模糊理论在预测函数控制上的应用

针对预测函数控制中模型失配的影响，提出了用模糊推理对控制量进行补偿的新型预测函数控制。并将基于模糊补偿的预测函数控制应用于锅炉燃烧控制系统，通过连续系统仿真，结果表明这种新型控制器具有较强的鲁棒性。     

神经网络解耦预测函数控制

结合解耦思想研究多变量系统预测函数控制。通过引入神经网络补偿环节，对多变量系统解耦，在此基础上，对解耦后各子系统进行单变量预测函数控制，以确定各个控制量。同时基于系统脉冲传递函数，得到单变量PFC控制器的显式表达式。仿真表明，该算法有较好的跟踪特性，对解决多变量系统的优化和控制具有一定的适用性。     

模糊预测函数控制

针对预测函数控制中模型失配的影响的情况，提出了用模糊推理对控制量进行补偿的解决方案。并将基于模糊补偿的预测函数控制应用于锅炉燃烧控制系统，通过连续系统仿真，结果表明这种控制器具有较强的鲁棒性。     

基于模糊性能指标的广义预测控制器参数调整

针对广义预测控制算法在控制时域中求得的M个控制量，利用模糊模拟技术对系统的约束进行检验，不断修正目标函数中控制量的加权系数，充分利用系统预测控制量的信息，增强系统的鲁棒性，并满足系统的约束。     

内模补偿预测函数控制在磁悬浮系统中的应用

由于磁悬浮系统参数时变及外界干扰的存在,采用预测函数控制会产生较大的预测误差,导致系统性能变差。针对这个问题,提出了一种基于内模补偿的预测函数控制方法。采用内模控制器的输出修正预测函数控制(PFC)补偿系统的控制量,克服不确定因素的影响,改善系统的控制品质。仿真和试验结果表明,该方法不仅能使磁浮球装置中的小球快速到达平衡位置,而且提高了系统的抗干扰能力和控制精度。     

基于非线性(Wiener)模型自适应预测函数控制

针对一类非线性对象提出了基于Wiener模型的非线性系统自适应预测函数控制方法。利用带遗忘因子的递推最小二乘算法在线辨识得到Wiener模型核参数，根据所得模型参数直接计算得到非线性预测函数控制律，而且使控制律计算容易，适用于具有一定非线性的被控对象，并能适应被控对象的环境变化。     

基于灰色系统模型的预测函数控制方法研究

以灰色系统模型为基础，建立了一种预测函数控制方法．分析了灰色系统建模、模型预测输出和控制量计算方程的求解．通过仿真结果表明，该算法具有鲁棒性好、跟踪快速和抑制干扰能力强等特点。     

网络控制系统中的时戳预测函数控制

传统预测函数控制算法不能有效处理网络控制系统中的随机延迟,为此提出了时戳预测函数控制算法.该算法使用时间戳来估计由网络引入的控制延迟,在预测系统未来输出时明确考虑了该延迟,然后借鉴传统预测函数控制算法的基本策略,得到了适用于网络控制系统的控制规律.进一步由TrueT im e工具箱搭建了网络控制系统仿真平台,对比了时戳预测函数控制算法和传统预测函数控制算法.仿真结果表明随着网络引入延迟的增大,时戳预测函数控制算法给出控制品质明显优越于传统预测函数控制算法.     

电加热炉系统预测函数PID控制算法的研究

由于电加热炉系统具有大时滞、时变性、非线性等特点,提出了一种新型预测函数PID控制算法.该算法将PID控制算法和预测函数控制算法结合起来,通过预测被控对象的未来输出值,得到一个新的优化目标函数,实时优化控制参数,得到控制量的解析解.仿真结果表明,与常规PID控制和预测函数PID串级控制相比,所设计的控制器满足系统对快速性和稳态精度的要求,系统具有较强的抗干扰性和鲁棒性,能够实现对电加热炉系统的有效控制.     

预测函数控制的内模控制理论

内模控制是一种基于过程数学模型进行控制器设计的新型控制策略,是研究预测控制重要的理论基础。预测函数控制是一种控制量计算方程简单,实时控制效果好的新型预测控制算法。本文用内模控制理论研究预测函数控制,分析了系统的鲁棒性和稳定性,最后进行了参数设计和仿真研究。     

Improved control using PFC and modified linear quadratic regulator for a kind of nonlinear systems

This paper describes the combination design of predictive functional control (PFC) and optimal linear quadratic (LQ) method for a kind of nonlinear process with output feedback coupling. In many existing control methods for this kind of nonlinear systems, the nonlinear part is either ignored or represented as a rough linear one when corresponding predictive control methods are designed. However, by assuming that the nonlinearity can be ignored or simplified to a linear time-varying part may not lead to the good control performance of subsequent linear control designs. The paper is a further investigation on this kind of systems, in which a procedure of PFC plus a modified optimal LQ control is developed. With respect to the proposed control strategy and the corresponding processes, the closed-loop performance is improved concerning tracking ability and disturbance rejection compared with previous predictive control methods. In addition, the proposed control is easy to implement as it selects a simple structure and a modification of the classical control scheme.     

基于Smith控制与预测函数控制的再热汽温多变量控制快速计算方法

针对再热汽温控制系统控制变量多、控制难度大等问题,提出了一种基于Smith控制与预测函数控制(PFC)的多变量控制快速计算方法。首先,将再热汽温多变量控制系统分解为三个单变量控制系统,在每个单变量控制系统中,将其中两个控制量作为干扰项;其次,根据Smith控制思想,设计每个单变量控制系统;最后在改进预测函数控制的性能指标的基础上,综合考虑三个单变量控制系统,实现对再热汽温度的控制。再热汽温控制仿真实验表明所提方法的计算速度是传统约束条件下预测控制的50倍左右,并且调整参数少,物理意义明确。实验结果表明该算法在现场使用中能够有效地提高再热汽温控制品质。     

Rail pressure controller design of GDI basing on predictive functional control

Gasoline direct injection (GDI) is a pivotal technique for a highly efficient engine. However, how to maintain a stable rail pressure which offers good fuel economy and low emissions, is still a challengeable work. In this paper, a rail pressure controller is designed basing on predictive functional control (PFC), a model predictive control (MPC) method, to surmount the nonlinearity and discontinuity brought by the common rail pressure system (CRPS). A control-oriented piecewise linear model is presented to simplify the CRPS. The simulation results on a benchmark show that rail pressure tracks the setpoint accurately even with some perturbations. Profiting from the conciseness of PFC algorithm, the controller can compute the online solution in a short time, which makes it possible to realize the strategy on a fast response system.     

一种基于滑模的自适应预测函数控制新算法

提出了一种应用带时变遗忘因子的基于滑模的自适应预测函数控制新算法。该算法采用带时变遗忘因子的递推最小二乘算法在线辨识模型参数,将滑模控制与预测函数控制(PFC)相结合对系统进行控制。与其他模型预测控制不同,预测函数控制可以克服其他模型预测控制可能出现规律不明的控制输入问题,具有良好的跟踪能力和较强的鲁棒性,离散滑模控制中的滑动模态对干扰具有不变性;最后分析了控制系统的闭环渐近稳定性。仿真结果验证了该方法的有效性。     

Adaptive Output Feedback based Output Tracking Control for a Time‐Delay System with a PFC

This output tracking control system for time‐delay systems with a parallel feedforward compensator (PFC). It has been clarified that one can design an adaptive output tracking control system for systems with almost strictly positive real (ASPR) properties. However, the robust stability for non‐ASPR time‐delay systems with a PFC introduced for making the resulting augmented system ASPR has not been analyzed. In this paper, it will be clarified that one can design a stable adaptive output tracking control system for time‐delay systems with a PFC, even if the resulting augmented system is not exactly ASPR.     

The Design of a Coprime‐Factorized Predictive Functional Controller for Unstable Fractional Order Systems

In this paper, a new approach, called coprime‐factorized predictive functional control method (CFPFC‐F) is proposed to control unstable fractional order linear time invariant systems. To design the controller, first, a prediction model should be synthesized. For this purpose, coprime‐factorized representation is extended for unstable fractional order systems via a reduced approximated model of unstable fractional order (FO) system. That is, an approximated integer model of fractional order system is derived via the well‐known Oustaloup method. Then, the high order approximated model is reduced to a lower one via a balanced truncation model order reduction method. Next, the equivalent coprime‐factorized model of the unstable fractional‐order plant is employed to predict the output of the system. Then, a predictive functional controller (PFC) is designed to control the unstable plant. Finally, the robust stability of the closed‐loop system is analyzed via small gain theorem. The performance of the proposed control is investigated via simulations for the control of an unstable non‐laminated electromagnetic suspension system as our simulation test system.     

Design of discrete time adaptive PID control systems with parallel feedforward compensator

This paper deals with the design of an adaptive PID control system with a parallel feedforward compensator (PFC) for discrete-time SISO systems and its application to water level control of a 3-tank system. The proposed method utilizes the characteristics of almost strict positive realness (ASPR) of the controlled plant. A conventional design scheme of a PFC which realizes an ASPR augmented controlled plant is also proposed. Further it is shown that the introduction of an internal model improves the control performance of the control system with the PFC. The effectiveness of the proposed method is confirmed through water level control experiments on a three-tank SISO system.     

感应电机最大转矩电流比的预测函数控制研究

研究感应电动机效率优化的最大转矩电流比控制问题,设计了基于Laguerre模型的稳定自适应预测函数控制器(PFC).采用前馈补偿解耦设计的思想,将系统分解成两个具有可测扰动的单入单出子系统,通过解方程组实现了PFC的设计.仿真实验结果表明,与传统的PI电流控制器相比,该控制器能在线辨识模型参数,跟踪精度高,响应迅速,抗扰能力强,取得了良好的控制效果.     

多星发射上面级主动抗扰姿态控制技术研究

针对多星发射的运载火箭上面级在入轨段由于卫星分离产生的质量偏移,从而引起的三轴姿态严重耦合问题展开了研究,提出了基于广义扩张状态观测器的改进预测函数控制姿态控制方法.该控制方法将质心偏移造成上面级结构参数偏差和引入的干扰力矩以及其他未知系统参数偏差、外界扰动和未建模动态视为集总扰动,并将该非匹配干扰通过等效输入扰动技术转换为匹配干扰,由广义扩张状态观测器对变化后的系统状态和未知集总扰动同时观测.将集总扰动在反馈回路予以补偿保证了预测模型与上面级真实动力学模型有较高匹配度,进一步保证预测函数控制有较高的控制跟踪精度和较快的响应速度,并对外界扰动和参数偏差有较强的鲁棒性.文中算例仿真和性能对比验证了该方法的有效性及可行性.