Simulation Of Control System Research Articles

Interdisciplinary Trends in the Reintegration of Organisms with Perceptron Units

Various artificial algorithms have emerged from imitating the behavior of primitive cells. Despite their independent development, these algorithms still have the potential to integrate with the intelligence of the primitive biological cells and control their behavior. Research on biologically inspired intelligence emerged earlier, with the goal of combining algorithms with the inherent intelligence of living organisms. When microbial behavior meets the requirements of the algorithm, such microorganisms can be used as a carrier for computation. This review analyzes the shortcomings of this approach and points out potential directions for development, including using existing structures inside cells to simulate control systems such as circuits, in order to construct cells that fully satisfy the needs of the algorithm. However, when using classical control systems to achieve the goal, it is necessary to construct a fairly complex internal cell structure, and this review analyzes the shortcomings of this approach. Subsequently, by analyzing recent research, this review points out the latest novel research direction, in which some scholars attempt to construct artificial cell structures to directly achieve the function of the algorithm by building low-implementation-difficulty internal control systems in cells. However, there are still some problems to be solved, and this review summarizes the relevant research and briefly discusses the current theoretical challenges.

Marine Pollution Simulation and Comparative Intervention Procedures Based on Case Scenario

Experience and evolving technology have made it possible to combat marine pollution in more effective ways. Apart from a lack of appropriate reaction resources in prior oil spill catastrophes, presently Turkiye has more potent ability. The objective of this research is to establish the efficiency of the response to marine pollution which might emerge in the Istanbul Strait with the presently available functionalities, as well as to offer suggestions over what operational and technical upgrades could be made to ramp up this effectiveness. PISCES II (Potential Incident Simulation Control and Evaluation System) oil pollution modelling and decision support system was utilized to fulfil the study's purpose. In the conclusion of the study, correlative statistics prove how to use assets in the intervention action to combat oil pollution in the Istanbul Strait, how surface vessels are employed during these operational processes, as well as the significance of the initial reaction speed.

A Combined Service Optimization and Production Control Simulation System

A Combined Service Optimization and Production Control Simulation System

Synchronization Control of Two Digital Hydraulic Cylinders Based on Cross-coupling

According to the problem that the displacement of a traditional digital hydraulic cylinder cannot be adjusted in real-time, a synchronous control algorithm for a double digital hydraulic cylinder is proposed based on the cross-coupling control strategy. AMESim simulation of the dual-cylinder synchronization control system shows that the control algorithm not only makes the digital hydraulic cylinder track the input signal accurately, but also improves robustness and synchronization performance.

Simulation Research on Ship-borne PMSM Speed Regulation Control System Based on Fuzzy PID Control

As the important actuator of ship-borne electromechanical equipment such as offshore cranes, the control system of Permanent-magnet synchronous motor (PMSM) is a complex system that features nonlinearity, time-varying parameters, and multi-variable coupling. Due to working in a swing environment, the ship-borne PMSM speed regulation control system is confronted with some problems, such as abrupt load change, external interference signals, motor parameters change, and given signals change frequently. To improve the control performance, this study designs the 2-dimensional Fuzzy PID controller and builds the control system simulation model with a double closed-loop structure in the MATLAB/Simulink. By comparing the control system under various simulation situations, the simulation findings demonstrate that the control system using the Fuzzy PID controller far outperforms the PID controller in terms of control indicators such as stability, tracking ability, and anti-disturbance ability, which can better adapt to working in swing environment.

Water injection control modelling by using model-based calibration

<p><span lang="EN-US">This study presents the development of water injection system for turbocharged spark ignition engine. The water injection control system is built for turbocharged spark ignition (SI) engine where water was injected at the intake port just before the throttle body. The data was collected from the simulation through the GT-Power software to determine the optimized injection output for the engine. Single-stage statistical engine responses and boundary models were established by using Model-Based Calibration Toolbox. Control system was built using Simulink and simulation tests were conducted based on the speed and throttle position as the variables. The highest value of brake torque achieved in the GT-Power simulation was taken as the base value to determine the injection amount. The mean value of the predicted injection was recorded at 12.29 g/s while the variance of the predicted injection to the optimized injection was below 1%. The control system was simulated with the set predicted injection and the standard deviation of the predicted injection was 1.18. The control system simulation recorded a low percentage of 0.04% variance to the optimized injection with the pulse width modulation signal. The control system is ideal to be constructed and tested on actual engine test bed.</span></p>

A Fuzzy Backstepping Attitude Control Based on an Extended State Observer for a Tilt-Rotor UAV

In order to overcome the influence of internal and external disturbances caused by rotor tilt motion and gust disturbance on the full flight mode control of a tilt-rotor unmanned aerial vehicle (UAV), a design method using fuzzy backstepping control based on an extended-state observer (FBS-ESO) is proposed. In this paper, fuzzy control is used to tune the parameters of the backstepping control law online, and the extended-state observer estimates the total disturbance of the controlled system to improve the controller’s robustness and anti-disturbance capability. This paper designs the attitude control system of a tilt-rotor UAV based on an FBS-ESO controller. The control performance of the FBS-ESO controller is tested in a hardware-in-loop simulation of the attitude control system. The simulation results show that changing the rotor tilt angle will destroy the stability of the traditional backstepping controller and active disturbance rejection controller (ADRC). In contrast, the FBS-ESO controller maintains good control performance. In addition, the performance of the FBS-ESO controller is not be significantly affected by adding external gust disturbance or changing the UAV parameters in the simulation. These disturbances significantly impact the traditional backstepping controller and ADRC. Therefore, the FBS-ESO controller has better anti-disturbance capabilities and robustness, as well as higher attitude control accuracy.

Simulation of Control System Based on New Electric Intelligent AN Toothbrush

This paper mainly introduces the simulation and Simulation of the processing effect of the new electric intelligent an toothbrush terminal based on ENBF156 chip. The system can detect the health of teeth in real time, connect their teeth with the Internet or GPRS network, and correctly transmit them to the toothbrush simulation control system and app. This simulation system gives full play to the data processing and real-time control functions of ENBF156 chip.

A Mathematical Modelling and Analysis of COVID-19 Transmission Dynamics with Optimal Control Strategy

We proposed a deterministic compartmental model for the transmission dynamics of COVID-19 disease. We performed qualitative and quantitative analysis of the deterministic model concerning the local and global stability of the disease-free and endemic equilibrium points. We found that the disease-free equilibrium is locally asymptotically stable when the basic reproduction number is less than unity, while the endemic equilibrium point becomes locally asymptotically stable if the basic reproduction number is above unity. Furthermore, we derived the global stability of both the disease-free and endemic equilibriums of the system by constructing some Lyapunov functions. If R 0 ≤ 1 , it is found that the disease-free equilibrium is globally asymptotically stable, while the endemic equilibrium point is globally asymptotically stable when R 0 > 1 . The numerical results of the general dynamics are in agreement with the theoretical solutions. We established the optimal control strategy by using Pontryagin’s maximum principle. We performed numerical simulations of the optimal control system to investigate the impact of implementing different combinations of optimal controls in controlling and eradicating COVID-19 disease. From this, a significant difference in the number of cases with and without controls was observed. We observed that the implementation of the combination of the control treatment rate, u 2 , and the control treatment rate, u 3 , has shown effective and efficient results in eradicating COVID-19 disease in the community relative to the other strategies.

Design and Simulation of an Intelligent Road Traffic Control System

Design and Simulation of an Intelligent Road Traffic Control System

Experience of virtual commissioning of a process control system for the production of high-paraffin oil

This work describes the experience in developing and testing software for oil industry automation control systems based on the simulation of technological processes and control systems combined in virtual reality, this approach is called virtual commissioning and is widely used in the world both to create automated process control systems and to simulate interactions between different systems.

Design of Gas Turbine Cooling System Based on Improved Jumping Spider Optimization Algorithm

The gas turbine cooling system is a complex MIMO system with a strong coupling, nonlinear, time-varying and large disturbance amplitude. In order to automatically control the target flow, target temperature and pipeline pressure, in this paper, the decoupler and regulator of a gas turbine cooling system are designed. Firstly, the working principle of a gas turbine cooling system and the coupling between the controlled variables of the system are analyzed. The decoupler of the system is designed by using the diagonal matrix decoupling method. The transfer function models of the coupling system are built through system identification, and the decoupling matrix of the system is calculated according to the diagonal matrix decoupling method and transfer function models. Then, the engine cooling control system simulation model is constructed and an improved jumping spider optimization algorithm is proposed. The parameters of the controller are optimized by the improved jumping spider optimization algorithm. Finally, the control system simulation is done and compared with the jumping spider optimization algorithm and the particle swarm optimization algorithm. The simulation results show that the improved jumping spider optimization algorithm is more suitable for the multivariable strong coupling nonlinear engine cooling system. For the flow and pressure control, the transient time and overshoot are reduced, and the steady-state error is less than 1%. For the temperature control, the result of the improved jumping spider optimization algorithm is more smooth, without overshoot, and almost does not exceed the set inlet water temperature. The overshoot, steady-state errors and transient time of the system have been improved, which proves the feasibility and significance of the improved jumping spider optimization algorithm by comparing the control performance and optimization time.

Rotor position angle control of permanent magnet synchronous motor based on sliding mode extended state observer

ABSTRACT To achieve fast, accurate control of the position angle of the rotor of permanent magnet synchronous motor (PMSM), traditional auto disturbance rejection control often has many adjustable parameters and complex tuning problems. Sliding mode control technology is introduced into the extended state observer (ESO) part of the auto disturbance rejection controller, and a new sliding mode approach law is designed based on several typical sliding mode approaches, which simplifies parameter tuning while retaining the original anti-interference performance of auto disturbance. In addition, the nonlinear state error feedback control law in active disturbance rejection control is enhanced to improve the component order PID control law, which can improve the response speed and robustness of the system, and prove the stability of the controller. Finally, the simulation of the PMSM rotor position control system based on the sliding mode ESO is carried out, and the results verify the validity of the method.

The Design and Simulation of Adaptive Cruise Control System

In this study, an Adaptive Cruise Control system is designed by using conventional Proportional Integral Controller (PID) and Model Predictive Controller (MPC). In the design, vehicle, acceleration, and deceleration models are constructed in a way to sim-ulate the real-life environment. The design and simulation were carried out through Matlab and Simulink. In order to investigate the effects of gains in the PID controller, several values for Kp, Ki, and Kd is tested. The simulation results illustrated that the gains Kp and Kd have negligible effects on the vehicle acceleration but the gain Ki has a substantial effect on the response of the ego car. The results of PID controller were compared with the results when the controller is replaced by MPC. It has been shown that the PID controller gives better results as compared to the MPC controller inde-pendent from Kp, Ki, and Kd values. Therefore, we can confidently state that the PID controller provides better responses in addition to its accessibility, simpler design, and cost advantages compared to the MPC controller.

Global optimization of hybrid AC/DC microgrid using HOMER and CPLEX

This work presents an idea about to design, simulation, and analysis of an operational control system in order to control and supervise the operations of a hybrid AC/DC microgrid (HMG) in the different operating modes (connected and islanded). The main task of this paper is concerned with the development and the implementation of a global optimization method for solving the problems of the energy crisis of HMG with an adequate control algorithm. The supervision system was developed in such a way that it coordinates when power should be generated by sources renewable energy sources (RES) such as PV array or wind turbine and when it should be produced by grid power in on-grid operation or with diesel generator (DG) in off-grid operation. This system is intended to maximize the use of the RES while limiting the use of the other emergency sources of energy (the utility grid and DG). The control simulation proves that the management system reduces the total cost of HMG thereby reducing the total cost of the RES. From the simulation results, the developed supervision system reduces the global operational hours of the HMG and the proposed algorithm respects the optimization in real-time operation under different constraints.

Application of Three-Dimensional Unbalanced Coordinate Transformation to Stand-Alone Four-Leg Voltage-Source Inverter

Three-phase four-leg voltage-source inverter has been extensively investigated in recent years for its compactness, small size, and high efficiency, and it has been proved to be the best solution for providing transformer-less neutral connection to three-phase asymmetric loads. The main purpose of this article is to apply 3-D unbalanced coordinate transformation to the four-leg inverter, which supplies stand-alone asymmetric loads, to maintain the balance of the output capacitor voltages, and obtain simpler control structure and better control performance. First, a double closed-loop PI control structure can be designed based on the Clarke and Park transformations. Second, the phases and amplitudes of the capacitor voltages are locked based on the 3-D unbalanced coordinate transformation. Furthermore, the Clarke transformation oriented on the inductor currents is replaced by a 3-D unbalanced coordinate transformation, and the corresponding unbalance indices are continuously adjusted according to the unbalance indices of the capacitor voltages, so as to recover the capacitor voltages to the balanced condition. The simulation and experimental results of the whole control system for the four-leg inverter are provided in the end, so as to verify the feasibility and effectiveness of the 3-D unbalanced coordinate transformation for application to the power electronic systems.

Design and Simulation of Satellite Attitude Control Algorithm Based on PID

According to the tasks of mapping and reconnaissance, the satellite needs to adjust its attitude and keep its attitude stable when it is in orbit. Firstly, the kinematic model and dynamic model of satellite attitude are established.Then the digital simulation of satellite attitude control system is built based on the mathematical model of satellite attitude, in which the control modules use PID controller and fuzzy PID controller respectively. Finally, the steady-state performance and dynamic performance of the two controllers are compared and analyzed.The experimental results show that both fuzzy PID control and fuzzy PID control can be used as effective means of attitude control.Both of them have high precision, fast speed and good steady-state performance to achieve the desired attitude. Fuzzy PID control also has the ability of self-tuning controller parameters, which makes the control process smoother.

Design and Simulation of Multichannel Dynamic Measurement Control System

The circuit system designed in this paper uses FPGA and single-chip microcomputer as the main chips. It uses VHDL language programming and performs functional simulation and verification of the core control program through ModelSim software, and finally, a storage-type dynamic measurement and control system with one-to-multiple channels, adjustable trigger modes, and optional sampling frequency is realized. At the same time, the system is further optimized in terms of power consumption and volume. The storage measurement and control system can successfully record eight-channel dynamic voltage signals, and the relative error of the experimental results is less than 2% through the simulation trigger experiment and Hopkinson bar experiment loading.

Towards the Optimal Performance of Washing Machines Using Fuzzy Logic

Washing machines (WMs) are common household appliances that help to save time and effort used in brushing and washing clothes. It is a common practice to use manually operated WMs, and based on their uses, WMs are classified into top and front open cloth washing machines, which operate based on an automatic control mechanism. In this paper, we present the design and simulation of an Arduino fuzzy logic-based WM control system, with an emphasis on improvement in its operating algorithm. Simulations were performed to determine the optimal time the WM takes to wash clothes, the maximum number of clothes the WM can wash per time, the acceptable dirtiness level of cloths, and the type of clothes that the machine can wash. The number of clothes to be washed, the degree of dirtiness, and the type of clothes govern the fuzzy logic control process adopted by the WM. The output voltage of the WM varies as the degree of dirtiness of the water varies from 0 to 1.95 V for very dirty water output from washed clothes and varies from 4 to 4.89 V for low-contaminated water. Another constraint considered was the load current, which increased as the number of clothes increased. The WM’s operation time is determined by the amount of voltage and load current used during its operation. As a result, the control of the WM is dependent on the dirtiness level of the clothes and the amount of load.

Taekwondo Trajectory Tracking Based on Multitarget Detection Algorithm

In order to further improve the effect of fuzzy PID controller applied to joint robot trajectory tracking control, a Taekwondo trajectory tracking method based on multitarget detection algorithm is proposed in this study. Firstly, a fuzzy PID controller for trajectory tracking of joint robot is designed. Secondly, considering the two optimization objectives of controller output torque and trajectory tracking control deviation, an improved multiobjective PSO algorithm is designed to optimize the membership function and fuzzy rules of fuzzy PID controller. Finally, the multiobjective PSO algorithm and the improved multiobjective PSO algorithm are used to optimize the trajectory tracking fuzzy PID controller. The vector sets of the two optimization objectives are obtained, and the optimization results are compared and analyzed. The simulation results show that the simulation step length is t = 0.01 s, and the total simulation time is 10 s. Using the controller, the simulation values and output torque values of each joint angle at each time can be obtained, which are used to calculate the two objective function values in the optimization algorithm. According to the process, the optimization algorithm parameters are set, and the control simulation system designed above is run to complete the improved multiobjective PSO optimization of the trajectory tracking fuzzy PID controller of the joint robot. Conclusion. The improved multiobjective PSO algorithm has better nondominated solution set, which verifies the effectiveness and superiority of the algorithm to optimize the robot trajectory tracking fuzzy PID controller.