基于RBF网络的大滞后系统自适应预测PID控制器

针对大滞后系统滞后时间长,难以控制的特点,提出一种基于RBF网络的自适应预测P ID控制器。该控制器利用超前预测克服时滞,并采用基于RBF网络的P ID控制器在线调整控制器参数,从而控制系统的输出。应用该控制方法对大滞后一阶和二阶环节进行了仿真研究,结果表明该方法具有较快的系统响应,较强的自适应性和鲁棒性,控制设计简单等特点。     

基于RBF网络的多变量系统自适应预测PID控制器

针对非线性、多变量、大滞后耦合系统使用常规PID控制难以达到理想效果,提出了一种基于RBF网络的自适应预测PID控制器.该控制器利用递推多步预测克服时滞,并采用基于RBF网络整定的PID控制器在线调整控制器参数,从而克服了系统的耦合作用,提高了控制系统的输出跟踪精度.仿真结果表明,该方法控制效果良好,具有较快的系统响应、较强的自适应性和鲁棒性.     

基于复合模糊PID的地源热泵空调控制系统研究

针对地源热泵控制系统的非线性、大滞后及时变等特点,将常规的模糊控制与传统的PID控制相结合,设计了一种复合模糊PID控制器,应用于地缘热泵空调控制系统中,建立控制系统模型,同时对该方案进行了仿真.仿真结果表明:该控制器调节迅速,超调小,抗干扰能力强,与PID控制器、模糊控制器相比性能指标更具优越性.     

网络控制系统的仿真平台设计

研究网络控制系统时,一项主要的研究内容是研究网络对控制系统性能的影响,基于此目的设计了网络控制系统仿真平台NCSS。该平台利用Matlab来构造实际对象模型,基于物理网络使用Windows套接字Winsock进行控制器与对象之间的通信。该平台可以方便地模拟实际对象的运行,并能够灵活地实现各种控制算法,为网络控制系统的分析与设计提供了较好的仿真环境。     

模糊PID控制器的设计

本文着重对基本模糊控制器、模糊PID控制器的设计和在仿真软件MATLAB中的具体实现方法作了比较详尽的论述，在仿真软件MATLAB中完成对基本模糊控制器和模糊PID控制设计工作，并对相应的控制系统进行仿真，对时间常数对控制系统的控制效果的影响作了演示，得到其响应曲线，并与PID控制方法进行比较，从而得出模糊PID控制器对系统进行控制优于一般模糊控制器控制方法。     

抓斗挖泥船平挖的智能控制及仿真

设计了一种基于模糊神经网络的PID控制器,将其运用到大型抓斗挖泥船平挖控制系统中。该系统建立一个两输入三输出的模糊神经网络,并提供样本进行自学习。在Simulink中对基于模糊神经网络的PID控制系统和常规PID控制系统进行平挖运动仿真,结果表明,与常规控制相比,该网络能使系统的响应更为迅速,超调量小,鲁棒性强。     

汽车电泳涂装输送用新型混联机构的动力学控制

由于汽车电泳涂装输送用新型混联机构存在高度非线性和耦合性,因此难以实现高性能控制。为此,首先采用拉格朗日法推导该机构的动力学模型。然后,在任务空间设计一种PD滑模神经网络动力学控制器并进行稳定性证明。最后,对该控制器进行了仿真,并将所得结果与PD滑模控制器仿真结果进行比较。比较结果表明：该动力学控制器通过神经网络前馈控制的作用有效解决了PD滑模控制器存在的剧烈抖振问题,使得汽车电泳涂装输送控制系统呈现良好的控制性能。     

基于结构改进Smith预估单神经元PSD的长时延NCS研究

针对长时延网络控制系统（NCS）中存在时延和被控对象等问题,提出了一种新型结构改进Smith预估单神经元PSD控制器.新型控制器由结构改进Smith预估器和单神经元PSD控制器组成,结构改进Smith预估器通过对传统Smith预估器模型结构上的改进,避免了建立网络时延的预估模型,无需对网络时延进行在线测量、估计或辨识,补偿了网络时延对系统的性能带来的影响;单神经元PSD控制器解决了结构改进Smith预估器的模型失配问题,通过Matlab环境下的TrueTime工具箱对NCS进行仿真实验,并对传统PID控制方法、结构改进Smith预估PID控制方法和结构改进Smith预估单神经元PSD控制方法进行了仿真比较.研究结果表明,该新型控制器有效地补偿了网络时延对NCS的性能带来的影响,在模型失配情况下具有良好的鲁棒性和适应性,是对长时延NCS-种可行且有效的控制方法.     

多目标系统的自适应模糊神经网络控制

提出了一种多目标系统的自适应模糊神经网络控制的方法.通过对系统的多目标量进行加权合成,采用改进的遗传算法离线调整控制器网络参数.接入控制系统后,采用在线学习方式,通过BP算法调节网络的规则权值和比例因子,达到自适应控制的目的.计算机仿真结果显示,该方法控制效果好,鲁棒性强.     

网络控制系统中网络时延与建模分析

网络技术的广泛应用,对控制理论的研究提出了挑战,同时也带来了崭新的研究机遇和发展空间.本文从网络控制系统的特点和要求出发,对网络时延及其对网络控制系统的影响进行了阐述,并与建模分析相结合,利用连续和离散系统理论建立了几种较为常用的网络控制系统数学模型.在建模过程中考虑了控制器的动态特性、不同的网络时延和不同的节点工作方式,为网络控制系统的分析、仿真和控制器的设计奠定了一定的理论基础.     

One-step receding horizon H(∞) control for networked control systems with random delay and packet disordering

The receding horizon H(∞) control (RHHC) problem is investigated in this paper for a class of networked control systems (NCSs) with random delay and packet disordering. A new model is proposed to describe the NCS with random delay which may be larger than one sampling period. The random delay is modeled as a Markov chain while the closed-loop system is described as a Markovian jump system. Sufficient conditions for the closed-loop NCS to be stochastically stable and the performance index to be upper bounded are derived by using the receding optimization principle. Furthermore, by solving a semi-definite programming (SDP) with linear matrix inequalities (LMIs) constraint, a piecewise-constant receding horizon H(∞) controller is obtained, and the designed piecewise-constant controller ensures that the closed-loop NCS achieves a prescribed H(∞) disturbance attenuation level. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed method.     

Design and implementation of a new fuzzy PID controller for networked control systems

This paper presents a practical network platform to design and implement a networked-based cascade control system linking a Smar Foundation Fieldbus (FF) controller (DFI-302) and a Siemens programmable logic controller (PLC-S7-315-2DP) through Industrial Ethernet to a laboratory pilot plant. In the presented network configuration, the Smar OPC tag browser and Siemens WinCC OPC Channel provide the communicating interface between the two controllers. The paper investigates the performance of a PID controller implemented in two different possible configurations of FF function block (FB) and networked control system (NCS) via a remote Siemens PLC. In the FB control system implementation, the desired set-point is provided by the Siemens Human-Machine Interface (HMI) software (i.e, WinCC) via an Ethernet Modbus link. While, in the NCS implementation, the cascade loop is realized in remote Siemens PLC station and the final element set-point is sent to the Smar FF station via Ethernet bus. A new fuzzy PID control strategy is then proposed to improve the control performances of the networked-based control systems due to an induced transmission delay degradation effect. The proposed strategy utilizes an innovative idea based on sectionalizing the error signal of the step response into three different functional zones. The supporting philosophy behind these three functional zones is to decompose the desired control objectives in terms of rising time, settling time and steady-state error measures maintained by an appropriate PID-type controller in each zone. Then, fuzzy membership factors are defined to configure the control signal on the basis of the fuzzy weighted PID outputs of all three zones. The obtained results illustrate the effectiveness of the proposed fuzzy PID control scheme in improving the performances of the implemented NCS for different transportation delays.     

Real-time random delay compensation with prediction-based digital redesign

Today’s technological demands require challenging control solutions such as real-time applications of Networked Control System (NCS). However, due to communication protocol and shared data bus, NCS experiences uncertain and unpredictable time delays in both input and output channels. These delays cause asynchronization between the controller and the plant thereby degrading the performance of closed-loop control systems. To address this problem, this paper proposes to utilize digital redesign technique to provide real-time random delay compensation.     

Tuning of an optimal fuzzy PID controller with stochastic algorithms for networked control systems with random time delay

An optimal PID and an optimal fuzzy PID have been tuned by minimizing the Integral of Time multiplied Absolute Error (ITAE) and squared controller output for a networked control system (NCS). The tuning is attempted for a higher order and a time delay system using two stochastic algorithms viz. the Genetic Algorithm (GA) and two variants of Particle Swarm Optimization (PSO) and the closed loop performances are compared. The paper shows that random variation in network delay can be handled efficiently with fuzzy logic based PID controllers over conventional PID controllers.     

Constrained off-line synthesis approach of model predictive control for networked control systems with network-induced delays

This paper investigates the off-line synthesis approach of model predictive control (MPC) for a class of networked control systems (NCSs) with network-induced delays. A new augmented model which can be readily applied to time-varying control law, is proposed to describe the NCS where bounded deterministic network-induced delays may occur in both sensor to controller (S–A) and controller to actuator (C–A) links. Based on this augmented model, a sufficient condition of the closed-loop stability is derived by applying the Lyapunov method. The off-line synthesis approach of model predictive control is addressed using the stability results of the system, which explicitly considers the satisfaction of input and state constraints. Numerical example is given to illustrate the effectiveness of the proposed method.     

Adaptive sampling rate control for networked systems based on statistical characteristics of packet disordering

This paper investigates an adaptive sampling rate control scheme for networked control systems (NCSs) subject to packet disordering. The main objectives of the proposed scheme are (a) to avoid heavy packet disordering existing in communication networks and (b) to stabilize NCSs with packet disordering, transmission delay and packet loss. First, a novel sampling rate control algorithm based on statistical characteristics of disordering entropy is proposed; secondly, an augmented closed-loop NCS that consists of a plant, a sampler and a state-feedback controller is transformed into an uncertain and stochastic system, which facilitates the controller design. Then, a sufficient condition for stochastic stability in terms of Linear Matrix Inequalities (LMIs) is given. Moreover, an adaptive tracking controller is designed such that the sampling period tracks a desired sampling period, which represents a significant contribution. Finally, experimental results are given to illustrate the effectiveness and advantages of the proposed scheme.     

Model predictive control of non-linear systems over networks with data quantization and packet loss

This paper studies the approach of model predictive control (MPC) for the non-linear systems under networked environment where both data quantization and packet loss may occur. The non-linear controlled plant in the networked control system (NCS) is represented by a Tagaki-Sugeno (T-S) model. The sensed data and control signal are quantized in both links and described as sector bound uncertainties by applying sector bound approach. Then, the quantized data are transmitted in the communication networks and may suffer from the effect of packet losses, which are modeled as Bernoulli process. A fuzzy predictive controller which guarantees the stability of the closed-loop system is obtained by solving a set of linear matrix inequalities (LMIs). A numerical example is given to illustrate the effectiveness of the proposed method.     

长时延网络控制系统的研究方法与展望

随着网络控制系统的发展。网络时延逐渐成为研究的热点问题。目前对于网络控制系统的研究主要集中在短时延网络控制系统,而对于长时延络控制系统的研究较少。本文主要从不同方面论述了具有长时延网络控制系统的现有研究方法。并对此问题的其他研究方法进行了展望。     

基于遗传算法的网络控制系统调度优化研究

网络控制系统NCS(Networked Control system)是基于网络的分布式控制系统,具有强实时性。结合控制网络的实时调度与系统控制性能,应用单调速率RM(Rate Monotonic)方法对一组周期性的网络控制传输任务进行调度,采用遗传算法实现NCS的调度优化,同时满足了网络传输的优化调度与控制系统传输误差最小化的要求,提高了网络控制系统的性能,最后给出了优化实例。