Level Control System Research Articles

A learning‐based hierarchical energy management control strategy for hybrid electric vehicles

AbstractIn this work, a novel energy management control framework is developed for hybrid electric vehicles (HEVs) driving in car‐following scenarios. In order to enhance the energy efficiency while maintaining the driving safety, a hierarchical control approach consisting of an upper level speed tracking control scheme and a lower level energy management control strategy is proposed. For the upper level tracking control system, an iterative learning model predictive control (ILMPC) scheme is developed to guarantee the tracking performance and the driving safety simultaneously. Additionally, a model predictive control (MPC) algorithm is adopted at the lower level to optimize the torque distribution in real‐time based on the driving cycles generated by the upper level control system. With the proposed hierarchical control framework, HEVs are able to improve the energy efficiency significantly by taking the advantages of the operational repeatability. The convergence of the proposed control strategy is analyzed rigorously, and its effectiveness is illustrated through numerical simulations.

Design and construction of wireless water level control system with motor protector

This research work presents the design and construction of a micro-controller-based wireless water level control system. The need to bring a solution to the problem of water shortage in various places by eliminating one of the culprit; waste of water during pumping and dispensing into overhead thanks, calls for an automated control system which puts into consideration, means of avoiding mechanical tears and wears that arises with the use of robes as water level sensor, through the incorporation of wireless water level sensor in place of robes in sensing the water level in the modeled tank. To solve this problem, circuit analysis and design, of the five main sub-circuitry units, this includes: power supply unit, logic and switching circuitry unit, relay unit, LCD display unit was carried out using ultrasonic water level sensor, AT89S51 microcontroller, LCD module relay circuitry system and a few discrete components. The design of the controller in this scenario is not just cost effective but helps in avoiding mechanical tears and wears that arises with the use of robes as water level sensor, by providing an improvement on existing water level control system through the incorporation of wireless water level sensor in place of robes in sensing the water level in the modeled tank.

Research on an Adaptive Active Suspension Leveling Control Method for Special Vehicles

Adaptive active suspension systems, integral to specialized vehicles, hold significance for their stability and safety. This study introduces a novel adaptive active suspension system featuring four independently controlled wheels employing wheel-hub motors, hydraulic cylinders, pump motor power, controllers, and sensors. A rapid and, within a certain range, leveling and height adjustment control strategy is proposed for this system, utilizing the Kalman filter algorithm. Additionally, the paper examines the front-wheel Ackermann steering model and four-wheel reverse Ackermann transition model to enhance the suspension’s stability. Subsequently, experiments on leveling and height adjustment are conducted, demonstrating the system’s capability to swiftly and accurately rectify the vehicle’s deviation angle within the specified threshold. Following adjustments made by the leveling and height control algorithm, the vehicle body promptly returns to the preset level state and designated height. The leveling control system holds broad applicability in intelligent agriculture, logistics handling, off-road equipment, and other domains, presenting significant practical utility.

Gain scheduled internal model control based on the dynamic sliding mode method for the water level of nuclear steam generators

Abstract The Steam Generator (SG) is a crucial component of a nuclear power plant. Proper water level control in a nuclear steam generator is of great importance to ensure a sufficient cooling source for the nuclear reactor and to prevent damage to turbine blades. The water level control problem of steam generators has been a leading cause of unexpected shutdowns in nuclear power plants, which must be addressed for plant safety and availability. The control problem is challenging, particularly at low power levels due to shrink and swell phenomena and flow measurement errors. Furthermore, the dynamics of the steam generator vary as the power level changes. Therefore, there is a need to enhance the water level control system of the SG. In this paper, a Gain Scheduled Internal Model Control (IMC) based on the Dynamic Sliding Mode (DSMC) method is developed for the level control problem. The proposed method exhibits the desired dynamic properties throughout the entire output tracking process, independent of perturbations. Simulation results are presented to demonstrate the effectiveness of the proposed controller in terms of performance, robustness, and stability. The simulation results confirm the improvement in transient response achieved by using the proposed controller.

HK-SPSA based performance optimization method for steam generator liquid level control

Steam generator level control systems play a crucial role in ensuring safe, economical, and stable operation of nuclear power plants. However, traditional control systems exhibit limited efficiency in commissioning and are susceptible to human error. Additionally, traditional parameter tuning methods are typically experienced-based, cumbersome, and time-consuming, making it challenging to obtain optimal parameters. To address these issues, we propose a hybrid knowledge-guided improved simultaneous perturbation stochastic approximation algorithm (HK-SPSA) to optimize the control parameters of steam generator level control systems. Firstly, the algorithm utilizes iteration point adjacency information to approximate the current optimization process status and guide the adaptive adjustment of the iteration step size. Secondly, it utilizes composite gradient information generated by the estimated historical and current gradients to guide the optimization direction and the tuning of iteration step size. Simulation experiments have shown that HK-SPSA improves optimization performance and reduces the costs of optimization and adjustment compared to traditional methods.

Liquid Level Control System for Degassing Chamber of Vacuum Oil Filter Based on Fuzzy PID

This paper proposed a fuzzy PID control method to address the complexities associated with the inertia and nonlinear variations in liquid level control within the degassing chamber of vacuum oil filter. Tailored to meet practical control demands, a fuzzy control rule table was devised. This solution was simulated and applied in MATLAB/Simulink. The results indicated that, in comparison to classic PID, fuzzy PID exhibited faster adjustment speed and reduced overshoot, making it a more suitable option for vacuum oil filter applications.

Automatic Drum Filling Machine Equipped with Liquid Level Control System

Automatic Drum Filling Machine Equipped with Liquid Level Control System

USING FUZZY LOGIC CONTROLLER FOR A TWO- TANK LEVEL CONTROL SYSTEM

This paper presents a fuzzy logic controller for a two-tank level control system, which is a process with a dead time. The fuzzy controller is a proportional-integral (PI-like) fuzzy controller which is suitable for steady state behavior of the system. Transient behavior of the system was improved without the need for a derivative action by suitable change in the rule base of the controller. Simulation results showed the step response of the two-tank level control system when this controller was used to control this plant and the effect of the dead time on the response of the system.

Automatic Tracking Based on Weighted Fusion Back Propagation in UWB for IoT Devices.

The global population is progressively entering an aging phase, with population aging likely to emerge as one of the most-significant social trends of the 21st Century, impacting nearly all societal domains. Addressing the challenge of assisting vulnerable groups such as the elderly and disabled in carrying or transporting objects has become a critical issue in this field. We developed a mobile Internet of Things (IoT) device leveraging Ultra-Wideband (UWB) technology in this context. This research directly benefits vulnerable groups, including the elderly, disabled individuals, pregnant women, and children. Additionally, it provides valuable references for decision-makers, engineers, and researchers to address real-world challenges. The focus of this research is on implementing UWB technology for precise mobile IoT device localization and following, while integrating an autonomous following system, a robotic arm system, an ultrasonic obstacle-avoidance system, and an automatic leveling control system into a comprehensive experimental platform. To counteract the potential UWB signal fluctuations and high noise interference in complex environments, we propose a hybrid filtering-weighted fusion back propagation (HFWF-BP) neural network localization algorithm. This algorithm combines the characteristics of Gaussian, median, and mean filtering, utilizing a weighted fusion back propagation (WF-BP) neural network, and, ultimately, employs the Chan algorithm to achieve optimal estimation values. Through deployment and experimentation on the device, the proposed algorithm's data preprocessing effectively eliminates errors under multi-factor interference, significantly enhancing the precision and anti-interference capabilities of the localization and following processes.

Industrial Material Liquid Level Control System based on PLC

According to the requirements of an enterprise for liquid level control of glycerine, this paper changes the traditional liquid level control mode to PLC control, improves the reliability, safety and visualization of the whole working process, makes the transmission control system has strong function and high reliability, and can be applied to the industrial field when combined with hardware. Based on the configuration software MCGS and PLC simulation industrial material level control, through FX5U-A/D acquisition signal to change the liquid level in each tank, so that the industrial material level control simulation can be carried out. In addition, the control mode can be changed through the touch screen or the button on the MCGS engineering interface to achieve different controls, and the configuration screen can monitor most of the functions of the control system.

Parameter Optimization of Steam Generator Water Level Control System Based on Piecewise ARX Modeling

Parameter Optimization of Steam Generator Water Level Control System Based on Piecewise ARX Modeling

An Experimental Investigation of Various Control Systems for an Archimedes Screw Turbine in a Micro-Hydropower Plant

The control system for a micro-hydropower plant using an Archimedes screw turbine is the focus of this work. Three control systems were implemented based on a Barreda micro-hydropower plant (Spain) currently in operation: an optimal water level control (OWLC) system, a maximum power point monitoring (MPPT) system, and a water level control (WLC) system. The comparison was made using several assessment indicators: electricity production, micro-hydropower plant efficiency, and gearbox fatigue. The electricity production is similar in the OWLC and MPPT systems (energy gain +0.5%) and significantly lower in the WLC system (energy gain −12%). The efficiency of the micro-hydro plant is similar in the OWLC and MPPT systems (average efficiency gain +0.9%) and significantly lower in the WLC system (average efficiency gain −15%). The mechanical stress on the gearbox is similar in the OWLC and WLC systems and significantly higher in the MPPT system. It can be concluded that the OWLC system performs better as concerns the three assessment indicators used, followed by the MPPT system. The WLC system is not recommended for use, due to its low electricity production and low efficiency of the micro-hydropower plant.

Modeling and control scheme of the absorption machine of a solar cooling plant.

The article presents the modeling of an absorption machine and a low level control system necessary to ultimately control the cooling power demanded by air conditioning systems. The modeling of the components has been implemented in Simulink in order to obtain a simulator of an absorption-machine-based cooling plant for controller design purposes. In the simulator, the proposed refrigeration system presents control loops to maintain the output variables of the flow rates and temperatures in established references. Finally, the results of the simulation are presented, which show the behavior of the absorption machine system and support the good performance of the proposed low level control system.

GK-SPSA-Based Model-Free Method for Performance Optimization of Steam Generator Level Control Systems

The Steam Generator (SG) is a crucial component of a Nuclear Power Plant (NPP), generating steam to transfer heat from the primary loop to the secondary loop. The control performance of the Steam Generator Level Control System (SGLCS) plays a crucial role in the normal operation of the SG. To improve the system’s performance, the parameters of the control system should be optimized. However, the steam generator and its corresponding control system are highly complex, exhibiting nonlinearity and time-varying properties. Conventional parameter-setting methods mainly rely on engineers’ experience, and are laborious and time-intensive. To tackle the aforementioned challenges, a Model-Free Optimization (MFO) method based on Knowledge-informed Historical Gradient-based Simultaneous Perturbation Stochastic Approximation (GK-SPSA) is applied to the performance optimization of the steam generator level control system. The GK-SPSA algorithm is a variant of the traditional SPSA algorithm. The fundamental idea of this revised algorithm is to maximize the utilization of historical gradient information generated during the optimization process of the SPSA algorithm, with the aim of enhancing overall algorithm performance in a model-free optimization context. Based on the effective utilization of historical gradient information, the GK-SPSA algorithm exhibits two improvements over the SPSA algorithm. The first improvement is related to the recognition of the online optimization progress, utilizing the state of the optimization progress to dynamically adjust the optimization step size. The second improvement is related to gradient estimation compensation, employing compensation rules to enhance the accuracy of gradient estimation, thus improving the optimization efficiency. Through simulation experiments, it can be observed that there is not much difference in the final iteration values among the GK-SPSA, IK-SPSA, and SPSA methods. However, the iteration count of GK-SPSA is reduced by about 20% compared to SPSA and by 11.11% compared to Knowledge-informed SPSA (IK-SPSA). The results indicate that this method can significantly improve the efficiency of parameter tuning for the liquid level control system of a steam generator.

Metaverse-based Water Level Simulator for the Festo MPS PA Workstation

The compact workstation developed by Festo represents a bench-scale model for facilitating industrial process simulations in the laboratory and enabling students to study common control systems used in the industry directly. The latest development of the virtual Festo modular production system (MPS) process automation (PA) workstation has yet to be able to provide open access. In the virtual world, it needs interaction between the user, which still needs to be accommodated. This research attempts to develop a metaverse-based simulator of the Festo MPS PA workstation using the Roblox platform. This research focuses on designing a level control system, considering aspects such as the 3D model, control interface design, the implementation of system equations and controller algorithms, and the system’s response. The findings reveal Roblox’s potential in developing a virtual educational ecosystem for engineering, demonstrated by the design of an open-loop system with an average error of 11.4% compared to a real system. In the case of a closed-loop system with interactive PID control, the system response exhibits an average error of 8.03%.

Layered Composite Decoupling Control Based on Regional Dynamic Sparrow Search Algorithm

This paper addresses the issues of coupling and disturbances in a dual-tank water level control system within the context of process control in chemical water treatment at industrial facilities. In response to these challenges, a Layered Composite Decoupling Control system based on the Regional Dynamic Sparrow Search Algorithm (RDSSA-LCDC) is proposed. The utilization of an enhanced Regionally Dynamic Sparrow Search Algorithm (RDSSA) addresses the pitfalls of the Sparrow Search Algorithm (SSA), such as susceptibility to local optima and inadequate precision. RDSSA is employed for the parameter tuning of the system’s PID controller. Structurally, it incorporates a Hierarchical Composite Decoupling Control (LCDC) strategy, initially establishing a forward channel to construct an inner-layer decoupling model employing pre-feedback to rectify the lower-level system’s inputs, thereby mitigating inter-branch coupling. Subsequently, it develops an improved disturbance observer model based on pseudo-inverse compensation in the feedback channel, addressing conventional disturbance observer biases, and observing and suppressing system coupling and disturbances. Finally, within the dual-tank water level control system, various control schemes are simulated and compared, affirming the approach’s commendable decoupling, responsiveness, and disturbance rejection performance.

A novel fault detection and diagnostic Petri net methodology for dynamic systems

Faults can have significant, negative impacts on the operation and performance of simple and complex dynamic systems. Based on the integration of Bayesian network diagnostic features with Petri net formalism, the existing Bayesian-supported Petri net tool has demonstrated the flexibility of using the Petri net approach for diagnosing failure scenario of a dynamic system. However, studies on using the proposed hybrid Petri net approach for condition monitoring and early detection and diagnosis of single and multiple failures in a dynamic system with feedback control loops are yet to be investigated. Thus, this paper presents a methodology to address this research gap using the operation of a water tank level control system as a case study. The method combines the constructed Generalised Stochastic Petri Net (GSPN) model of the system operation with its corresponding fault diagnostic Petri net model, created using the proposed modified Bayesian Stochastic Petri Net (mBSPN) formalism. The GSPN model establishes the causal relationships between the system’s components and/or subsystems. It further identifies deviations in the sensor measurements of the observable process variables characterising the system operation. The information provided by the sensors in the system model are then inputted into the mBSPN model to diagnose the root cause of the observed deviations. The obtained results demonstrated the capability of using the proposed integrated Petri net methodology for system condition monitoring, early fault detection and diagnosis of single and multiple failures in a dynamic system with feedback control loops.

Studying the adequacy of the neural network level controller in the automated control system of an evaporator

The aim of the study is to substantiate the use of neural network control of beet juice level in an evaporator by evaluating the accuracy and adequacy of the model. This allows us to assess how well the model properties describe the course of the real process. The use of mathematical statistics methods is the most common way to test models for adequacy. In the automation scheme of level control, capacitive level gauges are used as a sensor. The actuators are pneumatic seat valves with a built-in throttle and an electropneumatic converter. The use of neural network controllers is found only in some specific cases of intelligent control of the evaporation process, and there are no data comparing the use of intelligent controllers with classical ones. In this paper, the Durbin-Watson d-criterion is used to assess the adequacy of the model. Statistical data on the behavior of the level control system circuits in different operating modes using intelligent and classical controllers were collected and a model of the evaporator unit operation was built. The advantage of the Durbin-Watson criterion is its simple and fast implementation, which does not require large economic and energy costs. The accuracy of the model was also evaluated. The static error of the control quality for the levels in the five enclosures of 25–65 % (in 10 % increments) is within the range of no more than 0,2 %. The proposed model of the evaporator station operation is generally characterized by high accuracy.

Fuzzy PID Controller Design for a Coupled Tank Liquid Level Control System

In industrial processes, the most important loop is the liquid-level control loop. The coupled tank system CT-100 becomes an essential apparatus for process control researchers. This paper introduces two controller techniques to control the water level in the second tank as a single input single output system. The PID controller is designed to control the linearized model, where the controller parameters are tuned using the Ziegler- Nichols tuning method. In addition, Fuzzy PID is designed based on adequate knowledge and experience. The proposed control approaches are simulated using MATLAB Simulink. Then, the obtained results using these controllers are compared in terms of time response specifications and the ITAE criterion. It is also, tested for step-change tracking signal and disturbance rejection. Finally, the simulation results showed that the Fuzzy PID controller has a robust performance.

Design of Double Tank Liquid Level Control System Based on Fuzzy PID

Liquid level is one of the main parameters in industrial production process control. There are many problems such as interference and delay in the dual capacity water tank. It is usually difficult to meet the strict production requirements with the conventional PID control scheme. The corresponding transfer function is firstly deduced through the material balance equation in this article. By testing, the performance of conventional PID needs to be further improved. Then build the fuzzy PID model in Matlab/simulink and carry out simulation verification. By comparing with the PID simulation effect, the results show that under fuzzy PID control, the overshoot of the system is effectively reduced and the adaptability is strong. It reflects that the control strategy has a good reference value.