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.

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.

Model Reference Variable Structure Autopilot Design for Homing Missile

To design the control system for some homing missile so that the autopilot can transfer guidance command correctly and be robust to disturbances, such as the measurement noises and parameter variation caused by areodynamic floating. The model reference adaptive control was combined with the variable structure control to design a model reference variable structure (MRVS) control system whose control structure is simple and can be realized easily. The simulation results indicate that MRVS can complete the task of transferring guidance command and suppress the distrubances 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.

Adaptive variable structure control based on backstepping for spacecraft with reaction wheels during attitude maneuver

An adaptive variable structure control method based on backstepping is proposed for the attitude maneuver problem of rigid spacecraft with reaction wheel dynamics in the presence of uncertain inertia matrix and external disturbances. The proposed control approach is a combination of the backstepping and the adaptive variable structure control. The cascaded structure of the attitude maneuver control system with reaction wheel dynamics gives the advantage for applying the backstepping method to construct Lyapunov functions. The robust stability to external disturbances and parametric uncertainty is guaranteed by the adaptive variable structure control. To validate the proposed control algorithm, numerical simulations using the proposed approach are performed for the attitude maneuver mission of rigid spacecraft with a configuration consisting of four reaction wheels for actuator and three magnetorquers for momentum unloading. Simulation results verify the effectiveness of the proposed control algorithm.

Nonlinear and Variable Structure Excitation Controller for Power System Stability

A new nonlinear variable structure excitation controller is proposed. Its design combines the differential geometry theory and the variable structure controlling theory. The mathematical model in the form of ＂an affme nonlinear system＂ is set up for the control of a large-scale power system. The static and dynamic performances of the nonlinear variable structure controller are simulated. The response of system with the controller proposed is compared to that of the nonlinear optimal controller when the system is subjected to a variety of disturbances. Simulation results show that the nonlinear variable structure excitation controller gives more satisfactorily static and dynamic performance and better robustness.

Compensation for secondary uncertainty in electro-hydraulic servo system by gain adaptive sliding mode variable structure control

Based on consideration of the differential relations between the immeasurable variables and measurable variables in electro-hydraulic servo system,adaptive dynamic recurrent fuzzy neural networks(ADRFNNs) were employed to identify the primary uncertainty and the mathematic model of the system was turned into an equivalent linear model with terms of secondary uncertainty.At the same time,gain adaptive sliding mode variable structure control(GASMVSC) was employed to synthesize the control effort.The results show that the unrealization problem caused by some system's immeasurable state variables in traditional fuzzy neural networks(TFNN) taking all state variables as its inputs is overcome.On the other hand,the identification by the ADRFNNs online with high accuracy and the adaptive function of the correction term's gain in the GASMVSC make the system possess strong robustness and improved steady accuracy,and the chattering phenomenon of the control effort is also suppressed effectively.

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.

Dynamic Friction Control Using Dynamic Structured RFNN and Friction Parameter Estimator

A nonlinear dynamic friction control is dealt with using dynamic friction observer and intelligent cantrol. The adaptive dynamic friction obsrver based on the LuGre friction is proposed to estimate the friction parameters and a directly friction state variable The dynamic structured Fuzzy Neural Network （RFNN） is designed to give additional robustness to the cantrol system under the presence of the friction model uncertainty. A proposed composite cantrol scheme is applied to the position tracking control of the servo systen. The performances of the proposed friction observer and the friction controller are demonstrated by simulation.

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.

Substructure design optimization and nonlinear responses control analysis of the mega-sub controlled structural system (MSCSS) under earthquake action

The newly proposed mega sub-controlled structure system(MSCSS)and related studies have drawn the attention of civil engineers for practice in improving the performance and enhancing the structural effectiveness of mega frame structures.However,there is still a need for improvement to its basic structural arrangement.In this project,an advanced,reasonable arrangement of mega sub-controlled structure models,composed of three mega stories with different numbers and arrangements of substructures,are designed to investigate the control performance of the models and obtain the optimal model configuration(model with minimum acceleration and displacement responses)under strong earthquake excitation.In addition,the dynamic parameters that affect the performance effectiveness of the optimal model of MSCSS are studied and discussed.The area of the relative stiffness ratio RD,with different mass ratio MR,within which the acceleration and displacement of the optimal model of MSCSS reaches its optimum(minimum)value is considered as an optimum region.It serves as a useful tool in practical engineering design.The study demonstrates that the proposed MSCSS configuration can efficiently control the displacement and acceleration of high rise buildings.In addition,some analytical guidelines are provided for selecting the control parameters of the structure.

A Survey of Control Structures for Reconfigurable Petri Nets

Software systems are increasingly executed in dynamic infrastructures. These infrastructures are dynamic as they are themselves subject to change as they support various applications that may or may not share some of the resources. Dynamic software systems become more and more important, but are difficult to handle. Modeling and simulating dynamic systems requires the representation of their processes and the system changes within one model. To that effect, reconfigurable Petri nets consist of a Petri net and a set of rules that can modify the Petri net. Their main feature is the capability to model complex coordination behavior in dynamically adapting infrastructures. The interplay of both levels of dynamic behavior requires a very precise description, so the specification when and which rules are to be applied plays a crucial role for the convenient use of reconfigurable nets. We differentiate several types of reconfigurable Petri nets and present a survey of control structure for these types, reconfigurable Petri nets. These control structures either concern the infrastructure, i.e., the rules and transformations or the system part, i.e., the firing behavior, or both. They are introduced by a short characterization and illustrated by examples. We state the results for various Petri net types and the tools supporting the different control structures.

Variable structure control for MRAC systems with perturbations in input and output channels

A design scheme of variable structure model reference control systems using only input and output measurements is presented for the systems with unmodeled dynamics and disturbances in input and output channels. The modeled part of the systems has relative degree greater than one and unknown upper bound of degree. By introducing some auxiliary signals and normalized signals with memory functions and appropriate choice of controller parameters, the developed variable structure controller guarantees the global stability of the closed-loop system and the arbitrarily small tracking error.

Single Phase Induction Motor Drive with Restrained Speed and Torque Ripples Using Neural Network Predictive Controller

In industrial drives, electric motors are extensively utilized to impart motion control and induction motors are the most familiar drive at present due to its extensive performance characteristic similar with that of DC drives. Precise control of drives is the main attribute in industries to optimize the performance and to increase its production rate. In motion control, the major considerations are the torque and speed ripples. Design of controllers has become increasingly complex to such systems for better management of energy and raw materials to attain optimal performance. Meager parameter appraisal results are unsuitable, leading to unstable operation. The rapid intensification of digital computer revolutionizes to practice precise control and allows implementation of advanced control strategy to extremely multifaceted systems. To solve complex control problems, model predictive control is an authoritative scheme, which exploits an explicit model of the process to be controlled. This paper presents a predictive control strategy by a neural network predictive controller based single phase induction motor drive to minimize the speed and torque ripples. The proposed method exhibits better performance than the conventional controller and validity of the proposed method is verified by the simulation results using MATLAB software.

京津冀科技创新投入对产业结构高级化的影响

京津冀科技创新对于推动京津冀地区产业结构高级化提供了有力支撑。通过明确京津冀科技创新投入对产业结构高级化影响的被解释变量、解释变量和控制变量,确定京津冀科技创新投入对产业结构高级化影响的指标。构建京津冀科技创新投入对产业结构高级化影响的静态回归模型和动态回归模型,利用2009—2020年面板数据,深入开展京津冀地区科技创新投入对产业结构高级化影响的对比研究。结果表明:京津冀整体的科技创新投入对其产业结构高级化的影响显著,科技创新投入增加能显著促进产业结构高级化;京津冀科技创新投入对产业结构高级化的影响程度存在显著的空间差异,经济发展水平显著影响地区科技创新投入对产业结构高级化的促进力度;考虑控制变量,区域对外开放水平显著抑制地区产业结构高级化,人力资本水平与政府支持力度对地区产业结构高级化影响存在显著空间差异。根据研究结果,提出京津冀科技创新推动产业结构高级化的对策建议。

直流电机位置伺服系统新型控制策略研究

针对伺服系统控制器参数设计的复杂性和系统抗干扰性低的问题,设计了内模PID速度控制器和基于指数趋近律的滑模变结构位置控制器,并通过李雅普诺夫理论对系统的稳定性进行分析。速度控制器采用内模PID控制,只调节滤波器参数λ,避免了因调参困难而影响伺服系统的控制精度;位置控制器采用滑模控制方式,对参数变化以及外界影响等因素具有强鲁棒性。仿真和实验结果表明,所提控制系统能够满足对直流伺服电机位置控制的快速性和准确性要求。

多节链式倾转旋翼飞行器重构控制与运动仿真

多节链式旋翼飞行器具有构形可变换的特点,是应对运动空间变化的一种有效构形设计方式。受限于构形变化下电机共轴带来的横向转动力矩的缺失,多节链式旋翼飞行器的动态重构飞行具有无法达成的临界构形区间。为此,设计了具备横向倾转的链式旋翼机体结构,以单机臂为模块化结构基本单元,通过旋转关节实现水平向的构形变化,机臂中段配置倾转矢量关节,用以提供滚转力矩支撑。在机体运动学、动力学模型推导的基础上,引入虚拟控制量对控制分配进行线性化处理,利用Moore-Penrose伪逆求解控制效率矩阵,面向全构形变换设计了基于全驱动控制的飞行控制律。对飞行器典型构形位姿控制的稳定性、构形变换控制的可行性进行实验论证,仿真结果表明:在飞行器各典型构形飞行状态下,姿态各轴向角度跟踪最大误差不超过0.05°,构形变换过程中,姿态各轴向角度跟踪误差不超出0.1°,2种情况下,位置偏差均能控制在1 mm以内,飞行器具备各构形下稳定飞行及构形变换的能力,为进一步开展动态重构及稳健飞行提供了必要条件。

基于模型预测静态规划的高速多体船减纵摇控制

为解决在海浪扰动下高速多体船的垂向稳定性变差问题,提出一种基于模型预测静态规划的减纵摇控制方法。考虑高速多体船模型不确定性、海浪噪声不符合高斯白噪声分布特点,根据噪声信息和误差信息设计平滑变结构滤波器,在线估计多体船的升沉速度、纵摇角速度,并将其引入到减摇控制中。在此基础上,基于模型预测静态规划提出多体船的减摇控制,采用终端偏差修正的求解方式,迭代更新控制输入,降低计算复杂度。最后,仿真实验表明了所提方法能有效抑制过大的升沉和纵摇运动幅度,以及减摇控制计算负荷小的优越性。

大展弦比飞行器变形辅助高度控制策略

针对变形飞行器结构/飞行耦合动力学的飞行控制问题,以大展弦比飞行器为研究对象开展了变形辅助高度控制策略研究。采用单元翼多体假设,构建了大展弦比飞行器二面角变形结构,建立了结构/飞行纵向耦合动力学模型,基于线性二次型(LQR)控制器设计方法设计了主动变形(AM)和被动变形(PM) 2种控制策略。其中,被动变形控制策略仅采用升降舵作为控制输入,结构二面角动态行为由耦合动力学驱动;主动变形控制策略以二面角铰链处的扭矩作为额外输入对高度跟踪进行协调控制。仿真分析了2种控制策略下的高度跟踪效果及状态变化,研究结果表明:采用主动变形控制策略可有效改善高度跟踪暂态过程的性能,降低姿态回路的阻尼特性,为未来先进变形飞行器的结构/飞行一体化控制提供研究基础。