Liquid Level System Research Articles

Advanced control parameter optimization in DC motors and liquid level systems

In recent times, there has been notable progress in control systems across various industrial domains, necessitating effective management of dynamic systems for optimal functionality. A crucial research focus has emerged in optimizing control parameters to augment controller performance. Among the plethora of optimization algorithms, the mountain gazelle optimizer (MGO) stands out for its capacity to emulate the agile movements and behavioral strategies observed in mountain gazelles. This paper introduces a novel approach employing MGO to optimize control parameters in both a DC motor and three-tank liquid level systems. The fine-tuning of proportional-integral-derivative (PID) controller parameters using MGO achieves remarkable results, including a rise time of 0.0478 s, zero overshoot, and a settling time of 0.0841 s for the DC motor system. Similarly, the liquid level system demonstrates improved control with a rise time of 11.0424 s and a settling time of 60.6037 s. Comparative assessments with competitive algorithms, such as the grey wolf optimizer and particle swarm optimization, reveal MGO’s superior performance. Furthermore, a new performance indicator, ZLG, is introduced to comprehensively evaluate control quality. The MGO-based approach consistently achieves lower ZLG values, showcasing its adaptability and robustness in dynamic system control and parameter optimization. By providing a dependable and efficient optimization methodology, this research contributes to advancing control systems, promoting stability, and enhancing efficiency across diverse industrial applications.

Design and implementation of the fractional-order controllers for a real-time nonlinear process using the AGTM optimization technique

AbstractSpherical tanks have been predominantly used in process industries due to their large storage capability. The fundamental challenges in process industries require a very efficient controller to control the various process parameters owing to their nonlinear behavior. The current research work in this paper aims to propose the Approximate Generalized Time Moments (AGTM) optimization technique for designing Fractional-Order PI (FOPI) and Fractional-Order PID (FOPID) controllers for the nonlinear Single Spherical Tank Liquid Level System (SSTLLS). This system features a large dead time, and its real-time modeling generally represents a Single Input Single Output (SISO) model. However, in practice, the derived SISO model is often a First Order Plus Dead Time (FOPDT) model, necessitating an effective controller to maintain the tank’s steady-state level. In this research, the proposed AGTM method, based on the conventional Proportional Integral (PI) and Proportional Integral Derivative (PID) controllers, is compared with the FOPI and FOPID controllers for the nonlinear SSTLLS. The performance of these controllers is contrasted using metrics such as Integral Squared Error (ISE) and Integral Absolute Error (IAE), as well as time-domain characteristics containing Rise time, Peak time, Settling time, Peak overshoot, and Steady-state error. The implementation of the aforementioned controllers is done in simulation and real-time employing the MATLAB software environment and the Data Acquisition (DAQ) device National Instrument NI-DAQmx 6211. The simulation and experimental results demonstrate the exceptional performance of the designed Fractional-Order controllers based on the proposed method which offers an increased degree of freedom despite the more complex design process.

A Novel Approach to Robust PID Autotuner for Overdamped Systems: Case Study on Liquid Level System

This paper proposes and validates an automatic control tuning methodology based on initial frequency response. This approach facilitates the design of robust PID controllers for overdamped systems characterized by S-shaped step responses. In the prior autotuner, which is inherently robust, the critical frequency value is determined via the relay test, while process frequency response and its derivative at this frequency are found using the sine test. Our novel approach offers a fully automated calculation for these parameters based solely on the step response test (i.e., minimal information from the process), eliminating the need for additional calculations by relay and sine tests. For this aim, it estimates these values employing the first order plus dead time models. Firstly, five step response methods are introduced to ascertain the model parameters. Secondly, three alternative estimation methods for the critical frequency of the system are proposed through (i) solving a nonlinear equation, (ii) employing a linear approximation, and (iii) using a power regression. Lastly, the model parameters are then employed to calculate the system frequency response and its derivative at the critical frequency. The remaining design steps are the same as in the initial robustness-based autotuner. In the simulation studies, two types of overdamped systems are considered. The critical frequency estimation values obtained from three estimation methods are compared to each other. Additionally, the impact of the step response methods and the proposed estimation methods within the novel approach on system response and control signal are investigated. The designed controllers use a new approach to the initial autotuner and are implemented on a two-tank liquid-level system. The experimental outcomes are in accordance with the simulation results, confirming the validity and compatibility of the findings. Quantitative performance metrics are used to evaluate the effectiveness of the designs comprehensively.

Non-smooth fixed-time state feedback stabilization of uncertain switched systems with output constraints.

In this paper, non-smooth fixed-time state feedback stabilization of output-constrained uncertain switched systems has been investigated. First, to deal with the output constraints implicitly, a tangent-type barrier Lyapunov function (Tan-BLF), which degenerates into a quadratic function as the output constraints tend to infinity, is constructed deliberately. Then, the fixed-time state feedback control scheme for the output-constrained uncertain switched systems is established with remoulding the technique called adding a power integrator (AAPI). The upper bound of the settling time does not depend on the initial state and the arbitrarily small settling time can be obtained by just adjusting the specific parameters. The proposed method is operated in a unified framework, because it can tackle the cases for the uncertain switched systems with/without output constraints without requiring changes of switched controllers structure. At last, the effectiveness of the method is verified by a numerical simulation and a two-tank liquid-level system.

Fuzzy Backstepping Control of Industrial Liquid Level System

Fuzzy Backstepping Control of Industrial Liquid Level System

A Fast Finite-Time Adaptive Stabilizing Strategy of Uncertain Nonlinear System With Output Constraints and Its Application in Liquid-Level System

A Fast Finite-Time Adaptive Stabilizing Strategy of Uncertain Nonlinear System With Output Constraints and Its Application in Liquid-Level System

A miniaturized sensing system for liquid level and concentration based on piezoelectric micromachined ultrasonic transducers

This paper presents a system utilizing scandium-doped aluminum nitride (ScAlN) piezoelectric micromachined ultrasonic transducers (PMUTs) for simultaneous detection of liquid level and concentration. The PMUTs comprise a grid of 13×13 square units, covering an area of 2.8×2.8 mm2 in total. The PMUTs exhibit a resonant frequency of approximately 1 MHz in water and a beam angle of 30.16°, providing excellent sound field directivity. Additionally, a custom package housing with a cantilever baffle is designed to measure sound velocity in real time without modifying the container's structure. Finally, the fabricated PMUTs transceiver is combined with the TDC1000 ultrasonic sensing analog front-end to produce a high-precision liquid level and concentration detector. Glycerol and NaCl solutions are used as test samples. The system demonstrates measurement errors of ±0.5 % / ±1.1 % and ±0.5 mm / ±0.5 mm for concentration and liquid level, respectively, with resolutions of 0.323 % / 0.914 % and 0.077 mm / 0.070 mm. Compared with the related work results, the system based on PMUTs demonstrates advantages in miniaturization and high precision, making it particularly suitable for small-volume fluid containers, where sensor size and detection precision are crucial.

Controlling a Single Tank Liquid Level System with Classical Control Methods and Reinforcement Learning Methods

In this study, the control of the single tank liquid level system used in control systems has been carried out. The control of the single tank liquid level system has been performed with the classic PI, modified PI, state feedback with integrator action, and Q learning algorithm and SARSA algorithms, one of the artificial intelligence methods. The tank system to be modelled was carried out using classical physics, namely Newton's laws. Then, the mathematical model obtained of the system that are continuous model in time is acquired. The originality of the study; the non-linear liquid tank system is controlled by classical controllers and reinforcement methods. For this purpose, the system was firstly designed to model the system, then the system has been linearized at a specific point in order to design classic PI, modified PI, and state feedback with integral. After that, agents of the Q Learning algorithm and SARSA algorithms were trained for the system. Then the agents have controlled the single-level tank system. The results of the classic controllers and supervised controllers are contrasted with regard to performance criteria such as rising time, settling time, overshoot and integral square error. Consequently, Q learning method has produced 0.0804-sec rising time, 0.943 sec settling time and 0.574 integral square errors. So, Q learning algorithm has produced and exhibited more thriving and successful results for controlling single liquid tank system than PI, Modified PI, state feedback controllers and SARSA.

A dynamic optimal decoupling controller design for a multi-variable system with stability analysis: an algebraic approach

ABSTRACT This study describes the design and implementation of an algebraic approach for a dynamic optimal decoupling controller in a multi-variable liquid-level system. This method aligns with model-matching criteria and the frequency-matching technique. The prime objective of the proposed approach is to create a closed-loop feedback system using a PID controller that aligns with a user-defined linear system model in terms of both system dynamics and static behavioral response. To illustrate robust stability, the study incorporates multiplicative input and output uncertainty. Simulation results verify the efficacy of the proposed decentralized controller, presenting its effectiveness in achieving both set-point accuracy and disturbance attenuation. Furthermore, the study employs disk margin analysis to ascertain safe ranges for gain and phase margin.

The Design and Development of a Multifunctional Measuring System for Liquid Level and Temperature

The Design and Development of a Multifunctional Measuring System for Liquid Level and Temperature

Event-triggered control for [formula omitted]-normal switched stochastic nonlinear systems with asymmetric output constraints

This article focuses on the event-triggered control design for a class of p-normal switched stochastic nonlinear systems(SNS) with asymmetric output constraints. Firstly, in order to handle the pre-specified output constraints, a modified asymmetric tan-type common barrier Lyapunov function(CBLF) is put forward through the idea of piece-wise function. Combining the proposed CBLF with adding a power integrator technique, an event-triggered state-feedback controller is designed to ensure the switched SNS states asymptotically converge to zero in probability. Simultaneously, it is proved that the output will be constrained in the pre-specified bound and Zeno-behavior will not happen. Finally, a simulation of two-tank liquid-level system is given to indicate the effectiveness of the proposed method.

Optimal PID Controller Design for Liquid Level Tank via Modified Artificial Hummingbird Algorithm

To enhance controller performance, the optimization of control parameters has emerged as a critical research area. Among the array of optimization algorithms, the modified elite opposition-based artificial hummingbird algorithm (m-AHA) stands out for its ability to emulate behavioral strategies of hummingbirds and elite opposition-based technique. This paper, therefore, proposes m-AHA optimizer as a novel approach to optimize control parameters in a three-tanks liquid level system. By fine-tuning the parameters of proportional-integral-derivative (PID) controller, superior performance is achieved. Comparative evaluations with competitive algorithms, including the arithmetic optimization algorithm with Harris hawks optimization and covariance matrix adaptation evolution strategy, assess the m-AHA optimizer-based approach for three-tank liquid level system control. The ITAE (integral of time multiplied absolute error) performance index analyzes time domain and frequency metrics, revealing the outstanding performance of the m-AHA optimizer-based approach.

Optimizing Three-Tank Liquid Level Control: Insights from Prairie Dog Optimization

The management of chemical process liquid levels poses a significant challenge in industrial process control, affecting the efficiency and stability of various sectors such as food processing, nuclear power generation, and pharmaceutical industries. While Proportional-Integral-Derivative (PID) control is a widely-used technique for maintaining liquid levels in tanks, its efficacy in optimizing complex and nonlinear systems has limitations. To overcome this, researchers are exploring the potential of metaheuristic algorithms, which offer robust optimization capabilities. This study introduces a novel approach to liquid level control using the Prairie Dog Optimization (PDO) algorithm, a metaheuristic algorithm inspired by prairie dog behavior. The primary objective is to design and implement a PID-controlled three-tank liquid level system that leverages PDO to regulate liquid levels effectively, ensuring enhanced stability and performance. The performance of the proposed system is evaluated using the ZLG criterion, a time domain metric-based objective function that quantifies the system's efficiency in maintaining desired liquid levels. Several analysis techniques are employed to understand the behavior of the system. Convergence curve analysis assesses the PDO-controlled system's convergence characteristics, providing insights into its efficiency and stability. Statistical analysis determines the algorithm's reliability and robustness across multiple runs. Stability analysis from both time and frequency response perspectives further validates the system's performance. A comprehensive comparison study with state-of-the-art metaheuristic algorithms, including AOA-HHO, CMA-ES, PSO, and ALC-PSODE, is conducted to benchmark the performance of PDO. The results highlight PDO's superior convergence, stability, and optimization capabilities, establishing its efficacy in real-world industrial applications. The research findings underscore the potential of PDO in PID control applications for three-tank liquid level systems. By outperforming benchmark algorithms, PDO demonstrates its value in industrial control scenarios, contributing to the advancement of metaheuristic-based control techniques and process optimization. This study opens avenues for engineers and practitioners to harness advanced control solutions, thereby enhancing industrial processes and automation.

Global Prescribed-Time Stabilization of Input-Quantized Nonlinear Systems via State-Scale Transformation

The problem of global prescribed-time stabilization is reported in this paper for a kind of uncertain nonlinear system in power normal form. Compared with related work, the distinct characteristics of this study are that the system under consideration has an input-quantized actuator, and the prescribed time convergence of the system states is wanted. To meet these special requirements, a novel state-scaling transformation (SST) is firstly given to convert the prescribed-time stabilization of original systems to the asymptotic stabilization of the transformed one. Then, under the new framework of equivalent transformation, a quantized state feedback controller that ensures the achievement of the performance requirements is developed by using a power integrator (API) technique. Finally, the simulation results of a liquid-level system are provided to confirm the efficacy of the proposed approach.

Design and realization of a femtosecond-laser-inscribed fiber Bragg grating for accurate measurement of liquid level and liquid density

An exceptionally sensitive liquid level and density sensor system using Femtosecond-Laser-Inscribed Fiber Bragg Gratings is designed and demonstrated utilizing the basic Archimedes’ Law of Buoyancy. The sensor works based on principles of Archimedes’ law of buoyancy and basic strain sensitivity of Fiber Bragg Grating (FBG). A cylindrical mass of 22.5 cm long is suspended from one end of the FBG and whereas the other end of the fiber is fixed. The mass is partially immersed into the liquid under consideration to measure the liquid level as well as liquid density. Following Archimedes’ law of buoyancy, the relative weight of the suspended mass gets reduced and the corresponding shift in Bragg wavelength is measured using an interrogator connected at the fixed end of the sensor lead fiber. The relative weight of the immersed mass also depends on the liquid density. Therefore, a change in liquid density also is reflected by the shift in Bragg wavelength. The system can be calibrated to measure the accurate liquid level and liquid density. A liquid (water) level measurement sensitivity of 5.47 to 5.60 pm/mm is achieved using the system under three times of consecutive experiments which is very close to the simulated value (5.9 pm/mm). A density measurement sensitivity of ∼ 0.71 nm/(gm/cm3) is calculated in this system and experimentally achieved sensitivity is ∼ 0.7 nm/(gm/cm3). The LOD (limit of detection) was also found to be 1.008 gm/cc for the density measurement and the average error during the measurement was 0.0021 nm/(gm/cm3).It is also shown that the density measurement sensitivity is highly dependent on the amount of immersed portion of the suspended mass and more amount of immersed mass is desirable for better sensitivity.

Research on the Control Methods Based on Liquid Level System

Liquid level control is a common process control in industry, and its impact on production cannot be ignored. Liquid level control systems are used in various aspects of life, such as reservoirs, cisterns, river levels, etc. Among the common liquid level control systems, the double-volume water tank is a typical controlled object, which is widely used in industrial production. The control difficulty of has also increased due to its nonlinearity and delay. PID control can achieve satisfactory results in the face of accurate mathematical models and is still widely used in society. However, PID control is less effective when dealing with nonlinear systems that are difficult to describe accurately with mathematical models. For better level control, this paper designs a double-volume tank level control system with single-loop PID control, Cascade PID Control and fuzzy PID control based on PID control theory, and compares their control effects. This paper therefore concludes that the control effect of fuzzy PID control is better than the other two controls, and through experiments, we also find that fuzzy PID has decent adaptivity. This paper provides a certain research basis for the subsequent research on PID control, which has important theoretical significance and engineering value.

Long-term deflection monitoring of a box girder bridge with an optical-fiber, liquid-level system

In this study, a fiber Bragg grating (FBG)–differential settlement measurement (DSM) system was used to conduct 2-year monitoring of the vertical displacement of a prestressed concrete box girder bridge that had previously been damaged in an earthquake. This system is based on the principles of the hydrostatic liquid leveling of connected vessels, buoyancy, the equilibrium of forces, and the photoelasticity of FBGs. Specifically, a series of vertical displacements were measured at 42 observation points along the aforementioned bridge and used to determine its load-carrying capacity. Static vehicle loading tests were also conducted, and the displacement measurements of the FBG–DSM system were compared with those of conventional sensors and the displacement values simulated through finite-element simulation. The results reveal that the FBG–DSM liquid-level system has high potential for the inexpensive, long-term monitoring of bridges over long distances without requiring suitable environmental conditions, in situ visibility and intensive labor work.

Global Prescribed-Time Stabilization of High-Order Nonlinear Systems with Asymmetric Actuator Dead-Zone

This paper is concerned with the global prescribed-time stabilization problem for a class of uncertain high-order nonlinear systems (HONSs) with an asymmetric actuator dead-zone. Firstly, a new state-scaling transformation (SST) is developed for high-order nonlinear systems to change the original prescribed-time stabilization into the finite-time stabilization of the transformed one. The defects of the conventional one introduced in Song et al. (2017), which is unable to ensure the closed-loop stability behind a prespecified convergence time and a closed-loop system, which is only driven to the neighborhood of destination, is successfully overcome by introducing a switching mechanism in our proposed SST. Then, by using the adding a power integrator (API) technique, a state feedback controller is explicitly constructed to achieve the requirements of the closed-loop prescribed time convergence. Lastly, a liquid-level system is utilized to validate the theoretical results.

Implementation of PID controller for liquid level system using mGWO and integration of IoT application

Industrial automation is a multi-disciplinary study field that is constantly evolving. This research proposes IoT-based real-time liquid level monitoring and control in a single tank system. A PID controller with parameters sets using a novel modified Grey Wolf Optimization (mGWO) algorithm is used to manage the liquid level. The PID controller was then built on the ESP32 microcontroller module, and an android-based application was created utilizing the Blynk platform for IoT plant monitoring and control. The mGWO algorithm is used in MATLAB to optimize the Kp, Ki, and Kd values of PID controller parameters. The Arduino IDE is used to create the microcontroller programing as well as the interface for the Android application to the ESP32 microcontroller module. The results reveal that a single tank liquid level control system based on mGWO outperforms Ziegler–Nichols and SIMC tuning approaches. Furthermore, the adoption of an IoT application-based user interface boosts the plant’s control and monitoring flexibility.

DESIGNING OF THE AUTOMATED CONTROL SYSTEM OF LIQUID LEVEL IN THE TANK SIZES SPECIFIED

The article describes the components of the automated liquid level system in the vessel of known volume and their interaction.