Fuzzy self-tuning PID control of the operation temperatures in a two-staged membrane separation process

A two-staged membrane separation process for hydrogen recovery from refinery gases is introduced. The principle of the gas membrane separation process and the influence of the operation temperatures are analyzed. As the conventional PID controller is difficult to make the operation temperatures steady, a fuzzy self-tuning PID control algorithm is proposed. The application shows that the algorithm is effective, the operation temperatures of both stages can be controlled steadily, and the operation flexibility and adaptability of the hydrogen recovery unit are enhanced with safety. This study lays a foundation to optimize the control of the membrane separation process and thus ensure the membrane performance.

Design and simulation about a self-Tuning fuzzy-PID controller

Fuzzy logic has attracted the attention of structural control engineers during the last few years,because fuzzy logic can handle nonlinearities,uncertainties,and heuristic knowledge effectively and easily.In this paper,a self-Tuning fuzzy-PID control method which used the technology of the fuzzy control and PID control unified is presented.These techniques can visualize the results and processes for structure stress.These techniques will also provide convenience for engineers and users,and have high practical values.The MATLAB simulation result shows that the system precision and the efficiency are very high and the static error is small,and robustness was also validated.

Self-adaptive PID controller of microwave drying rotary device tuning on-line by genetic algorithms

The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and with multivariable nonlinear interaction of microwave and materials. The conventional PID control strategy incorporated with optimization GA was put forward to maintain the optimum drying temperature in order to keep the moisture content below 1%, whose adaptation ability included the cost function of optimization GA according to the output change. Simulations on five different industrial process models and practical temperature process control system for selenium-enriched slag drying intensively by using IMDRDWM were carried out systematically, indicating the reliability and effectiveness of control design. The parameters of proposed control design are all on-line implemented without iterative predictive calculations, and the closed-loop system stability is guaranteed, which makes the developed scheme simpler in its synthesis and application, providing the practical guidelines for the control implementation and the parameter design.

Development of seam tracking system with ultrasonic sensor using self-tuning fuzzy control

One kind of the SAW seam tracking system with contactless ultrasonic sensor is presented in this paper. The new contactless ultrasonic sensor for seam tracking and the working principle of the seam tracking with the sensor are introduced. Based on the experiments, the optimal values of the fuzzy control parameters α and k 3 are defined by means of the off line adjusting method. Because the self tuning fuzzy control is adopted in the seam tracking system, the overshoot of the system is restrained, the steady state error is reduced, and the system's response speed is improved effectively. The results of the SAW seam tracking experiments show that this system's tracking accuracy is up to ±0.5 mm and the system can satisfy the requirements of the engineering application.

Stabilization of CSTR w ith Self-tuning Sliding Mode Controller Using T-S Fuzzy Linearization

A self-tuning reaching law based sliding mode control(SMC)theory is proposed to stabilize the nonlinear continuous stirred tank reactor(CSTR).T-S fuzzy logic is used to build a global fuzzy state-space linear model.Combing the traits of SMC and CSTR,three fuzzy rules can meet the requirements of controlled system.The self-tuning switch control law which can drive the state variables to the sliding surface as soon as possible is designed to ensure the robustness of uncertain fuzzy system.Lyapunov equation is applied to proving the stability of the sliding surface.The simulations show that the proposed approach can achieve desired performance with less chattering problem.

A Design of a PID Self-Tuning Controller Using LabVIEW

In this paper a trial has been made to design a simple self-tuning LabVIEW-based PID controller. The controller uses an open-loop relay test, calculates the tuned parameters in an open loop mode of operation before it updates controller parameters and runs the process as a closed-loop system. The controller reacts on a persistent offset error value as a result of load disturbance or a set point change. Practical results show that such a controller may be recommended to control a variety of industrial processes. A GUI was developed to facilitate control-mode selection, the setting of controller parameters, and the display of control system variables. GUI makes it possible to put the controller in manual or self-tuning mode.

Adaptive Self‐Tuning Fuzzy Controller for a Soft Rehabilitation Machine Actuated by Pneumatic Artificial Muscles

Pneumatic artificial muscles (PAMs) have the highest power to weight and power to volume ratios of any actuator. Therefore, they can be used not only in rehabilitation engineering, but also as actuators in robots, including industrial and therapy robots. Because PAMs have highly nonlinear and time‐varying behavior associated with gas compression and the nonlinear elasticity of bladder containers, achieving excellent tracking performance using classical controllers is difficult. An adaptive self‐tuning fuzzy controller (ASTFC) including adaptive fuzzy sliding mode control (AFSMC) and functional approximation (FA) was developed in this study for overcoming the aforementioned problems. The FA technique was used to release the model‐based requirements and the update laws for the coefficients of the Fourier series function parameters were derived using a Lyapunov function to guarantee control system stability. The experimental results verified that the proposed approach can achieve excellent control performance despite external disturbance.

Robust PID Controller Design on Quantum Fuzzy Inference: Imperfect KB Quantum Self-Organization Effect-Quantum Supremacy Effect

The new method of robust self-organized PID controller design based on a quantum fuzzy inference algorithm is proposed.The structure and mechanism of a quantum PID controller(QPID)based on a quantum decision-making logic by using two K-gains of classical PID(with constant K-gains)controllers are investigated.Computational intelligence toolkit as a soft computing technology in learning situations is applied.Benchmark’s simulation results of intelligent robust control are demonstrated and analyzed.Quantum supremacy demonstrated.

Development of an Enhanced Self-Tuning RBF-PID Controller for Achieving Higher Energy-Efficient Process Control

Proportional, integral and derivative (PID) control strategy has been widely applied in heating systems in decades. To improve the accuracy and the robustness of PID control, self-tuning radial-basis-function neural network PID (RBF-PID) is developed and used. Even though being popular, during the control process both of PID and RBF-PID control strategy are inadequate in achieving simultaneous high energy-efficiency and good control accuracy. To address this problem, in this paper we develop and report an enhanced self-tuning radial-basis-function neural network PID (e-RBF-PID) controller. To identify the superiority of e-RBF-PID, following works are conducted and reported in this paper. Firstly, four controllers, i.e., on-off, PID, RBF-PID and e-RBF-PID are designed. Secondly, in order to test the performance of the e-RBF-PID controller, an experimental water heating system is constructed for being controlled. Finally, the energy consumption for the four controllers under the three control scenarios is investigated through experiments. The experimental results indicate that in the three scenarios, the developed e-RBF-PID controller outperforms on-off controller as having higher accuracy. Compared to the PID controller, the e-RBF-PID controller has higher speed in control, and the experimental results show that settling time savings is between 12.6% - 49.0%. Most importantly, less control energy consumption is obtained if using the e-RBF-PID controller. It is found that up to 28.5% energy consumption can be saved. Therefore, it is concluded that the proposed e-RBF-PID is capable of enhancing energy efficiency during control process.

APPLICATION OF FUZZY CONTROL METHOD WITH SELF-TUNING FACTOR IN JIGGER'S DISCHARGING

Adopting the strategy of fuzzy control with self tuning factor within whole universe of discourse, a kind of fuzzy control method for jigger discharging is put forward. This method has many advantages over the conventional PID controller in terms of response speed, stability and robustness. It is effective to restrain the jig bed from over thick or empty, and the stability of the bed is markedly improved. The good results are obtained in factory tests.

AUTOMATIC TUNING OF PID CONTROLLERS IN THE THERMAL POWER UNIT LOAD CONTROL SYSTEM

A method of measuring the interactions in a multivariable control sys-tem(MVCS)in time domain is defined in this paper.An intelligent decoupling com-pensator is designed in terms of the concept of fuzzy control,so that the auto-tuningof controllers’ parameters in a 2×2 MVCS can be turned into that of two independentsingle-loop control systems(SLCS).The method presented in the paper has success-fully been used in a simulation experiment on the automatic tuning of a coordinatedcontrol system(CCS)in the drum-boiler turbogenerating unit(DBTU)and the simu-lation results axe satisfactory.

Motion Control of Omnidirectional Mobile Platform based on Fuzzy PID

The omnidirectional mobile platform has three degrees of freedom that make it widely applicable to all areas of industry, while the Mecanum wheel has the disadvantages wheel omnidirectional mobile platform is always difficult in of large vibration, the trajectory precision of Mecanum the omnidirectional mobile platform. To control the trajectory of the omnidirectional mobile platform better, this paper proposes a fuzzy self-tuning PID control model, through establishing the motion model of omnidirectional mobile platform in Adams software, then combined with Simulink simulation, analysis of fuzzy PID controller to improve the accuracy of the speed control of omnidirectional mobile platform, improve the control method of a precise trajectory of the omnidirectional mobile platform motion.

Neural Model-Based Self-Tuning PID Strategy Applied to PEMFC

This paper illustrates the benefits of a self-tuning PID strategy applied to a proton exchange membrane fuel cell system. Controller parameters are updated on-line, at each sampling time, based on an instantaneous linearization of an artificial neural network model of the process and a General Minimum Variance control law. The self-tuning PID scheme allows managing nonlinear behaviors of the system while avoiding heavy computations. The applicability, efficiency and robustness of the proposed control strategy are experimentally confirmed using varying control scenarios. In this aim, the original built-in controller is overridden and the self-tuning PID controller is implemented externally and executed on-line. Experimental results show good performance in setpoint tracking accuracy and robustness against plant/model mismatch. The proposed strategy appears to be a promising alternative to heavy computation nonlinear control strategies and not optimal linear control strategies.

基于Fuzzy推理的自调整PID控制器

本文提出一种新的基于Fuzzy推理的PID自整定控制器．它利用Fuzzy推理，对系统所处的不同状态实现PID参数的在线自动整定，使系统在任何状态下，都能得到比传统PID更好的控制效果和更强的鲁棒性．仿真结果也证明了这一点．

Fuzzy PID 控制起动机性能测试系统的研究(英文)

针对起动机性能测试系统，设计由标准ＰＩＤ控制器和模糊自整定机构组成的模糊自整定ＰＩＤ控制器．其模糊自整定机构通过调整参数α来在线整定ＰＩＤ 参数以求控制的快速性和鲁棒性．实际运行结果表明起动机性能测试系统检测精度高，快速性好，可靠性高。

Fuzzy-PID控制算法在永磁电磁混合悬浮系统中的应用

永磁电磁混合磁悬浮平台控制系统是典型的非线性迟滞系统,单纯采用经典PID控制或Fuzzy控制难以满足系统的快速性、稳定性、鲁棒性等要求.虽然可以采用PID控制算法结合分段调节PID控制参数的所谓非线性PID来进行控制,但是这种整定方法由于采用了分段控制,在每个分段内PID参数不再变化,在受到较大扰动时控制作用可能会不及时,从而导致吸死现象的发生.针对以上问题,提出采用Fuzzy控制和PID控制相结合的Fuzzy-PID控制算法,在常规PID调节器的基础上运用模糊推理思想,根据不同的偏差、偏差变化率对PID参数进行自校正.仿真结果表明,系统具有较好的动静态性能,满足混合磁悬浮系统的要求.

基于Fuzzy-PID的大功率UPS智能充电系统设计

给出了大功率不间断电源(UPS)的充电电路系统结构,设计出模糊自整定PID控制器。同时,给出了利用Matlab中Simulink仿真工具来实现模糊控制器的设计方法。仿真和实验结果表明,该控制器与常规PID相比,提高了系统的适应能力,改善了系统的动态性能和静态性能。

Fuzzy自调整PID的Smith预估主汽温控制系统

针对火电厂锅炉主汽温被控对象的大迟延、模型不确定性,设计了Fuzzy自调整PID参数的Smith预估主汽温控制系统。运用MATLAB对系统在多种工况下进行了仿真,结果表明所设计的控制系统在控制品质、鲁棒性方面明显优于常规的Smith预估控制系统。

基于Matlab的2种Fuzzy-PID控制器的设计与仿真

针对电温控制,提出2种Fuzzy-PID控制方式Fuzzy-PID阈值控制和Fuzzy-PID参数自整定控制,运用仿真软件Matlab实现这2种Fuzzy-PID温度控制器的设计与仿真.Fuzzy-PID阈值控制器选用给定温度偏差值作为阈值,阈值以上的大偏差范围内采用模糊控制,温差小于阈值时采用PID控制;Fuzzy-PID参数自整定控制器先由模糊控制策略得到自适应的PID参数KP,KI,KD,再采用这个改进的PID控制器来控制全局系统.仿真结果表明2种Fuzzy-PID控制器都具有良好的动态和稳态性能.

参数自整定Fuzzy-PID在液奶杀菌系统的应用研究

介绍了液奶杀菌的工艺流程,针对在液奶杀菌系统中传统的温度PID控制所存在的控制精度低,PID参数无法根据工况在线调整等问题,提出了将模糊控制与经典PID控制结合起来的参数自整定模糊PID控制算法,对传统PID温度控制系统进行了优化处理,并以西门子PLC为控制器通过查表法实现了此模糊控制算法。为了检验系统的性能指标,通过MATLAB软件对系统进行了仿真实验,仿真结果表明在液奶杀菌温度控制系统中,参数自整定模糊PID控制相比于经典的PID控制系统控制精度更高,响应速度更快,鲁棒性更好。