A PID Tuning Approach for Inertial Systems Performance Optimization

In the practice of control the industrial processes, proportional-integral-derivative controller remains pivotal due to its simple structure and system performance-oriented tuning process. In this paper are presented two approaches for synthesis the proportional-integral-derivative controller to the models of objects with inertia, that offer the procedure of system performance optimization based on maximum stability degree criterion. The proposed algorithms of system performance optimization were elaborated for model of objects with inertia second and third order and offer simple analytical expressions for tuning the PID controller. Validation and verification are conducted through computer simulations using MATLAB, demonstrating successful performance optimization and showcasing the effectiveness PID controllers’ tuning. The proposed approaches contribute insights to the field of control, offering a pathway for optimizing the performance of second and third-order inertial systems through robust controller synthesis.

GA-BASED PID NEURAL NETWORK CONTROL FOR MAGNETIC BEARING SYSTEMS

In order to overcome the system non-linearity and uncertainty inherent in magnetic bearing systems, a GA（genetic algnrithm）-based PID neural network controller is designed and trained tO emulate the operation of a complete system （magnetic bearing, controller, and power amplifiers）. The feasibility of using a neural network to control nonlinear magnetic bearing systems with unknown dynamics is demonstrated. The key concept of the control scheme is to use GA to evaluate the candidate solutions （chromosomes）, increase the generalization ability of PID neural network and avoid suffering from the local minima problem in network learning due to the use of gradient descent learning method. The simulation results show that the proposed architecture provides well robust performance and better reinforcement learning capability in controlling magnetic bearing systems.

Implementation of Control Algorithms in Small Embedded Systems

This work describes how a control algorithm can be implemented in a small (8-bit) microcontroller for the main purpose of merging embedded systems and control theory in electrical engineering undergraduate classes. Two different methods for discretizing the control expression are compared: Euler transformation and bilinear transformation. The sampling rate’s impact on the algorithm is discussed and theoretical results are verified by an application to a temperature control system in a heating plant. Four control algorithms are compared: PID and PI algorithms discretized with Euler and bilinear transformation, respectively. It is shown that for the heating plant used in this work, a bilinear PI algorithm implemented in a small 8-bit microcontroller outperforms a commercial controller from Panasonic. It is also demonstrated that all the derived algorithms can be implemented using integer calculations only, obviating the need for expensive and time-consuming floating-point calculations. This work bridges the gap between control theory equations and the implementation of control systems in small embedded systems with no inherent floating-point processing power.

Design of the pressure regulation algorithm for active braking in vehicle ACC system

To develop the pressure control algorithm for active braking of adaptive cruise control（ACC） system,a test bench with real parts of the tested vehicle is built.With the dynamic analysis of the active braking actuators,it is demonstrated that different duty of pulse-width modulation（PWM） signals could control the pressure changing rate of the wheel cylinder.To obtain that signal,a modified proportional-integral-differential（PID） control algorithm is developed using the variable parameter method,the control value reset method,the dead zone method and the integral saturation method.Experimental results show that the delay and overshoot of the pressure response could be reduced considerably using the modified PID algorithm compared with the conventional one.The proposed pressure control algorithm could be used for the further development of the ACC＇s controller.

Research on Double Cascade Control Algorithm for Self-Balancing Two-Wheeled Vehicle

To solve the problem of self-balancing two-wheeled vehicle, this article presents double cascade PID control algorithm. This method reduces the coupling of balance control, speed control and direction control, because of the special system structure. This article successfully solved the sensor fusion of gyroscope and accelerometer by using Kalman filtering algorithm, and adding in fuzzy PID algorithm to improve the flexibility of the steering system, thus greatly improving the accuracy and response rate of the system.

Research on the application of digital power supply based on domestic FPGA

Purpose The digital controller for the accelerator magnet power supply typically employs a field-programmable gate array(FPGA)as the signal processing chip for executing digital processing of closed-loop control.Currently,FPGA chips are predominantly utilized in Intel or Xilinx products.To address the“key areas and stranglehold”issue pertaining to FPGA chips in accelerator power supply,we have devised a digital power supply prototype using a domestic FPGA chip and validated its feasibility in the upgrade project’s magnet power supply digital transformation plan for the Beijing Electron Positron Collider(BEPCII).Method A domestic FPGA chip from the Seal5000 SA5Z-30-D1 series by Xi’an ZhiDuoJing Microelectronics Co.serves as the core component for the design of a digital corrector magnet power supply to replace the existing analog controlled corrector power supply at BEPCII.The power supply’s digital control of the closed loop is achieved through the use of a hardware description language,and the digital controller hardware is constructed based on the original power supply power topology.Results and conclusions After conducting experiments and tests on the power supply prototype,we have successfully met the current operational requirements of the BEPCII corrector power supply,thus confirming the feasibility of utilizing domestic FPGA for digital application on accelerator power supply.

Design of variable-rate liquid fertilization control system and its stability analysis

Variable-rate technology(VRT)has been paid more attentions by farmers in an attempt to match inputs to local growing conditions efficiently.Farmers in every country are highly encouraged to adopt this practice rather than uniform-rate application(URA).However,the standard methods and design used to quantify application accuracy for VRT remain lacking.Therefore,a variable-rate liquid fertilization control system was designed to meet accurate fertilization demand.The designed control system could enable the real-time proportion and mixture of three kinds of liquid fertilizers,namely,N,P and K,in accordance with decision support subsystem.The task controller reads related information and sends such data to the control system,which is responsible for fertilization operation.The controller could realize liquid fertilizer adjusting through the electromagnetic flow control valves.A high-precision flow meter could measure the fertilization amount,which is sent as feedback to the controller to form a closed-loop control system based on the improved proportional-integral-derivative(PID)control algorithm that could enhance the stability and accuracy of precision variable-rate liquid fertilization control systems.Comparisons between the actual and planned application rates indicated good performance for both static and field experimental trials.Mathematical models and transfer functions for some functional modules were then constructed by classical theories to derive a system characteristic equation.To verify the static and dynamic performances,the control system was simulated using the Simulink module on Matlab.Results showed that the variable-rate fertilization was in accordance with the planned data and that the signal trace effect was good.The error was less than 5%for fertilization amount and fertilizer proportion,respectively,and the control response time was 6 s.