Research Of Control Algorithm Research Articles

Control and physical verification of 6-DOF manipulator for power inspection robots based on expert PID algorithm

To enhance the performance of power inspection robots in intricate nuclear power stations, it is necessary to improve their response speed and accuracy. This paper uses the manipulator of the power inspection robot as the primary research object, and unlike previous control algorithm research, which only remained in the software simulation stage, we constructed a set of physical verification platforms based on CAN communication and physically verified the robotic arm’s control algorithm. First, the forward motion model is established based on the geometric structure of the manipulator and D-H parameter method, and the kinematic equation of the manipulator is solved by combining geometric method and algebraic method. Secondly, in order to conduct comparison tests, we designed PID controllers and expert PID controllers by utilising the expertise of experts. The results show that compared with the traditional PID algorithm, the expert PID algorithm has a faster response speed in the control process of the manipulator. It converges quickly in 0.75 s and has a smaller overshoot, with a maximum of only 6.9%. This confirms the expert PID algorithm’s good control effect on the robotic arm, allowing the six-degree-of-freedom robotic arm to travel more accurately and swiftly along the trajectory of the target point.

Research and Simulation of Improved Smith Prediction Algorithm Based on PLC

Aiming at the problem of excessive overshoot caused by large delay in temperature control process, based on the research of Smith predictive control algorithm, an improved gain adaptive Smith predictive control scheme is proposed, which can track the change of gain in real time. The simulation program is written based on TIA Botu and configuration software, and the operation results show that the improved scheme improves the lag effect and the adaptability to the model, and it still has good control quality after the parameter changes.

A trajectory tracking method based on robust model predictive control for a bionic ankle–foot aided by a tensegrity mechanism

In this article, a robust model predictive control method is investigated for settling the trajectory tracking problem of a bionic ankle–foot aided by a tensegrity mechanism. In order to achieve adaptive movement of the ankle–foot mechanism, a three-degrees-of-freedom spatial ankle–foot mechanism is designed by tensegrity, which is a spatial grid structure composed of springs and struts. Dynamic analysis is the basis of control algorithm research, and the dynamic model of the mechanism can be established by a Lagrangian equation. Then, a controller is proposed for tracking the trajectory of the ankle–foot mechanism under external disturbances. Combining rolling optimization and feedback correction, the controller can be defined as an optimization problem, by solving which the ankle–foot mechanism can be controlled to track the desired trajectory quickly. Furthermore, stability analysis is an essential part of predictive controller design, which can help to understand the operational mechanism of the control strategy. Numerical results demonstrate that the proposed approach improves trajectory tracking accuracy and avoids mechanism movement problems caused by disturbances.

Comparative analysis and the prospect of flight control strategies and performance of quadrotor UAV

Quadcopter UAVs are increasingly used for military and civilian applications such as surveillance, reconnaissance, pesticide spraying, and traffic monitoring due to their simplicity of operation, ease of attitude adjustment, and ability to take off and land vertically. The flight control system is the key to the aircraft's ability to perform flight tasks. However, when faced with external disturbances, obstacles, and uncertain parameters, traditional PID control is unable to meet the demands of complex flight tasks. Research on more advanced control strategies is the trend of future development. This paper surveys the flight control methods of quadrotor UAVs in the past two decades and classifies and introduces these methods one by one. Finally, the experimental feasibility of these methods is discussed, the advantages and disadvantages of these methods are briefly compared, and the future development trend of UAV flight control systems is analyzed. An important reference is provided for the development of quadrotor UAV flight control algorithm research.

A Survey of Intelligent Driving Vehicle Trajectory Tracking Based on Vehicle Dynamics

<div>Trajectory tracking control, as one of the core technologies of intelligent driving vehicles, determines the driving performance and safety of intelligent driving vehicles and has received extensive attention and research. In recent years, most of the research results of trajectory tracking control are only applicable to conventional working conditions; however, the actual operating conditions of intelligent driving vehicles are complex and variable, so the research of trajectory tracking control algorithm should be extended to the high-speed low-adhesion coefficient, large curvature, variable curvature, and other compound limit working conditions. This requires more consideration of the vehicle dynamics in the controller design. In this article, a comprehensive review of trajectory tracking control under extreme operating conditions is conducted from three levels: vehicle dynamics model, vehicle speed tracking (longitudinal motion control), and path tracking (transverse motion control), and the existing research results are analyzed and summarized to obtain the research trends and pain points and difficulties in each field. On this basis, the future outlook of trajectory tracking control is proposed, which is expected to provide some help and inspiration to the research workers in this field.</div>

Magnetic detection of underdriven USV track adaptive tracking in complex marine environment control algorithm research

In marine magnetic detection, in order to improve the accuracy of the measurement data of the field, to consider the impact of the storm interference environment, and to design a weakly driven USV tracking control system, it is necessary to drive the USV in a complex marine environment to determine the accuracy and stability of tracking. First, a 3-degrees of freedom mathematical model is built and decoupled by virtue of coordinate transformation to rely only on the absolute geographic velocity. Second, the variable forward-looking distance integral line-of-sight method is used to design the guidance law and stabilize the course tracking error. Moreover, sliding mode control is adopted to design the heading and velocity virtual control law and stabilize the heading angle and longitudinal velocity errors. Third, an adaptive observer is designed by introducing tracking errors to estimate the interference. The algorithm effectively improves the accuracy and reduces the oscillation during convergence. In the end, theoretical analysis and simulation experiments are carried out to confirm whether the proposed method is effective and advanced.

Primary frequency modulation of microgrid based on consistent droop control method

The rapid development of new energy sources gradually challenges the frequency stability of power systems. This article focuses on how to realize the frequency modulation control of the power grid under the fluctuation of the power grid. In order to improve the frequency stability of the microgrid system, based on the traditional droop control and consensus algorithm research, this paper proposes a microgrid primary frequency modulation based on the consistency droop control method. This control strategy improves the consistency of the progressive correction term to realize the control of the output of the energy storage unit, and improves the traditional droop controller to quickly restore the stability of the primary frequency. The root locus method verifies the effectiveness and feasibility of the control strategy. The simulation experiment verifies the frequency modulation ability of the proposed control strategy, which not only has a faster adjustment speed and response ability, but also has a strong anti-interference ability.

Green Building Design Based on 5G Network and Internet of Things System

An information-based and intelligent comprehensive energy consumption management system should not only collect, manage, and analyze energy consumption data but also monitor the environmental data inside the building, to manage and display the real energy consumption and internal environmental quality more effectively and reliably. In order to solve this problem, the design and construction of the front-end hardware of the energy consumption management system are proposed, mainly including the design of data acquisition node and data centralization end. The design of data acquisition node includes the selection of DSP controller, wireless communication module, and data acquisition module and the design of main circuit and peripheral circuits. The design of data centralization end includes the selection of its high-performance processor and the transplantation of Linux operating system. This paper only introduces the design and research of lighting control algorithm and applies fuzzy control algorithm to intelligent lighting. The fuzzy control system is introduced, and a fuzzy controller based on intelligent lighting is created. The fuzzy control rule table and fuzzy control query table of the intelligent lighting system are obtained through the fuzzy control algorithm. According to the basic rules of light intensity control, when the indoor light intensity is greater than the set value of light intensity, the LED lamps are turned off, so when e < 0 , the LED lamp is off and the PWM output value is 0. Therefore, when designing the fuzzy controller of intelligent lighting system, the basic domain of illumination intensity error E is 0500 , excluding the case that the indoor illumination intensity is greater than the set value of illumination intensity.

Research of control algorithm of traction drive of a mining dump truck using simulation models of motion

The paper describes control algorithms for a combined power plant made according to a sequential scheme for a 6x6 mining dump truck. The general approaches used in the development of control systems for similar power plants and transmissions are described. The methods of testing and simulation mathematical models used to analyze the operation of control systems for combined power plants are presented. As an example of control systems, the architecture of the developed system used for a mining dump truck is given. The developed control system and simulation model make it possible to analyze the behavior of the traction motor, energy storage device, transmission elements, and operational properties.

Iterative Learning-Based PID Precision Control for Sports Performance Analysis

Traditional function algorithms are contradictory to accuracy and performance. Therefore, taking into account the balance of accuracy and performance, the research of accuracy control-oriented mathematical function algorithms is of great significance to the design of high-precision and high-performance mathematical function algorithms. This paper is aimed at the design of mathematical function algorithm for precision control and has conducted indepth research on traditional PID control algorithm and fuzzy logic control theory. By analyzing the advantages and disadvantages of the two in practical applications, a parameter fuzzy cascade PID control is designed. The algorithm and its performance simulation and comparative analysis provide a theoretical basis for the follow-up accuracy control algorithm research and realization process. The accuracy control algorithm is then used to calculate and statistically analyze the sports performance including speed, strength (comprehensiveness and explosiveness), endurance, sensitivity, and coordination. The results show that the optimized function random point (nonextreme) test calculation accuracy is 99.5%, and the control accuracy improvement rate of the parameter fuzzy cascade PID control algorithm is about 18.24%. It has better control effect, stronger stability, and higher control accuracy. In the test of extreme points, the optimized test results are obviously better than those before optimization, which can effectively calculate sports results with high accuracy.

Research and application of cable pipeline robot for underground pipeline 3D simulation technology

In this paper, an underground cable intelligent pipeline detection robot is designed for the collection of pipeline position information. First of all, its mechanical structure is developed. In addition, the research of operation control algorithm is discussed. Finally, the digital image and pipeline space coordinate acquisition and communication methods are studied. In the design stage, the design scheme of each module is first determined and researched, designed and improved; then the integration and verification are carried out; finally, the field test and improvement are carried out; the prototype is produced and operated after meeting the conditions of trial operation, and the operation data are actively collected for improvement and improvement.

Development and research of adaptive control algorithm for road train lateral motion

In the presented work, the problem of control of a road train when it performs various maneuvers while moving along the highway is considered. An adaptive algorithm for controlling the lateral displacement of road train elements is proposed, based on the use of a PD-controller, the values of the coefficients of which depend on the current value of the longitudinal velocity. Computer simulation has been carried out, which has shown the correctness of the proposed algorithm.

Application Research of Intelligent Control Algorithm in Air Conditioning System

In order to reduce the energy consumption of HVAC system, we analyzed and compared modern intelligent control algorithm applied to HVAC control system, introduced the basic principles of fuzzy control, neural network and genetic algorithm, and analyzed the applicability of intelligent algorithm in HVAC system with engineering examples.

Research and Analysis of Nonlinear Model Identification Control Algorithm Based on Improved Neural RBF For Short Term Heat Load Forecasting of Heat Supply Network

Aiming at the mismatch between heat supply and demand of heating system, a nonlinear model identification control algorithm based on improved neural network for short-term heat load prediction of heat supply network is proposed by using the characteristics that heat load and temperature of heating system will not change dramatically in a short period of time By using MATLAB simulation, short-term heat load rolling prediction is realized. From the experimental results, this algorithm is better than the traditional RBF neural network in the prediction accuracy, and can accurately predict the trend of heat load.

Study on Design of the whole vehicle test platform and Modeling simulation for In-wheel motor electric vehicles

In order to meet the needs of actual vehicle research, the whole vehicle test platform for in-wheel electric vehicles is designed based on the idea of modularity. On the basis of the vehicle test platform, a joint simulation platform for in-wheel motor electric vehicles is established based on CarSim-Simulink, and simulation verification is carried out. The results show that the designed real-vehicle platform scheme is feasible, and the established simulation model has high accuracy, which can simulate the experimental vehicle well, accurately reflect the dynamic performance response of the vehicle, and provide a basis for further control algorithm research and verification.

Research of Wireless Congestion Control Algorithm Based on EKF

The random variation of bandwidth in wireless networks causes some significant challenges to the congestion control protocols based on bandwidth estimation. In this paper, a wireless congestion control scheme based on extended Kalman filtering and bandwidth (CSEKB) is proposed. The CSEKB can effectively perceive the bandwidth oscillation of wireless networks and distinguish the type of packet loss by establishing a noise perception factor. According to the congestion factor, the congestion control parameters are adjusted to correspondingly improve the performance of the wireless network. Moreover, the variation trend of the size of the congestion window presents a law of similar normal distribution curve, which has a certain degree of local symmetry. The CSEKB was implemented in Network simulator 3 (NS3) and compared with TCP Westwood (TCPW), CUBIC, and extended Kalman filtering-based bandwidth estimation (EBE). Through extensive simulation studies, the proposed CSEKB demonstrated the significant performance in wireless networks. First, the CSEKB can achieve congestion control based on the accurate prediction of available bandwidth, and improve average throughput and link utilization. In addition, the CSEKB has good fairness and friendliness compared with several other well-known congestion control methods.

Research and Practice of Neural Network PID Process Control Algorithm Based on Offshore Oil and Gas Platform

Since the exploitation of offshore oil and gas, after decades of development, it has gradually played an important role in world economic development. The central control system of offshore platforms is the core equipment of offshore oil and gas fields. Offshore platform industrial process control requires PID control most of the time. However, in practical applications, the tuning of PID parameters has not been well resolved. This paper combines neural network and PID control to build a neural network PID controller. At the same time, using OPC communication technology, the intelligent control PID algorithm is perfectly combined with the central control system, and the optimized model and parameters are applied to the actual control object of the oil level control of the offshore oil production platform, and the control effect is obtained satisfactorily.

Research and application of intersection traffic signal control algorithm based on vehicle location

This paper focuses on the optimising algorithms of signal timing of urban intersection combined with vehicle location using the platform of the new type of wireless electronic license plate system. With the traffic flow information obtained from the platform, a dynamic optimisation model with optimal control parameters of green light time of all four phases for single intersection is constructed. Then genetic algorithm is applied to obtain the satisfying signal timing scheme. In simulation examples, the proposed dynamic distribution method and the traditional time control method are compared. The results show that compared with the traditional time control method, in traffic rush hour, the genetic optimisation algorithm can reduce the waiting time by 23% with the same road vehicle capacity. At non-peak time, the proposed method can reduce the waiting time by 10%. Therefore, the introduced method can effectively reduce the total queue delay, and improve the traffic capacity of the intersection.

Thyristor voltage regulator control algorithm research

The article deals with the development and research of thyristor voltage regulator (TVR) dual-zone control algorithm in the electrical distribution networks 6-20 kV. The TVR control system hardware and software complex based on the algorithm was developed using LabVIEW and NI myRIO controllers. The transverse, longitudinal and longitudinal-transversal voltage regulation modes experimental research was conducted by the TVR prototype. The experimental research results confirmed the developed algorithm and its program realization effectiveness and efficiency.

Research and Application of Control Algorithm Based on Intelligent Vehicle

Cars are becoming more and more common in today’s society, and people are increasingly relying on cars when they travel daily. In developed countries, more than 50% of goods are transported by car, and passenger transportation is as high as 60%. Nowadays, it is necessary to refer to the per capita car holdings to evaluate whether a country’s industry is developed. Therefore, the number of cars is increasing day by day. At the same time, environmental pollution and traffic accidents caused by automobiles are becoming more and more serious. In the automotive engineering world, it is extremely urgent to solve a series of negative problems brought about by automobiles. Since the mid to late 1980s, many countries have begun to do some research on smart car systems. The smart car is a comprehensive system that integrates multiple levels of assisted driving and environmental awareness. With the progress of research, nowadays smart cars can complete the functions of roadblock recognition and security. This article is based on the research of intelligent cars, and conducts a more in-depth discussion on the control algorithms of smart cars, hoping to help the development of smart cars.