Hybrid Dynamic Variables-Dependent Event-Triggered Fuzzy Model Predictive Control

This article focuses on dynamic event-triggered mechanism(DETM)-based model predictive control(MPC) for T-S fuzzy systems.A hybrid dynamic variables-dependent DETM is carefully devised,which includes a multiplicative dynamic variable and an additive dynamic variable.The addressed DETM-based fuzzy MPC issue is described as a “min-max” optimization problem(OP).To facilitate the co-design of the MPC controller and the weighting matrix of the DETM,an auxiliary OP is proposed based on a new Lyapunov function and a new robust positive invariant(RPI) set that contain the membership functions and the hybrid dynamic variables.A dynamic event-triggered fuzzy MPC algorithm is developed accordingly,whose recursive feasibility is analysed by employing the RPI set.With the designed controller,the involved fuzzy system is ensured to be asymptotically stable.Two examples show that the new DETM and DETM-based MPC algorithm have the advantages of reducing resource consumption while yielding the anticipated performance.

Model predictive control of rigid spacecraft with two variable speed control moment gyroscopes

In this paper, an attitude maneuver control problem is investigated for a rigid spacecraft using an array of two variable speed control moment gyroscopes （VSCMGs） with gimbal axes skewed to each other. A mathematical model is constructed by taking the spacecraft and the gyroscopes together as an integrated system, with the coupling interaction between them considered. To overcome the singular issues of the VSCMGs due to the conventional torque-based method, the first-order derivative of gimbal rates and the second-order derivative of the rotor spinning velocity, instead of the gyroscope torques, are taken as input variables. Moreover, taking external disturbances into account, a feedback control law is designed for the system based on a method of nonlinear model predictive control （NMPC）. The attitude maneuver can be realized fast and smoothly by using the proposed controller in this paper.

MODELING, VALIDATION AND OPTIMAL DESIGN OF THE CLAMPING FORCE CONTROL VALVE USED IN CONTINUOUSLY VARIABLE TRANSMISSION

Associated dynamic performance of the clamping force control valve used in continuously variable transmission （CVT） is optimized. Firstly, the structure and working principle of the valve are analyzed, and then a dynamic model is set up by means of mechanism analysis. For the purpose of checking the validity of the modeling method, a prototype workpiece of the valve is manufactured for comparison test, and its simulation result follows the experimental result quite well. An associated performance index is founded considering the response time, overshoot and saving energy, and five structural parameters are selected to adjust for deriving the optimal associated performance index. The optimization problem is solved by the genetic algorithm （GA） with necessary constraints. Finally, the properties of the optimized valve are compared with those of the prototype workpiece, and the results prove that the dynamic performance indexes of the optimized valve are much better than those of the prototype workpiece.

Design of Model Following Variable Structure Controller for Three-axle Vehicle

An optimal control procedure is developed for the front and rear wheels of a three-axle vehicle moving on a complex typical road based on model following variable structure control strategy. The actual vehicle may be considered as an uncertain system. Cornering stiffness of front and rear wheels and external disturbances are varied in a limited range. The model-following variable structure control method is used to control both front and rear wheels steering operations of the vehicle, so that steering responses of the vehicle follow from those of the reference model. By numerical results obtained from computer simulation, it is demonstrated that the control system model can cope with the effects of parameter perturbations and outside disturbances.

VARIABLE STRUCTURE MODEL－FOLLOWING ADAPTIVE CONTROL DESIGN FOR ROBOT MANIPULATORS

The increasing demand on robotic system performance leads to the use of advanced control strategies. A variable structure model-following adaptive control design is presented for the nonlinear robot manipulator systems, when subjected to fast and wide ranges of unknown-but-bounded parameter variations and disturbances. The design does not require any knowledge of a nonlinear robotic system. The system is robust and insensitive to the parameter variation, disturbances, as well as to the unmodeled dynamics. This insensitive property enables the elimination of interactions among the various joints of the robotic manipulator. In the closed loop, the robotic system asymptotically converges to the reference trajectory with a Prescribed transient resPOnse. The problem of chattering is discussed with the introduction of the special approaches: boundary layer, smoothing law, and nonlinear compensation.

MODELING AND INTEGRATED CONTROL FOR A METAL PUSHING BELT CONTINUOUSLY VARIABLE TRANSMISSION SYSTEM

By the bond graph theory,a bond graph analysis model of continuously variable transmission is established On the basis of improving the ratio change response and reducing the engine torque response lag in normal control,a new synthetic control algorithm is developed By analyzing the engine driving torque characteristics and the transmission inertia torque while ratio is changed under transient condition,the compensation value for engine driving torque is presented The simulation result shows that by this compensation control algorithm the engine torque response lag can be reduced and the driving torque response can be improved effectively.

An Approach to Polynomial NARX/NARMAX Systems Identification in a Closed-loop with Variable Structure Control

Many physical processes have nonlinear behavior which can be well represented by a polynomial NARX or NARMAX model. The identification of such models has been widely explored in literature. The majority of these approaches are for the open-loop identification. However, for reasons such as safety and production restrictions, open-loop identification cannot always be done. In such cases, closed-loop identification is necessary. This paper presents a two-step approach to closed-loop identification of the polynomial NARX/NARMAX systems with variable structure control （VSC）. First, a genetic algorithm （GA） is used to maximize the similarity of VSC signal to white noise by tuning the switching function parameters. Second, the system is simulated again and its parameters are estimated by an algorithm of the least square （LS） family. Finally, simulation examples are given to show the validity of the proposed approach.

Neural Network Predictive Control of Variable-pitch Wind Turbines Based on Small-world Optimization Algorithm

通过将混沌映射用于产生初始节点集和进行算子构造,提出一种新的基于实数编码的混沌小世界优化算法。采用4种算法对多例复杂函数的优化问题进行仿真试验,表明所提算法具有能够有效避免陷入局部极小值、快速搜索到最优值的能力。将上述方法应用于变桨距风电机组启动并网时的转速控制,提出一种基于混沌小世界优化算法的神经网络预测控制策略,其预测模型由基于现场数据的神经网络模型建立。仿真与实际测试结果表明,该系统可以根据风速扰动提前预测电机的转速变化,使控制器超前动作,保证系统输出跟踪参考轨迹的方向稳步改变,确保风电机组平稳并网。

Research on Variable Structure and Adaptive Control for Strap-on Rocket

Considering the increase of structural disturbance caused by large thrust misalignment and lack of synchronism after installation of the solid booster on the rock,as well as the increase of external disturbance resulting from the installation of the configuration and tail,while also considering the parameter uncertainties,parameter perturbations,unmodeled dynamics and coupling between channels during modeling,this paper proposes the design method for the adaptive control of sliding mode variable structure,based on the model reference. The paper firstly establishes the attitude dynamics model for the solid strap-on launch vehicle; then proposes the design method for the adaptive control of the sliding mode variable structure based on the model reference,implements the design of attitude control system for the three channels respectively,and uses the Lyapunov function to prove the global asymptotic stability; and finally verifies,through numerical simulation,that the control method proposed in this paper can guarantee the attitude stability of rockets in the primary flight phase.

Asymptotic Tracking Control for Wind Turbines in Variable Speed Mode

This paper presents a variable speed control strategy for wind turbines in order to capture maximum wind power.Wind turbines are modeled as a two-mass drive-train system with generator torque control.Based on the obtained wind turbine model,variable speed control schemes are developed.Nonlinear tracking controllers are designed to achieve asymptotic tracking for a prescribed rotor speed reference signal so as to yield maximum wind power capture.Due to the difficulty of torsional angle measurement,an observer-based control scheme that uses only rotor speed information is further developed for global asymptotic output tracking.The effectiveness of the proposed control methods is illustrated by simulation results.

Development of a Portable Electro-Mechanical Educational Model for Variable Rate Center Pivot Irrigation Technology

Center pivot irrigation systems usually apply a relatively uniform amount of water to fields that are often inherently variable, which could lead to significant waste of water and energy. To address this issue, our team is now developing an Intelligent Center Pivot (ICP) by integrating sensor-based irrigation scheduling with variable rate irrigation technology. However, before this technology can be applied in commercial production, it is necessary to educate growers about its practicality and potential benefits. The objective of this study was to develop a portable tabletop intelligent center pivot model (ICPDemo) to demonstrate and promote adoption of the ICP technology. This paper describes an ICPDemo constructed in 2014, including the design specifications, electro-mechanical design, control strategy, and performance. The ICPDemo has performed according to design specifications and is successfully being used to demonstrate the benefits and effectiveness of ICP technology for irrigation scheduling.

Design and Experiment of Slave Computer Control System for Applying Variable-rate Liquid Fertilizer

In order to increase the applying rate of liquid fertilizer and reduce environmental pollution, a slave computer control system for applying variable-rate liquid fertilizer was designed. The system used SMC as core processor and electrically controlled pressure regulator as execution component. The characteristic equation of the system was obtained by using classical control theory. Results indicated that the characteristic equation met the requirements of routh-criterion, which indicated the working process of the system was stable. Performance of the slave computer was verified via bench tests. Results demonstrated that there was no significant influence on the response from interclass error. The fertilization error was less than 0.9, and the fertilization accuracy was larger than 97%. The liquid fertilizer emitted by the fertilizing devices had no significant difference in uniformity, which met the demands of the slave computer control system for applying variable-rate liquid fertilizer.

The Control System Simulation of Variable-Speed Constant-Frequency Wind Turbine

In general,Variable-Speed Constant Frequency (VSCF)Wind generation system is controlled by stator voltage orientation method which based on the mathematic model of VSCF Wind generation system and discussed the control strategy.Present the whole dynamic control model of variable-speed wind generator system in MATLAB/ Simulink,and the simulation results confirm the validity and effectiveness of the proposed control strategy.

Cox模型中基于Model-X Knockoffs的高维控制变量选择方法

在生物医学、临床试验和流行病学等领域的研究中,由于获得生存数据的试验设计、观测时间的局限,以及观测对象在进入或退出试验时的个体差异等方面的原因,与所关注事件的发生时间相关的数据经常存在右删失。基于右删失生存数据解析协变量和生存时间的关系时,应用最为广泛的统计模型是Cox模型。随着科学技术的进步,数据收集变得越来越容易,导致数据库规模越来越大、复杂性越来越高,数据的维度通常可以达到成百上千维,甚至更高。文章提出一种Cox模型中基于Model-X Knockoffs的高维控制变量选择方法。首先基于Knockoffs框架建立一个Knockoffs变量,并基于原始协变量和其相应的Knockoffs变量构造一个正则化的目标函数,然后通过求解目标函数的最优解构造一个统计量和基于数据的阈值,最后进行变量选择。模拟分析和实证研究结果表明:所提方法可以在变量选择的同时提供可靠的FDR控制,优于传统的LASSO方法。

Optimization Transmission Efficiency with Driver Intention for Automotive Continuously Variable Transmission under Slip Mode

This study proposes and experimentally validates an optimal integrated system to control the automotive continuously variable transmission(CVT)by Model Predictive Control(MPC)to achieve its expected transmission efficiency range.The control system framework consists of top and bottom layers.In the top layer,a driving intention recognition system is designed on the basis of fuzzy control strategy to determine the relationship between the driver intention and CVT target ratio at the corresponding time.In the bottom layer,a new slip state dynamic equation is obtained considering slip characteristics and its related constraints,and a clamping force bench is established.Innovatively,a joint controller based on model predictive control(MPC)is designed taking internal combustion engine torque and slip between the metal belt and pulley as optimization dual targets.A cycle is attained by solving the optimization target to achieve optimum engine torque and the input slip in real-time.Moreover,the new controller provides good robustness.Finally,performance is tested by actual CVT vehicles.Results show that compared with traditional control,the proposed control improves vehicle transmission efficiency by approximately 9.12%-9.35%with high accuracy.

Dynamic modelling and robust current control of wind-turbine driven DFIG during external AC voltage dip

Doubly-Fed Induction Generator (DFIG), with vector control applied, is widely used in Variable-Speed Constant- Frequency (VSCF) wind energy generation system and shows good performance in maximum wind energy capture. But in two traditional vector control schemes, the equivalent stator magnetizing current is considered invariant in order to simplify the rotor current inner-loop controller. The two schemes can perform very well when the grid is in normal condition. However, when grid disturbance such as grid voltage dip or swell fault occurs, the control performance worsens, the rotor over current occurs and the Fault Ride-Through (FRT) capability of the DFIG wind energy generation system gets seriously deteriorated. An accurate DFIG model was used to deeply investigate the deficiency of the traditional vector control. The improved control schemes of two typical traditional vector control schemes used in DFIG were proposed, and simulation study of the proposed and traditional control schemes, with robust rotor current control using Internal Model Control (IMC) method, was carried out. The validity of the pro- posed modified schemes to control the rotor current and to improve the FRT capability of the DFIG wind energy generation system was proved by the comparison study.

Variable selection-based SPC procedures for high-dimensional multistage processes

Monitoring high-dimensional multistage processes becomes crucial to ensure the quality of the final product in modern industry environments. Few statistical process monitoring(SPC) approaches for monitoring and controlling quality in highdimensional multistage processes are studied. We propose a deviance residual-based multivariate exponentially weighted moving average(MEWMA) control chart with a variable selection procedure. We demonstrate that it outperforms the existing multivariate SPC charts in terms of out-of-control average run length(ARL) for the detection of process mean shift.

Feasibility analysis and online adjustment of constraints in model predictive control integrated with soft sensor

Feasibility analysis of soft constraints for input and output variables is critical for model predictive control(MPC).When encountering the infeasible situation, some way should be found to adjust the constraints to guarantee that the optimal control law exists. For MPC integrated with soft sensor, considering the soft constraints for critical variables additionally makes it more complicated and difficult for feasibility analysis and constraint adjustment. Therefore, the main contributions are that a linear programming approach is proposed for feasibility analysis, and the corresponding constraint adjustment method and procedure are given as well. The feasibility analysis gives considerations to the manipulated, secondary and critical variables, and the increment of manipulated variables as well. The feasibility analysis and the constraint adjustment are conducted in the entire control process and guarantee the existence of optimal control. In final, a simulation case confirms the contributions in this paper.

Optimal Driving of Large Belt Conveyor with Multi-roller Variable-Frequency Drive

in this paper, an electromechanically coupled mathematic model of multi-roller driving system for belt conveyor is set up, and the computing equations for dynamic displacement and dynamic tension of the conveyor are also formulated when the hoister is used for straining. Based on the belt conveyor of main inclined shaft in Chengzhuang coal mine, the driving torque, driving power and starting-speed characteristic of each electric motor are studied and measured when multi-roller variable-frequency drive (power distribution 2∶1) is used. The optimal control and the optimal starting-acceleration of the multi-roller variable-frequency drive are determined by a large number of industrial experiments and theoretical calculations.

Fuzzy Modeling, Tracking Control and Synchronization of the Rossler's Chaotic System

In this paper, a novel method to model, track control and synchronize the Rossler’s chaotic system is proposed. The fuzzy logical system is used so that the fuzzy inference rule is transferred into a type of variable coefficient nonlinear ordinary differential equation. Consequently the model of the chaotic system is obtained. Then a fuzzy tracking control and a fuzzy synchronization for chaotic systems is proposed as well. First, a known tracking control for the Rossler’s system is used in this paper. We represent the Rossler’s chaotic and control systems into fuzzy inference rules. Then the variable coefficient nonlinear ordinary differential equation is also got. Simulation results show that such an approach is effective and has a high precision.