Kinematics control of a pneumatic system by hybrid fuzzy PID

In a pneumatic system, normally, the piston can stop at only two terminal endpoints. In order to extend the capabilities of the system, this research is conducted to develop a kinematics control-based pneumatic system. Both position and velocity of the pneumatic piston are controlled in such a way that the controlled piston is able to move with the specified velocity to the target position. A hybrid of fuzzy and proportional-plus-integral-plus-derivative (PID) control algorithm is proposed in this paper as the solution. The control algorithm is separated into two parts: fuzzy control and PID control. The fuzzy controller is used to control the piston when the piston locates far away from the target position whereas the PID controller is applied when the piston is near the desired position. The development starts with designing of a position sensor to detect position information of the piston. The sensor-manipulating circuit consisting of potentiometer, inverting amplifier, summing amplifier, low-pass filter and analog-to-digital converter is then designed and realized. Next, the proposed hybrid of fuzzy and PID control is implemented and programmed on the microprocessor. In order to test performance of the system, settling time and steady-state error of five control algorithms – proportional (P) control, proportional-plus-integral (PI) control, proportional-plus-derivative (PD) control, PID control, and hybrid of fuzzy and PID control – are investigated. The results from the experiments show that the proposed hybrid of fuzzy and PID control gives the most satisfied settling time and steady-state error.     

Hybrid fuzzy proportional-integral plus conventional derivativecontrol of linear and nonlinear systems

This paper presents a new approach toward the optimal design of a hybrid proportional-integral-derivative (PID) controller applicable for controlling linear as well as nonlinear systems using genetic algorithms (GAs). The proposed hybrid PID controller is derived by replacing the conventional PI controller by a two-input normalized linear fuzzy logic controller (FLC) and executing the conventional D controller in an incremental form. The salient features of the proposed controller are as follows: (1) the linearly defined FLC can generate nonlinear output so that high nonlinearities of complex systems can be handled; (2) only one well-defined linear fuzzy control space is required for both linear and nonlinear systems; (3) optimal tuning of the controller gains is carried out by using a GA; and (4) it is simple and easy to implement. Simulation results on a temperature control system (linear system) and a missile model (nonlinear system) demonstrate the effectiveness and robustness of the proposed controller     

Analytical analysis and feedback linearization tracking control ofthe general Takagi-Sugeno fuzzy dynamic systems

The Takagi-Sugeno (TS) fuzzy modeling technique, a black-box discrete-time approach for system identification, has widely been used to model behaviors of complex dynamic systems. The analytical structure of TS fuzzy models, however, is unknown, causing at two major problems. First, the fuzzy models cannot be utilized to design controllers of the physical systems modeled. Second, there is no systematic technique for designing a controller that is capable of controlling any given TS fuzzy model to achieve the desired tracking or setpoint control performance. In this paper, we provide solutions to these problems. We have proved that a general class of TS fuzzy models is a nonlinear time-varying ARX (Auto-Regressive with eXtra input) model. We have established a simple condition for analytically determining the local stability of the general TS fuzzy dynamic model. The condition can also be used to analytically check the quality of a TS fuzzy model and invalidate the model if the condition warrants. We have developed a feedback linearization technique for systematically designing an output tracking controller so that the output of a controlled TS fuzzy system of the general class achieves perfect tracking of any bounded time-varying trajectory. We have investigated the stability of the tracking controller and established a condition, in relation to the stability of non-minimum phase systems, for analytically deciding whether a stable tracking controller can be designed using our method for any given TS fuzzy system. Three numerical examples are provided to illustrate the effectiveness and utility of our results and techniques     

Hemodynamic management of congestive heart failure by means of a multiple mode rule-based control system using fuzzy logic

A rule-based system was designed to control the mean arterial pressure (MAP) and the cardiac output (CO) of a patient with congestive heart failure (CHF), using two vasoactive drugs: sodium nitroprusside (SNP) and dopamine (DPM). The controller has three different modes, that engage according to the hemodynamic state. The critical conditions control mode (CCC) determines the initial infusion rates, and continues active if the MAP or the CO fall outside of the defined criticality thresholds: an upper and a lower boundary for the MAP and a lower boundary for the CO. Inside the boundaries the control is performed by noncritical conditions control modes (NCC's), which are fuzzy logic controllers. If the CO is within normal range and the MAP is close to the goal range, then the MAP is driven using only SNP, in a single-input-single-output mode (NCC-SISO). Otherwise the NCC multiple-input-multiple-output is active (NCC-MIMO). The goal values for the controlled variables are defined as a band of 5 mmHg for the MAP and 5 mL/kg/min for the CO, but there is little concern for this application if the CO is too high (i.e., in practical terms the CO only needs to achieve a necessary minimum rate). The NCC-MIMO includes a gain adaptation algorithm to cope with the wide variety in sensitivities to SNP. Supervisory capabilities to ensure adequate drug delivery complete the controller scheme. After extensive testing and tuning on a CHF-hemodynamics nonlinear model, the control system was applied in dog experiments, which led to further enhancements. The results show an adequate control, presenting a fast response to setpoint changes with an acceptable overshoot.     

Fuzzy Sliding-Mode Control of Active Suspensions

In this paper, a robust fuzzy sliding-mode controller for active suspensions of a nonlinear half-car model is introduced. First, a nonchattering sliding-mode control is presented. Then, this control method is combined with a single-input–single-output fuzzy logic controller to improve its performance. The negative value of the ratio between the derivative of error and error is the input and the slope constant of the sliding surface of the nonchattering sliding-mode controller is the output of the fuzzy logic controller. Afterwards, a four-degree-of-freedom nonlinear half-car model, which allows wheel hops and includes a suspension system with nonlinear spring and piecewise linear damper with dry friction, is presented. The designed controllers are applied to this model in order to evaluate their performances. It has been shown that the designed controller does not cause any problem in suspension working limits. The robustness of the proposed controller is also investigated for different vehicle parameters. The results indicate the success of the proposed fuzzy sliding-mode controller.      

电压模式Buck-Boost变换器变论域模糊PI控制

电压模式Buck-Boost变换器是一个典型的非最小相位系统。根据DC-DC Buck-Boost变换器的工作特性,运用状态空间平均法建立其小信号模型,据此设计PI控制器参数。Buck-Boost变换器是一个时变的非线性系统,传统PI控制难以达到最优的控制效果,由此采用模糊PI控制来规避PI控制的弊端。针对模糊PI控制在被控量变化较大时,控制精确度变差的问题,设计了模糊论域自适应伸缩变化的变论域模糊PI控制器,对Buck-Boost电路进行控制。通过Matlab/Simulink环境仿真,实验结果表明,变论域模糊PI控制具有更好的动态控制性能。     

A model-based algorithm for blood glucose control in Type Idiabetic patients

A model-based-predictive control algorithm is developed to maintain normoglycemia in the Type I diabetic patient using a closed-loop insulin infusion pump. Utilizing compartmental modeling techniques, a fundamental model of the diabetic patient is constructed. The resulting nineteenth-order nonlinear pharmacokinetic-pharmacodynamic representation is used in controller synthesis. Linear identification of an input-output model from noisy patient data is performed by filtering the impulse-response coefficients via projection onto the Laguerre basis. A linear model predictive controller is developed using the identified step response model. Controller performance for unmeasured disturbance rejection (50 g oral glucose tolerance test) is examined. Glucose setpoint tracking performance is improved by designing a second controller which substitutes a more detailed internal model including state-estimation and a Kalman filter for the input-output representation The state-estimating controller maintains glucose within 15 mg/dl of the setpoint in the presence of measurement noise. Under noise-free conditions, the model based predictive controller using state estimation outperforms an internal model controller from literature (49.4% reduction in undershoot and 45.7% reduction in settling time). These results demonstrate the potential use of predictive algorithms for blood glucose control in an insulin infusion pump     

基于双模糊控制器的水箱液位控制

针对工业锅炉自动控制系统中的水箱系统液位控制问题,提出基于模糊控制器的基础上,设计实现一种双模糊控制器。根据输出信号的误差大小分别利用两个模糊控制器进行控制,控制结果传递给调节器,以实现水箱水位不变。从仿真结果来看,双模糊控制器有效地减小了系统稳态误差,响应时间、超调量、稳定时间等性能优于传统的PID控制。     

改进的电动钻机柴油发电机组调速系统研究

针对传统电动钻机柴油发电机组调速系统,在不同工况下由于模型参数变化而引起的新的控制问题,设计了一个基于模糊控制与PI调节相结合的调速系统。该系统主要利用了模糊控制对被控对象非线性和时变性有很强适应能力的特点,在转速误差较大时进行模糊控制,当系统调节到稳定状态附近时进行PI调节。仿真实验结果表明该系统比传统PID控制和模糊控制在控制精度、稳定性方面都有很大提升。     

Extremum-seeking nonlinear controllers for a human exercise machine

In this paper, a next generation exercise machine controller is developed for a single degree of freedom (DOF) system to maximize the user's power output and ensure passivity with the user. In an effort to optimize the user's power expenditure, a desired velocity trajectory is developed that seeks the unknown user-dependent optimal velocity setpoint. Two extremum-seeking algorithms are presented (e.g., Kristic and Deng, and Tuekosky et al.) that seek the optimal velocity setpoint while ensuring the trajectory is sufficiently differentiable. To track the reference trajectory and to ensure passivity, two controllers are developed. The first controller is developed based on the assumption that the user's torque input can be measured. A second controller is designed that estimates the user's torque input. Both controllers are proven to ensure that the exercise machine remains passive with respect to the user's power output. The controllers are proven to yield semiglobal tracking through Lyapunov-based analyses. Proof-of-concept experimental results are provided that illustrate the performance of the torque estimation controller.     

NPC三电平逆变器中点电位观测器设计及控制

针对中点嵌位型（Neutral Point Clamp,NPC）三电平逆变器的中点电压波动会引起输出电压失真的问题,设计了一种观测器对中点电压波动进行观测,并根据观测结果设计了模糊PI控制器对其进行控制。首先建立了NPC三电平逆变器的数学模型,通过对直流侧电容电压的数学模型进行分析,将逆变器的中点电位不平衡问题近似为系统存在扰动下的误差估计;其次,根据模糊逻辑规则定义了新的误差变量,设计了模糊PI控制器,对中点电位波动问题进行控制;最后通过仿真和实验结果表明：设计的观测器可有效完成对中点电位的准确观测,利用模糊PI控制器实现了对中点电压波动的有效控制。     

基于状态观测器的混沌动态系统跟踪控制

针对一类连续混沌动态系统,提出一种基于状态观测器的跟踪控制方法来进行混沌控制.在引入状态观测器观测混沌动力学系统状态变量的基础上,采用反馈线性化方法将非线性混沌系统转换为线性系统,再针对反馈线性化后的线性系统设计轨迹跟踪控制器,实现被控混沌系统的跟踪控制.仿真结果进一步验证了该方法的有效性.     

Commissioning of a state-controlled high-powered electrical driveusing evolutionary algorithms

The subject of this research is the automated startup procedure of a PI state-controlled rolling-mill motor by using evolutionary algorithms. Compared to the conventional PI speed control, applying the method of deliberate pole placement to the state controller design succeeds in improving the transient response of setpoint and disturbance changes. To put the PI state-controlled drive with observer into operation to obtain a controller with a high robustness and dynamics, the precise knowledge of this physical parameter is necessary. An evolution-based system is used to solve the estimation problem. A high degree of reliability respecting multimodal characteristics and robustness against random noise is expected from the identification method. Evolutionary algorithms fulfill this requirement. With genetic operators like mutation, crossover, and selection, evolutionary algorithms mimic the principles of organic evolution in order to solve the optimization problem     

一种模糊-PI双模控制系统的仿真与设计

为了提高系统的控制性能,综合了模糊控制和PID控制的优点,提出一种基于模糊-PI双模控制器设计方法。典型的二维模糊控制器因缺少积分环节,难以消除稳态误差,控制的精度常常不能满足系统要求;而PI控制器具有良好的消除稳态误差的作用,所以将其与模糊控制器结合构成复合控制器。通过Matlab/Simulink仿真,结果表明,与经典的PID控制方式相比较,该控制方式在快速性、稳态性及准确性方面都有较大提高。     

一种双模糊控制器的设计实现

在工程实际中,很多被控对象具有时变、非线性的特点,用常规的控制方法难以进行控制或者控制效果不好,为了对这类实际系统进行有效地控制,本文基于模糊控制器的基础上,设计实现了一种双模糊控制器,根据实际系统输出信号的误差大小利用两个模糊控制器分别进行控制,以改善系统的快速性和消除误差。从仿真结果来看,和常规PID控制及普通模糊控制相比,双模糊控制器有效地减小了系统稳态误差,响应时间、超调量、稳定时间等性能均优于传统的PID控制和模糊控制。     

A DC Voltage Monitoring and Control Method for Three-Phase Grid-Connected Wind Turbine Inverters

Space vector pulsewidth modulation (SVPWM) based three-phase voltage source inverters provide a widely used interface between electric grids and wind turbine systems. PI controllers, predictive algorithms and real-time sampling techniques are often used to overcome the shortcomings of SVPWM. These techniques depend highly on accurate measurements of inverter voltages and currents, thus making sensors the key elements in the control process. Among these sensors, the dc link voltage (Vdc) sensor is critical: if it sends out a signal with a significant error, the output current will be distorted. The Authors have developed a combination of PI and predictive methods, using them simultaneously to control a three-phase grid-connected inverter. Under this new control scheme, the PI controller is given a new task of monitoring and controlling Vdc. As a result, the output current of the inverter is of high quality, and more importantly, Vdc can be double checked for its correctness of measurements. When the Vdc sensor fails or its signals are corrupted, the Vdc PI controller will become a Vdc controller, adding an extra protective function for the reliable operation of wind turbine inverters.     

Research on fuzzy self-adaptive PI-Smith control in long time-delay system

The long time-delay often exists in industrial process.In order to overcome the big overshoot and long regulating time of the long time-delay system control,a new fuzzy self-adaptive PI-Smith control method is proposed.This method combines the Smith predictive control with fuzzy self-adaptive proportional-integral(PI)control.The traditional proportional-integral-derivative(PID)controller in Smith predictive control is replaced by fuzzy PI controller which utilizes the principle of fuzzy control to tune parameters of PI controller on-line.The results of simulation for electric furnace show that the method has the advantages of shortening regulating time,no overshoot,no steady-state error,excellent control accuracy,and good adaptive ability to the change of system model.     

基于环形交叉耦合结构的多电机比例同步控制

针对多电机同步控制,国内外学者提出了多种算法和策略,但是这些策略对需要转速成一定比例的情况具有一定的局限性。文中在相邻交叉耦合控制策略和环形耦合控制策略的基础上,对比例同步系统相邻耦合误差的数学模型进行变换,将系统转化为近似同步系统,考虑系统各轴同步系数,结合传统交叉耦合控制结构,应用经典控制理论设计跟踪误差控制器和同步误差控制器。同时,针对系统可能出现的不确定性,文中设计了一种参数自整定模糊PID控制器。最后文章应用Matlab/Simulink对环形交叉耦合结构进行了计算机仿真,仿真结果表明,该环形交叉耦合结构模糊PID控制算法收敛速度快、稳定性能好,能很好的实现多电机比例协同控制。     

Adaptive lattice bilinear filters

Two fast least-squares lattice algorithms for adaptive nonlinear filters equipped with bilinear system models are presented. The lattice filter formulation transforms the nonlinear filtering problem into an equivalent multichannel linear filtering problem, thus using multichannel lattice filtering algorithms to solve the nonlinear filtering problem. The computational complexity of the algorithms is an order of magnitude smaller than that of previously available methods. The first of the two approaches is an equation error algorithm that uses the measured desired response signal directly to compute the adaptive filter outputs. This method is conceptually very simple, but results in biased system models in the presence of measurement noise. The second is an approximate least-squares output error solution; the past samples of the output of the adaptive system itself are used to produce the filter output at the current time. Results indicate that the output error algorithm is less sensitive to output measurement noise than the equation error method     

Sensorless speed control of nonsalient permanent-magnet synchronous motor using rotor-position-tracking PI controller

This paper presents a new velocity estimation strategy of a nonsalient permanent-magnet synchronous motor (PMSM) drive without a high-frequency signal injection or special pulsewidth-modulation (PWM) pattern. This approach is based on the d-axis current regulator output voltage of the drive system that has the information of rotor position error. Rotor velocity can be estimated through a rotor-position-tracking proportional-integral (PI) controller that controls the position error to zero. For zero and low-speed operation, the PI controller gains of rotor position tracking controller have a variable structure according to the estimated rotor velocity. In order to boost the bandwidth of the PI controller around zero speed, a loop recovery technique is applied to the control system. The proposed method only requires the flux linkage of the permanent magnet and is insensitive to parameter estimation error and variation. The designers can easily determine the possible operating range with a desired bandwidth and perform vector control even at low speeds. The experimental results show the satisfactory operation of the proposed sensorless algorithm under rated load conditions.