Adaptive Fuzzy Proportional Integral Sliding Mode Control for Two-Tank Interacting System

This paper presents an adaptive fuzzy proportional integral sliding mode control (AFPISMC) for two-tank interacting system (TTIS). In order to maintain the desired liquid level of the TTIS and meet the reference values for attenuated chattering problems, this paper proposes a combination of a sliding mode control (SMC) with a proportional integral (PI) sliding surface and a fuzzy inference system. Fuzzy logic and the universal approximation theorem of fuzzy systems are used to approximate the uncertain function in the PISMC. The stability of the control system is proved by the Lyapunov theory. The simulation results of the proposed method in MATLAB/Simulink were compared to a fuzzy control, a sliding mode control with conditional integrals, a fuzzy-PID control, and a conventional PID control. The comparison results showed that the proposed controller was most effective when the rising time reached 0.2375 s, the percent of overshoot was 0%, the steady state error converged to zero, the settling time was 0.4612 s, and chattering was reduced

Adaptive Sliding Mode Control Based on Fuzzy Logic and Low Pass Filter for Two-Tank Interacting System

An adaptive sliding mode control (SMC) based on fuzzy logic and low pass filter is designed in this research. The SMC is one of the most widely accepted robust control techniques. However, the main disadvantage of the SMC is chattering phenomena, which inhibits its usage in many practical applications. Fuzzy logic control has supplanted conventional techniques in many applications. A major feature of fuzzy logic is the ability to express the amount of ambiguity in individual perception and human thinking. In this study, a fuzzy inference system is applied to approximate the function in the SMC law. A low pass filter is used to reduce chattering phenomena around the sliding surface. The stability of the control system is proved by the Lyapunov theory. The proposed controller is tested to position tracking control for two-tank interacting system. This system has been applied in process industries like petroleum refineries, chemical, paper industries, water treatment industries. Simulation results in MATLAB/Simulink show that the proposed algorithm is more effective than the sliding mode control, sliding mode control using conditional integrators and fuzzy control without steady-state error, the overshoot is 0 (%), the rising time achieves 2.187 (s) and the settling time is about 3.9133(s)

Adaptive Fuzzy Proportional Integral Sliding Mode Control for Two-Tank Interacting System

This paper presents an adaptive fuzzy proportional integral sliding mode control (AFPISMC) for two-tank interacting system (TTIS). In order to maintain the desired liquid level of the TTIS and meet the reference values for attenuated chattering problems, this paper proposes a combination of a sliding mode control (SMC) with a proportional integral (PI) sliding surface and a fuzzy inference system. Fuzzy logic and the universal approximation theorem of fuzzy systems are used to approximate the uncertain function in the PISMC. The stability of the control system is proved by the Lyapunov theory. The simulation results of the proposed method in MATLAB/Simulink were compared to a fuzzy control, a sliding mode control with conditional integrals, a fuzzy-PID control, and a conventional PID control. The comparison results showed that the proposed controller was most effective when the rising time reached 0.2375 s, the percent of overshoot was 0%, the steady state error converged to zero, the settling time was 0.4612 s, and chattering was reduced

Design And Performance Evaluation A Sliding Mode Control Based On The K Observer For A Three Tank Non-Interacting System

A sliding mode control (SMC) based on the K observer for a three tank non-interacting system is designed and evaluated in this paper. This system is important in modern process control since it can potentially improve product quality and enhance economic benefits. The SMC controller is designed to ensure that the actual liquid level tracks the desired in a finite time. The K observer is used to estimate the speed and acceleration signal, and realize sliding mode control only by using the position signal. The Lyapunov theory is chosen to prove the stability of the control system. The simulation results of the proposed method in MATLAB/Simulink were compared to an optimal controller tuning of a PI controller based on Skogestad’s tuning method, Cohen coon based tuning and Internal Model Control, an optimal PIDA controller with model uncertainty by Cuckoo Search, a fuzzy logic controller, a PID-Fuzzy logic controller. The comparison results showed that the proposed controller was more effective when the rising time reached 2.1521s, the percent of overshoot was 0%, the steady state error converged to zero, the settling time was 3.8577s

Adaptive PID sliding mode control based on new Quasi-sliding mode and radial basis function neural network for Omni-directional mobile robot

This article designs a PID sliding mode controller based on new Quasi-sliding mode (PID-SMC-NQ) and radial basis function neural network (RBFNN) for Omni-directional mobile robot. This is holonomic vehicles that can perform translational and rotational motions independently and simultaneously. The PID-SMC is designed to ensure that the robot's actual trajectory follows the desired in a finite time with the error converges to zero. To decrease chattering phenomena around the sliding surface, in the controller robust term, this paper uses the tanh (hyperbolic tangent) function, so called the new Quasi-sliding mode function, instead of the switch function. The RBFNN is used to approximate the nonlinear component in the PID-SMC-NQ controller. The RBFNN is considered as an adaptive controller. The weights of the network are trained online due to the feedback from output signals of the robot using the Gradient Descent algorithm. The stability of the system is proven by Lyapunov's theory. Simulation results in MATLAB/Simulink show the effectiveness of the proposed controller, the actual response of the robot converges to the reference with the rising time reaches 307.711 ms, 364.192 ms in the x-coordinate in the two-dimensional movement of the robot, the steady-state error is 0.0018 m and 0.00007 m, the overshoot is 0.13% and 0.1% in the y-coordinate, and the chattering phenomena is reduced

A multi-microcontroller-based hardware for deploying Tiny machine learning model

The tiny machine learning (TinyML) has been considered to applied on the edge devices where the resource-constrained micro-controller units (MCUs) were used. Finding a good platform to deploy the TinyML effectively is very crucial. The paper aims to propose a multiple micro-controller hardware platform for productively running the TinyML model. The proposed hardware consists of two dual-core MCUs. The first MCU is utilized for acquiring and processing input data, while the second is responsible for executing the trained TinyML network. Two MCUs communicate to each other using the universal asynchronous receiver-transmitter (UART) protocol. The multi-tasking programming technique is mainly applied on the first MCU to optimize the pre-processing new data. A three-phase motors faults classification TinyML model was deployed on the proposed system to evaluate the effectiveness. The experimental results prove that our proposed hardware platform was improved 34.8% the total inference time including pre-processing data of the proposed TinyML model in comparing with single micro-controller hardware platform

Early detection of slight bruises in apples by cost-efficient near-infrared imaging

Near-infrared (NIR) spectroscopy has been widely reported for its useful applications in assessing internal fruit qualities. Motivated by apple consumption in the global market, this study aims to evaluate the possibility of applying NIR imaging to detect slight bruises in apple fruits. A simple optical setup was designed, and low-cost system components were used to promote the future development of practical and cost-efficient devices. To evaluate the effectiveness of the proposed approach, slight bruises were created by a mild impact with a comparably low impact energy of only 0.081 Joules. Experimental results showed that 100% of bruises in Jazz and Gala apples were accurately detected immediately after bruising and within 3 hours of storage. Thus, it is promising to develop customer devices to detect slight bruises for not only apple fruits but also other fruits with soft and thin skin at their early damage stages

Design of a smart doorbell for a leader’s office with availability status notification and visitor recognition features

Smart doorbells have become a critical component of smart homes and modern offices. However, a smart doorbell, particularly designed for a leader’s office, has not been introduced. In this study, a smart doorbell is developed for a leader’s office. The system includes an application that allows availability status notification on the doorbell module and voice communication with the visitor from inside the office based on a private Wi-Fi network without an Internet connection to prevent the leader from potential privacy and security issues. It also features a live video capture of the visitor with face recognition by implementing a MobileNet model. In training and testing this model, 1,549 free face images of 125 people were augmented to generate training, validation, and testing datasets of 9,185, 2,500, and 5,000 face images, respectively. An additional authentication testing dataset of 1,068 AI-generated face images was also used to evaluate the system’s False Acceptance Rate (FAR). A high confidence level of 0.945 was selected for the developed MobileNet model to obtain zero FAR and high accuracy, recall, and F-score values of 0.960, 0.960, and 0.978, respectively. Therefore, the proposed doorbell could be used for an office leader, showing potential use for biometric authentication

Deep Learning Approach for Forecasting Water Quality in IoT Systems

Global climate change and water pollution effects have caused many problems to the farmers in fish/shrimp raising, for example, the shrimps/fishes had early died before harvest. How to monitor and manage quality of the water to help the farmers tackling this problem is very necessary. Water quality monitoring is important when developing IoT systems, especially for aquaculture and fisheries. By monitoring the real-time sensor data indicators (such as indicators of salinity, temperature, pH, and dissolved oxygen - DO) and forecasting them to get early warning, we can manage the quality of the water, thus collecting both quality and quantity in shrimp/fish raising. In this work, we introduce an architecture with a forecasting model for the IoT systems to monitor water quality in aquaculture and fisheries. Since these indicators are collected every day, they becomes sequential/time series data, we propose to use deep learning with Long-Short Term Memory (LSTM) algorithm for forecasting these indicators. Experimental results on several data sets show that the proposed approach works well and can be applied for the real system

Effect of Coating Thickness on Fatigue Behavior of AISI 1045 Steel with HVOF Thermal Spray and Hard Chrome Electroplating

The effects of coating thickness on the fatigue lives of AISI 1045 steel shaft-bending specimens with WC-10%Co-4%Cr high-velocity oxygen fuel (HVOF) coatings and hard chrome electroplated coatings under cyclic loading conditions are investigated. Residual stress distributions of the HVOF-coated layer and the hard chrome-plated layer were measured. During cyclic fatigue testing, cracks are initiated near the interface between the HVOF coating and the steel substrate and propagate through the substrate to cause final fracture based on experimental results. For the specimens with hard chrome-plated coatings, the fatigue crack is initiated near the top of the coating, propagates through the coating, and then grows in the thickness direction of the steel substrate to cause final fracture. As the coating thickness of the HVOF-coated specimens increases, the fatigue strength of the specimens increases, which can be attributed to the fact that the magnitude of the compressive residual stress near the interface between the substrates and the HVOF coatings is higher when the coating thickness gets higher. As for the hard chrome-plated specimens, the fatigue strength is deteriorated when the coating thickness is increased. The microcrack density in the hard chrome coatings increases with the coating thickness and, therefore, may result in the decreased fatigue strength