Self-adaptive Control System Research Articles

An artificial intelligence based self-adaptive dynamic process control system for enhancing in-situ bioremediation of benzene-contaminated groundwater – Part I methods

This study develops a new AI-based self-adaptive dynamic process control (SADPC) system based on stepwise inference combined with genetic algorithm optimization technologies, including a filtered-clustering inference prediction model (FCI simulator), a stepwise inference controller (SI emulator), a model predictive control controller, and two optimizers. This system effectively reflects the dynamics and complexity of the bioremediation process and controls the remediation system based on the feedback information. To achieve this goal, a statistical model for simulating the enhanced bioremediation process through the FCI simulator is proposed, which can predict the resulting contamination situation based on the previous contamination situation and pumping/injecting flow rate. Then a bridge is established through the SI emulator, which can generate a control action based on a given contamination situation. This suggested decision makers that guidelines and policies on remediation-oriented SADPC systems could be tentatively investigated, developed, and applied in the future effort.

Application of Adaptive Fuzzy Algorithm in Single-Chip Microcomputer Control System

Objective: In practical application, an SCM control system needs to respond to user instructions quickly and accurately, and at the same time needs to have robustness and adaptability to adapt to complex and changeable environments and working states. Therefore, how to improve the control accuracy and stability of SCM control systems, and how to adapt to the change of different working environments and working states, has become one of the important issues in the design and research of SCM control systems. Methods: Adaptive fuzzy algorithm, as a new control algorithm, has the advantages of simple structure, easy implementation and high precision, and has been widely used in many fields. On the basis of three kinds of fuzzy logic system framework, this paper analyzes the self-adaptive fuzzy algorithm single-chip microcomputer control system and carries on the corresponding performance test of the system by constructing an intelligent car. The testability test of single-chip microcomputer detection, hardware detection, algorithm recognition rate and system control rate is tested, respectively, to ensure the normal operation of the system. Conclusion: The microcontroller control system of fuzzy algorithm system is compared with that of traditional algorithm system in many aspects. The average error rate of the traditional algorithm system is 2%, while the average error rate of the fuzzy algorithm system is 0.8%. In other aspects, the fuzzy algorithm system is superior to the traditional system. For example, the fuzzy algorithm system has a 100% instruction recognition rate and a data processing speed of up to 1 second. According to the characteristics and requirements of the single-chip microcomputer control system, applying the adaptive fuzzy algorithm to the design of a single-chip microcomputer control system can effectively improve the control precision and stability of thesystem.

Dual-objective optimization strategy of self-adaptive transient pressure controller in water delivery engineering

ABSTRACT Controlling pressure impact of water hammer is an important guarantee for safe and stable running of pipeline systems. Previously, we proposed a spring self-adaptive auxiliary control (SAC) system to improve the pressure control ability of a surge tank. However, the working efficiency of the SAC system is affected by various parameters. A reasonable designing strategy becomes an urgent need to properly determine the parameters of the SAC controller. In this study, based on our calibrated numerical model, various transient responses of a SAC system with different parameters were further investigated. The latency response threshold and the spring orifice coefficient were identified to be the two most sensitive parameters that determine the controller working efficiency. Based on the objectives of reducing the in-pipe extreme pressure and in-tank water level fluctuation, an analytical dual-objective optimizing Method was proposed for application. The results demonstrated that the pressure control capability of SAC controller can be optimized by the proposed method.

Research on Pump-Controlled AGC Micro-Displacement Position Control of Lithium Battery Pole Strip Mill Based on Friction Compensation Control Strategy of Imoroved LuGre Pattern

Accurate mathematical patterning of friction has always been a significant research project in the domains of machinery and control, and has played a crucial role in the analysis, control and compensation of mechanical systems containing friction. For high-property electrohydraulic servo control systems, friction compensation is an urgent problem to be solved. The LuGre friction pattern can represent most frictional behaviors, but the LuGre friction pattern is piecewise-continuous, making it non-differentiable. Therefore, the question of how to combine the LuGre friction pattern, enhancing its tracking capacity and robust performance problem, to friction perturbation in hydraulic backstep devices is an important focus for research. In this study, the conventional LuGre friction pattern was enhanced using the continuous differentiability of a friction of rest pattern that laid the foundation of a smooth tangent function. Laying the foundation of an electrohydraulic servo pump-controlled hydraulic roll-gap thickness automatic control system (pump-controlled AGC) pattern, a self-adapting friction compensation controller laid the foundation of the enhanced LuGre pattern. The gradual tracking capacity was determined academically using conditions of parameter, uncertainty and nonlinear friction, and the position control precision of the pump-controlled AGC system was enhanced. The steady-state error of the self-adapting friction compensation control system, which laid the foundation of the enhanced LuGre pattern, attained ±0.1 μm, and the tracking capacity was better than the LuGre pattern control and the conventional PID control strategy at low input speed.

Design and Simulation-Based Optimization of an Intelligent Autonomous Cruise Control System

Significant progress has recently been made in transportation automation to alleviate human faults in traffic flow. Recent breakthroughs in artificial intelligence have provided justification for replacing human drivers with digital control systems. This paper proposes the design of a self-adaptive real-time cruise control system to enable path-following control of autonomous ground vehicles so that a self-driving car can drive along a road while following a lead vehicle. To achieve the cooperative objectives, we use a multi-agent deep reinforcement learning (MADRL) technique, including one agent to control the acceleration and another agent to operate the steering control. Since the steering of an autonomous automobile could be adjusted by a stepper motor, a well-known DQN agent is considered to provide the discrete angle values for the closed-loop lateral control. We performed a simulation-based analysis to evaluate the efficacy of the proposed MADRL path following control for autonomous vehicles (AVs). Moreover, we carried out a thorough comparison with two state-of-the-art controllers to examine the accuracy and effectiveness of our proposed control system.

Design of yarn tension self-adaptive control system on warp knitting machine

In order to realize the control of yarn dynamic tension, the warp knitting machine should be able to control the variation of tension values in different angles in one course during the knitting process. In view of the defects of controlling the let-off of warp beam, such as large yarn tension fluctuating and can’t accurately control the yarn tension at different angles within a course and so on, a specific kind of yarn tension self-adaptive control system on warp knitting machine has been developed. By analyzing the fluctuation of yarn tension combined with the looping mechanism motion law and process parameters of a warp knitting machine, the hardware and software platform of the system are designed; the velocity control strategy of the system is optimized; the quintic polynomial interpolation curve is calculated, and the double FIFO(first input first output) dynamic interpolation motion method is planned. Meanwhile, the self-adaptive control algorithm is designed to realize the self-adaptive control of yarn tension. From the analysis of the feedback yarn dynamic tension value curve and in comparison with the traditional let-off control system, the self-adaptive control system can reduce the yarn tension peak by at least 55.2% and the yarn tension fluctuation range by at least 51.6%. It is verified that the self-adaptive control system has an efficient performance of yarn dynamic tension regulation.

Investigation of partially expanded surge tank with self-adaptive auxiliary system controlling water hammer in pipelines

Intensive water hammer can cause pipe collapse in long-distance water transfer pipeline systems. Pressure control facilities like surge tank have been widely applied to help control the extensive pressure fluctuations. In our previous work, a kind of spring self-adaptive auxiliary control (SAC) system was proposed and demonstrated to have a significant improvement on pressure control capacity of a normal surge tank. In this study, an additional solution, a partially expanded structural treatment, was introduced to a conventional SAC surge tank to further improve its functional ability. The 1D numerical model was established in our in-house codes on FORTRAN. The dominant geometrical parameters were identified and quantitatively studied with various cases. According to the effects of the geometrical parameters, a designing protocol for searching the optimal solutions of partially expanded SAC surge tank was concluded. With the obtained optimal solutions, the proposed partially expanded SAC surge tank can perform a much better pressure control performance dealing with valve closure induced water hammer, compared with a conventional SAC surge tank as well as a normal surge tank.

Design and Test of a Straw-Clearing-Depth Self-Adaptive Control System of a Front-Mounted Seedbed-Preparation Device

In northeast China, most seedbed-preparation devices use the ground-wheel profiling method to ensure their operational stability. However, during the wide-width operation of the front-mounted seedbed-preparation device, the poor trafficability characteristics and the low profiling accuracy of the ground-wheel profiling mechanism result in unstable straw clearing depth, poor straw clearing quality, and the low operational efficiency of the seedbed-preparation device. In order to solve the above problems, a straw-clearing-depth self-adaptive control system of a front-mounted seedbed-preparation device was designed. The key structural design of the self-adaptive control system was completed through theoretical analysis. The performance test results of the self-adaptive control system showed that the lifting speed of the front-suspension mechanism was greater than 0.2 m/s in the manual button control mode, and the relative error between the target value and the actual value of the straw clearing depth was 10.8% under the self-adaptive profiling control mode. The three-factor and five-level quadratic regression orthogonal rotation center combination test method was adopted to conduct a parameter combination optimization test, with the machine operation speed, the operation depth of the straw clearing knife, and the straw covering amount as test factors, and the straw clearing rate, the qualified rate of operation depth, and the consistency of straw clearing between rows as evaluation indices. The results indicated that when the machine operation speed was 5~8.8 km/h, the operation depth of the straw clearing knife was 50 mm, the straw covering amount was 0.9~1.44 kg/m2, the straw clearing rate was ≥86%, the qualified rate of operation depth was ≥86%, and the consistency of straw clearing between rows was ≥83%. Field tests were carried out on the machine using operation speeds of 5 km/h, 6 km/h, 7 km/h, and 8 km/h under the conditions of an operation depth of the straw clearing knife of 50 mm and a straw covering amount of 1.2 kg/m2. The results showed that the straw clearing rate, the qualified rate of operation depth, and the consistency of straw clearing between rows were all within the optimized range under different machine operation speeds, which was basically consistent with the optimized results.

АДАПТИВНОЕ БЕСПОИСКОВОЕ УПРАВЛЕНИЕ НАСОСНЫМ КОМПЛЕКСОМ В УСЛОВИЯХ НЕСТАЦИОНАРНОСТИ

At operation of the automated pump complexes except for signal (coordinate) disturbances, there are the parametric disturbances, caused by non-stationarity of parameters of the given complex, in particular hydraulic resistances of the network, pump, inlet pipeline, and also fluctuations of parameters of the pumped liquid. The traditional approach to the automatic control of the output coordinates of the pump complex is reduced to the construction of systems with coordinate feedback and, as a rule, the regulation of speed of the centrifugal pump, which is inefficient for solving the problems of fast parametric control in the conditions of the relevant perturbations. The use of automated control of the bypass channel of pumping complex allows to provide more adequate processing of parametric disturbances, such as, in particular, vibration and elements of water hammer, as well as disturbances activating various undesirable hydraulic processes, such as cavitation and surge. The article considers the issues of building an adaptive search-less self-adaptive system to solve the problem of increasing the efficiency of working off the above parametric disturbances. Research objective: Investigation of the possibility of automatic processing of parametric disturbances when controlling the pumping complex by the bypass channel by constructing an adaptive system in the class of searchless self-adaptive control systems with a reference model. Materials and methods. The methods of mathematical modelling, in particular, the method of electron analogy, methods of the theory of automatic control with use of the apparatus of transfer functions, methods of the theory of adaptive control, methods of numerical modelling with use of the program complex SimInTech have been used to conduct research. Results. The synthesis of the control algorithm of the search-free self-adaptive system with a reference model to solve the problem of parametric perturbations in the pumping complex using the bypass channel has been made. Conclusion. The results of the study substantiate the possibility of building and using the adaptive searchless control system of the pumping complex for more effective automatic processing of parametric disturbances in order to compensate and reduce their negative effects.

Efficiency and Reliability Analysis of Self-Adaptive Two-Stage Fuzzy Control System in Complex Traffic Environment

In this paper, a self-adaptive, two-stage fuzzy controller is established to realize the real-time online optimization of traffic signal timing plan, which takes multimodels of transportation as the research object to analyze the reliability of the control system at the isolated urban intersection. In this system, the first stage calculates traffic urgency degree for all red phases and selects the red phase with maximum traffic urgency degree as the next green phase. The second stage determines whether to extend or terminate the current signal phase. Aiming at the problems of the parameters of membership functions empirical settings and insufficient response to the real-time fluctuation in traffic flow, the controller introduces an improved hybrid genetic algorithm to solve it and enable the controller to self-learn. Finally, a microsimulation platform is constructed based on the VISSIM and Python language to evaluate the efficiency and reliability of the controller under complex actual traffic conditions. Results showed that the average delay time per vehicle is reduced by 14.59%, while the average number of stops per vehicle is reduced by 0.71% compared with the traditional control method. Results indicate that the traffic signal timing plan generated by the controller can efficiently improve the intersection traffic capacity and has good efficiency and reliability under the condition of medium saturation and unsteady flow.

Self-Adaptive Control System for Hydroponics

Self-Adaptive Control System for Hydroponics

Self-Adaptive Control System for Additive Manufacturing Using Double Electrode Micro Plasma Arc Welding

Wire arc additive manufacturing (WAAM) has been investigated to deposit large-scale metal parts due to its high deposition efficiency and low material cost. However, in the process of automatically manufacturing the high-quality metal parts by WAAM, several problems about the heat build-up, the deposit-path optimization, and the stability of the process parameters need to be well addressed. To overcome these issues, a new WAAM method based on the double electrode micro plasma arc welding (DE-MPAW) was designed. The circuit principles of different metal-transfer models in the DE-MPAW deposition process were analyzed theoretically. The effects between the parameters, wire feed rate and torch stand-off distance, in the process of WAAM were investigated experimentally. In addition, a real-time DE-MPAW control system was developed to optimize and stabilize the deposition process by self-adaptively changing the wire feed rate and torch stand-off distance. Finally, a series of tests were performed to evaluate the control system’s performance. The results show that the capability against interferences in the process of WAAM has been enhanced by this self-adaptive adjustment system. Further, the deposition paths about the metal part’s layer heights in WAAM are simplified. Finally, the appearance of the WAAM-deposited metal layers is also improved with the use of the control system.

Automatic adaptation of a Solar Plant Intelligent Control System

The article continues the authors’ scientific research in the field of solar plant intelligent control system. This paper presents a developed on-line and off-line automatic adaptation methods which allow solar plant intelligent control system to adapt to rapid dynamic of insolation in real time and to seasonal insolation fluctuations during night time. The experimental results show that the proposed solar plant intelligent self-adaptive control system produced robust and rapid maximum power point tracking, as compared to a classical solar plant MPPT system based on Perturb & Observe or particle swarm optimization under seasonal fluctuations or rapid dynamic of insolation.

Self-Learning in Aerial Robotics Using Type-2 Fuzzy Systems: Case Study in Hovering Quadrotor Flight Control

This paper aims to design an enhanced self-adaptive interval type-2 fuzzy control system (ESAF2C) for stabilization of a quadcopter drone under external disturbances. Due to the ability to accommodate the footprint-of-uncertainty (FoU), an interval type-2 Takagi-Sugeno fuzzy scheme is employed to directly address the uncertainties in the nonlinear system. Sliding mode control (SMC) is utilized to optimize the upper and lower parameters of our proposed ESAF2C system using a self-tuning technique. The ‘Enhanced Iterative Algorithm with Stop Condition’ type-reducer is accommodated in the proposed design for its suitability to real-time implementation. To handle external disturbances and the ground effect in the closed-loop flight control system, a robustness term is added to the control effort. Lyapunov theory is applied to prove the stability of our closed loop control system. Moreover, we study the measurement noise effect for different levels of noise powers using our proposed technique. The efficacy of the proposed controller is investigated in a hovering quadcopter drone through numerical simulations and real-time flight tests in the presence of external disturbances. We highlight the disturbance rejection capability of our proposed control system with respect to type-1 fuzzy and conventional PID controllers.

Control of operating modes of an electroadsorption apparatus with a fixed layer of adsorbent

This paper provides a new scheme and algorithm of automated control of modes of operation of electroadsorption mass transfer apparatuses are presented on the example of a continuously operating electroadsorber with a fixed adsorbent layer. The required values of technological parameters and ranges of their regulation were obtained during the calibration of technological parameters at the stage of commissioning of the electric adsorption mass transfer equipment, also in an automated mode. A detailed description and algorithm of the stages of calibration of technological parameters of electroadsorption apparatuses with a fixed adsorbent layer are given in the second part of this work (Calibration of technological parameters of an electroadsorption apparatus with a fixed layer of adsorbent). The principle of automated control consists in self-adaptation of the mass exchange system to optimal productiveness, due to the imposition of adjustable electric fields of a given intensity on the adsorption processes and recognition of the most effective hydromechanical modes flow about of the surfaces of the adsorbent granules with a continuous gas phase flow using the turbulization index, that is, assessing the contribution of the inertial component of the structure filtration flow of a continuous gas phase flow through the adsorbent layer. A self-adaptive automated control system for electroadsorption processes will allow achieving the highest levels of gas emissions purification, with optimal energy costs for mass transfer processes, and will provide an opportunity to smooth out technological, large-scale and other factors inherent in specific mass transfer processes and apparatus designs. The most important feature of the developed self-adaptive control system is multi-functionality and a wide range of variation of operating modes from energy-saving optimal modes to emergency capture modes in cases of emergency emissions and unexpected bursts of concentrations of harmful captured substances from the continuous gas phase flow.

Building energy consumption prediction and energy control of large-scale shopping malls based on a noncentralized self-adaptive energy management control system

Central air conditioning is the main energy-consuming equipment in modern large-scale commercial buildings. Its energy consumption generally accounts for more than 60% of the electricity load of an entire building, and there is a rising trend. Focusing on reducing central air conditioning energy consumption is a first priority to achieve energy savings in modern large-scale commercial buildings. To study the main influencing factors of central air conditioning energy consumption in large shopping malls, in-depth collection and analysis of energy consumption data of Shenzhen Tian-hong shopping mall were considered, and the impact of factors such as the basic composition of central air conditioning, time, and Shenzhen weather on the energy consumption of shopping malls was considered. The most representative Buji Rainbow store of the Rainbow Group is used as the research object. The influencing factors of central air conditioning on its energy consumption are divided into air conditioning pumps, host 1–1, host 1–2, host 2–1, and host 2–2. The power consumption of the freezer and the eight impact indicators of time and weather in Shenzhen were constructed using Pearson correlation coefficients and a long short-term memory neural network method to construct a regression model of the energy consumption prediction of the mall building. The average relative deviation between the predicted energy consumption values and the measured energy consumption values is less than 10%, which indicates that the main influencing factors selected in this paper can better explain the energy consumption of the mall, and the obtained energy consumption prediction model has high accuracy.

СИСТЕМА АВТОМАТИЗИРОВАННОГО УПРАВЛЕНИЯ РЕЖИМАМИ РАБОТЫ ЭЛЕКТРОАДСОРБЦИОННЫХ АППАРАТОВ СЕЛЕКТИВНОЙ ОЧИСТКИ ГАЗОВЫХ ВЫБРОСОВ

The scheme and algorithm of automated control over the modes of operation of electric adsorption mass transfer devices for selective purification of gas emissions are presented on the example of a continuous electric adsorber with a moving bed of adsorbent. The principle of automated control consists in self-adaptation of the mass exchange system to the reference (optimal) performance indicators, due to the imposition of regulated electric fields of a given intensity on the adsorption processes and recognition of the most effective hydromechanical modes of washing sorbent surfaces with a continuous phase using the turbulization index, i.e., assessing the contribution of the inertial component of the structure filtration flow of a continuous phase through a sorbent layer. A self-adaptive system for automated control of electrical adsorption processes will allow achieving the highest rates of gas emissions purification, with optimal energy consumption for the implementation of mass transfer processes and will provide an opportunity to smooth out technological, large-scale and other factors inherent in specific mass transfer processes and apparatus designs. The most important feature of the developed self-adaptive control system is its multifunctionality and a wide range of variation of operating modes from energy-saving optimal to emergency capture modes in cases of emergency emissions and unforeseen surges in the concentrations of harmful trapped substances from the continuous gas phase flow.

Water Hammer Control Analysis of an Intelligent Surge Tank with Spring Self-Adaptive Auxiliary Control System

The water hammer can cause great risks in water supply pipe systems. A surge tank is a kind of general water hammer control device. In order to improve the behavior of the surge tank, a self-adaptive auxiliary control (SAC) system was proposed in this paper. The system can optimize the response of the surge tank according to the transient pressure. The numerical model and the matched boundary conditions were established to simulate the improved surge tank and optimize the SAC system. Then, various transient responses were simulated by the proposed model with different parameters set. The proposed system is validated by comparing the water hammer process in a river-pipe-valve (RLV) system with and without SAC. The results show that the SAC can greatly improve the water hammer control of the pipeline and the water level oscillation of the surge tank. With the SAC system, the required vertical size of the surge tank can be significantly reduced with the desired water hammer control function.

Self-adaptive method for performance enhancement of sweep-velocity-locked lasers

Optical frequency-domain reflectometry and frequency-modulated continuous wave (FMCW)-based sensing technologies, such as LiDAR and distributed fiber sensors, fundamentally rely on the performance of frequency-swept laser sources. Specifically, frequency-sweep linearity, which determines the level of measurement distortion, is of paramount importance. Sweep-velocity-locked semiconductor lasers (SVLLs) controlled via phase-locked loops (PLLs) have been studied for many FMCW applications owing to its simplicity, low cost, and low power consumption. We demonstrate an alternative, self-adaptive laser control system that generates an optimized predistortion curve through PLL iterations. The described self-adaptive algorithm was successfully implemented in a digital circuit. The results show that the phase error of the SVLL improved by around 1 order of magnitude relative to the one without using this method, demonstrating that this self-adaptive algorithm is a viable method of linearizing the output of frequency-swept laser sources.

Self-Adaptive Virtual Inertia Control-Based Fuzzy Logic to Improve Frequency Stability of Microgrid With High Renewable Penetration

Maintaining frequency stability of low inertia microgrids with high penetration of renewable energy sources (RESs) is a critical challenge. Solving this challenge, the inertia of microgrids would be enhanced by virtual inertia control-based energy storage systems. However, in such systems, the virtual inertia constant is fixed and selection of its value will significantly affect frequency stability of microgrids under different penetration levels of RESs. Higher frequency oscillations may occur due to the fixed virtual inertia constant or unsuitable selection of its value. To overcome such a problem and provide adaptive inertia control, this paper proposes a self-adaptive virtual inertia control system using fuzzy logic for ensuring stable frequency stabilization, which is required for successful microgrid operation in the presence of high RESs penetration. In this concept, the virtual inertia constant is automatically adjusted based on input signals of real power injection of RESs and system frequency deviations, avoiding unsuitable selection and delivering rapid inertia response. To verify the efficiency of the proposed control method, the contrastive simulation results are compared with the conventional method for serious load disturbances and various rates of RESs penetration. The proposed control method shows remarkable performance in transient response improvement and fast damping of oscillations, preserving robustness of operation.