rescue. UAV control mechanisms tend to be designed for specific tasks; new tasks often require new controls. Previous research has shown RL (Reinforcement Learning) to be a feasible solution by autonomously learning a general control scheme without explicit engineer knowledge. However, a major drawback of RL has been the requirement to obtain many iterative training sequences, i.e. trial and error exploration of a robot. The main contribution of this paper is a rapid model-based RL method that combines a PID (Proportional, Integral and Differential) control approach with an RL algorithm in a hybrid manner. PID control is one of the most practical control methods and has been used for a century by both academy and industry since it reduces dynamic model demands and costly gain-tuning effort. This hybrid RL method can amplify synergy between the learning convergence speed and the control performance, which I evaluate with a simulation of path planning for a nano-UAV.

Adopting Setpoint Weighting Strategy for WirelessHART Networked Control Systems Characterised by Stochastic Delay

In networked control system, such as WirelessHART that is characterized by stochastic delay, the use of proportional integral and differential (PID) controllers is inadequate. This is because PID performs poorly in handling time-delay processes. The main reason for this poor performance is the limitation in the range of stable gain of the controller. Time delay causes oscillatory response of the PID with large gain. Likewise, sluggish response is experienced with small gain of the PID. Also, dead time compensators like smith predictor and internal model controller are difficult to be implemented practically since they require exact model of the process to be controlled. Therefore, this paper proposes the application of setpoint weighting strategy to be used alongside PID controller in a WirelessHART network. This method extends significantly the range of the PID gain, while providing good set point tracking and load regulation. From the simulation and experimental results obtained, the capability of the approach to load regulation and tracking can be seen in its fast recovery from effect of disturbance with minimal overshoot. Thus, a two degree of freedom control is achieved. Results also showed that the method is robust to real-time random variable network delay and model mismatches.

Precision laser tracking servo control system for moving target position measurement

Laser tracking and servo control is essential for the laser tracker to accurately measure coordinates and trajectories of dynamic targets in the space. It has demanding requirements for tracking performance of the servo system in terms of dynamic response properties, controlling accuracy and stability. The currently used servo controlling system in the laser tracker usually adopts the traditional proportional, integral and differential (PID) controlling methods While measuring the dynamic coordinates, the target lens move randomly in a greatly dynamic way; the system’s tracking speed faces a delay in adapting to it, resulting in frequent miss or loss of the target. Based on the requirements of the laser tracing and servo system to quickly track targets moving in a very random and dynamic manner, this paper studies the controlling properties of the laser tracking servo system and the modelling of the controlled objects, proposing a hybrid controlling structure and method which incorporates multi-loop feedback control as well as fuzzy prediction and control-based correction. The deviation signal of the photoelectric location is extracted and fuzzified. Fuzzy rules and controlling strategies are formulated. A fuzzy adaptive PID tracking control algorithm is also presented. A platform for testing the servo tracking system is constructed. The proposed controlling strategies and algorithms are applied to the single-axis laser tracking and rapid prototype tracking tests. Test results show that the angular acceleration of the dynamic tracking servo exceeds 200°/s2, proving great improvements in the system’s random dynamic tracking performance and stability.

Multi Area Load Frequency Control Using Particle Swarm Optimization and Fuzzy Rules

Abstract This paper present heuristics based study of multi area power network. Heuristic procedures involving Particle Swarm Intelligence and Fuzzy based inferences have been employed to effectively obtain the optimized gains of PID controller. Any change in the load demand causes generator's shaft speed lower than the pre-set value and the system frequency deviates from the standard value results in malfunctioning of frequency relays. A five area load frequency model is constructed in Matlab/simulink by implementing the PID (Proportional, Integral and Differential) controllers to control the frequency deviations. The effect of interconnection of multi area power system as ring connection has been discussed. Simulations performed show the effectiveness of the current approach over simple fuzzy inferences in terms of performance as well as execution efficiency.

Fuzzy Control Strategy of the Mixed Magnetic Levitation Bearing Rotor System

This paper proposes a Fuzzy Control strategy of magnetic levitation bearing rotor according to the mixed magnetic levitation bearing. Combined with electromagnetic winding working principle, this paper uses the self-sensing displacement self-diagnosing system instead of the special displacement sensor, makes a no sensor self-diagnosing magnetic suspension control system, controls the system by the fuzzy PID (proportional, integral and differential) controller, and builds a mathematical model of the control system. Analyzing the fuzzy rules and fuzzy control principle of the fuzzy PID controller setting parameters, this paper has a fuzzy simulation for the system.

Experimental analysis and characterization of electrostatic-drive tri-axis micro-gyroscope

A planar micro-machined tri-axis gyroscope in decoupled-mode mechanical structure is presented, verified for superior detection capability and analyzed by experiments in this paper. Initially, the natural frequencies of sense modes are successfully tuned to match the natural frequency of drive mode by polarization voltages onto the associated sensing electrodes so that the inherent bias frequency at each sense mode can be removed. Secondly, the undesired cross-axis coupling effects between drive mode and sense modes are substantially suppressed by the cooperation of mechanical design and an integrated Automatic Gain Control (AGC) loop for drive mode. For highly reliable tuning to ensure resonance, the AGC and PLL (Phase Lock Loop) are integrated with a PID (Proportional, Integral and Differential) feedback controller to eliminate steady-state errors and overshoots. The performance of the micro-gyroscope is analyzed and evaluated by experiments. The achieved scale factors (the reflected voltage to the detected angular rate) of the proposed tri-axis micro-gyroscope are 50.4 μV/°/ s, 60.3 μV/°/ s, and 71.2 μV/°/ s for X-, Y- and Z-axes (principal axis: Z-axis) respectively. The resulted resolutions are about 0.72 ° / s / Hz , 143 ° / s / Hz and 0.42 ° / s / Hz for X-, Y- and Z-axes respectively. The Cross-axis sensitivities are reduced down to 22%, 9% and 1.84% for X-, Y- and Z-axes respectively. S/N ratios reach 59.3, 13.8, and 140.1 for X-, Y- and Z-axes respectively. The experimental results illustrate that the gyroscope exhibits superior to detect exerted angular rate, in addition to successful suppression upon the cross-axis perturbation between drive mode and sense mode. Principle-axis sensitivity, resolution and floor noise are all numerically evaluated. Further more, cross-axis sensitivity, Signal-to-Noise Ratio (SNR) and measurement error are investigated. Finally, a few comparisons with the other typical types of gyroscopes are reported.

Dynamic MIPS rate stabilization in out-of-order processors

Today's microprocessor cores reach high performance levels not only by their high clock rate but also by the concurrent execution of a large number of instructions. Because of the relationship between power and frequency, it becomes attractive to run an OoO (Out-of-Order) core at a frequency lower than its nominal frequency in the context of embedded or real-time systems. Unfortunately, whereas OoO pipelines have high average throughput, their highly variable and hard-to-predict execution rate makes them unsuitable for real-time systems with hard or even soft deadlines. In this paper, we demonstrate that the execution time of an OoO processor can be stable and predictable by controlling its MIPS (Mega Instructions Per Second) rate via a PID (Proportional, Integral, and Differential gain) feedback controller and DVFS (Dynamic Voltage and Frequency Scaling). The stabilized processor uses much less power per committed instruction, because of the reduced average frequency. The EPI (Energy Per Instruction) is also cut by an average of 28% across our benchmark programs. Since a stable MIPS rate is maintained consistently with lower power/energy per instruction, OoO processors stabilized by a feedback controller can realistically be deployed in real-time systems. To demonstrate this capability we select a subset of the MiBench benchmarks that displays the widest execution rate variations and stabilize their MIPS rate in the context of a 1GHz Pentium III-like microarchitecture.

The plasma current control in the TRIAM-1M tokamak

TRIAM-1M is a superconducting tokamak, the plasma is maintained by RF (radio frequency) wave completely without ohmic field in the steady-state operation. An active control of plasma current in fully non-inductive lower hybrid current drive (LHCD) plasmas on TRIAM-1M is demonstrated successfully for more than 1 min. A simple model to decide the PID (proportional integral and differential) control parameters based on secondary lower hybrid wave (LHW) is proposed. The PID parameters different from the prediction of the model prevent from maintaining plasma current well.

On parameters identification of computational models of vibrations during quiet standing of humans

Vibration of the center of pressure (COP) of human body on the base of support during quiet standing is a very popular clinical research, which provides useful information about the physical and health condition of an individual. In this work, vibrations of COP of a human body in forward–backward direction during still standing are generated using controlled inverted pendulum (CIP) model with a single degree of freedom (dof) supplied with proportional, integral and differential (PID) controller, which represents the behavior of the central neural system of a human body and excited by cumulative disturbance vibration, generated within the body due to breathing or any other physical condition. The identification of the model and disturbance parameters is an important stage while creating a close-to-reality computational model able to evaluate features of disturbance. The aim of this study is to present the CIP model parameters identification approach based on the information captured by time series of the COP signal. The identification procedure is based on an error function minimization. Error function is formulated in terms of time laws of computed and experimentally measured COP vibrations. As an alternative, error function is formulated in terms of the stabilogram diffusion function (SDF). The minimization of error functions is carried out by employing methods based on sensitivity functions of the error with respect to model and excitation parameters. The sensitivity functions are obtained by using the variational techniques. The inverse dynamic problem approach has been employed in order to establish the properties of the disturbance time laws ensuring the satisfactory coincidence of measured and computed COP vibration laws. The main difficulty of the investigated problem is encountered during the model validation stage. Generally, neither the PID controller parameter set nor the disturbance time law are known in advance. In this work, an error function formulated in terms of time derivative of disturbance torque has been proposed in order to obtain PID controller parameters, as well as the reference time law of the disturbance. The disturbance torque is calculated from experimental data using the inverse dynamic approach. Experiments presented in this study revealed that vibrations of disturbance torque and PID controller parameters identified by the method may be qualified as feasible in humans. Presented approach may be easily extended to structural models with any number of dof or higher structural complexity.

Control system for 5MW neutral beam ion source for SST1

This article describes the control system for a 5MW ion source of the NBI (neutral beam injector) for steady-state superconducting tokamak-1 (SST-1). The system uses both hardware and software solutions. It comprises a DAS (data acquisition system) and a control system. The DAS is used to read the voltage and current signals from eight filament heater power supplies and 24 discharge power supplies. The control system is used to adjust the filament heater current in order to achieve an effective control on the discharge current in the plasma box. The system consists of a VME (Verse Module Eurocard) system and C application program running on a VxWorks™ real-time operating system. A PID (proportional, integral, and differential) algorithm is used to control the filament heater current. Experiments using this system have shown that the discharge current can be controlled within 1% accuracy for a PID loop time of 20ms. Response of the control system to the pressure variation of the gas in the chamber has also been studied and compared with the results obtained from those of an uncontrolled system. The present approach increases the flexibility of the control system. It not only eases the control of the plasma but also allows an easy changeover to various operation scenarios.

PID-RPR: A High Performance Bandwidth Allocation Approach for RPR Networks

Resilient Packet Ring (RPR) is a new technology currently being standardized in the IEEE 802.17 working group. The existed bandwidth allocation algorithms for RPR networks are not able to provide satisfactory solutions to meet the performance requirements. In this paper we propose one fair bandwidth allocation algorithm, termed PID-RPR, which satisfies the performance goals of RPR networks, such as fairness, high utilization and maximal spatial reuse. The algorithm is operated at each RPR node in a distributive way; the proportional, integral and differential (PID) controller is used to allocate bandwidth on the outgoing link of the node for the flows over the link in a weighted manner. To achieve the global coordination, one control packet containing every node's message runs around the ring in order to update the relevant message for all nodes on the ring. When the packet reaches one node, this node adjusts its own rate according to its own message in the control packet; in the meantime it updates other nodes' control message in the control packet. As the control packet propagates around the ring, each node can eventually adjust its sending rate to reach its fair share according to the fairness criterion, and the buffer occupancy at each node is kept within the target value. Our algorithm is of distributed nature in the sense that upstream ring nodes inject traffic at a rate according to congestion and fairness criteria downstream. The simulation results demonstrate that satisfactory performance of RPR networks can be achieved under the proposed bandwidth allocation scheme.

Development of an Enthalpy and Carbon Dioxide Based Demand Control Ventilation for Indoor Air Quality and Energy Saving with Neural Network Control

An enthalpy and carbon dioxide level based demand control ventilation (EDCV) algorithm has been developed. This takes into account both the indoor occupancy level and the energy content of the fresh air and return air while controlling the fresh air supply. It has been applied under various operating conditions to ensure that the most effective control strategy was used. A back propagation (BP) neural network was used to tune the proportional, integral and differential (PID) parameters in order to obtain a good control performance. Experiments were conducted in a mediumsized lecture theatre to verify the performance of the developed EDCV algorithm in a real application. The results showed that acceptable indoor air quality could be obtained with less energy consumption. Under the optimum experimental conditions, about 15.4% of the total cooling energy was saved. The control performance was found to be good with the PID parameters tuned via the neural network

Feedback control of flexible four-bar linkages: a numerical and experimental investigation

A control scheme for a four-bar linkage with all the links flexible is proposed and tested both numerically and experimentally. The control strategy consists in selecting a reduced number of measurable variables through which performing position and vibration are controlled independently. The controlled variables are the crank angle and the link curvatures, which provide an adequate description of the temporal evolution of the mechanism position and vibrational phenomena. Position control is performed through a proportional integral and differential (PID)-like regulator while proportional controllers are employed to damp the fundamental components of the link oscillations. A force of gravity compensator is introduced to increase the control system performances and appropriate devices are proposed to avoid coupling effects among the controlled variables. The control scheme is first tested and tuned in simulation, where the dynamic behaviour of the flexible linkage is reproduced through a fully coupled non-linear model based on the finite element theory. The performances of the control scheme are assessed by studying the step response of the closed-loop system. The numerical results attained prove that the proposed control scheme achieves efficient positioning and vibration suppression performances. The experimental validation of the control scheme is carried out on an instrumented prototype of the flexible four-bar linkage. Experimental recordings are in good agreement with the numerical results therefore confirming both the effectiveness of the control scheme and the accuracy of the dynamic model.