CN102063106A - External feedback and inner loop nondeterministic network time delay compensation method of network cascade control system - Google Patents

Abstract

The invention proposes a network cascade control system external feedback and internal loop non-deterministic network delay compensation method, which belongs to the technical field of network control systems. It uses the real network cascade control system external feedback network access nodes, and the network data transmission process between the inner loop network access nodes, instead of the network delay compensation model in between, and avoids the non-deterministic delay of network data transmission between nodes The measurement, observation, estimation or identification of , exempts the requirement of synchronizing the clock signal of the nodes. The method can reduce the influence of non-deterministic network delay on system stability, and improve the quality of system control performance. The present invention is applicable to the known mathematical models of the primary and secondary controlled objects, the network delay can be greater than several or even dozens of sampling periods, and the network only exists in the non-deterministic network in the external feedback and internal loop network paths of the network cascade control system Dynamic compensation and control of delay.

Description

Nondeterministic Network Delay Compensation Method for External Feedback and Inner Loop of Networked Cascade Control System

technical field

The invention relates to a method for compensating the non-deterministic network time delay of external feedback and internal loop network paths in a network cascade control system, belonging to the technical field of network control systems.

Background technique

The control loop is closed through a real-time network, which is called Networked Control Systems (NCS). Networked control systems can greatly reduce system wiring, reduce system costs, improve system reliability and flexibility, and facilitate system diagnosis and control. Maintenance has been widely used in aircraft, spacecraft, chemical plants, power systems and other fields.

An important feature of the network control system is that the sensing information and control information in the closed-loop control loop are transmitted through the real-time network. Since the real-time network is inserted into the control loop, it will inevitably bring about network-induced delay and packet loss, etc. A series of problems. The existence of network delay often reduces the performance of the system and even causes system instability.

At present, research on networked control systems at home and abroad is mainly aimed at single-loop control systems, respectively, when the network delay is constant, time-varying or random, the network delay is less than a sampling period or greater than a sampling period, single-packet transmission or multi-packet transmission Under various conditions such as transmission, data packet loss, etc., modeling and stability analysis are carried out on it, but few papers study the network cascade control system. The cascade control system whose control loop is closed through the real-time network is called the network Cascade control system (NCCS), a typical structural block diagram of the network cascade control system applicable to the present invention is shown in Figure 1.

Since the network cascade control system is a multi-closed-loop network control system, the analysis of the influence of network delay and the research on system performance are far more complicated than the single-loop network control system. The network delay of the inner loop will seriously affect the inner loop. The rapidity and anti-interference ability of the loop network control system will also have a negative impact on the stability and control quality of the entire network cascade control system together with the delay of the outer loop network.

The difficulty in researching network delay lies in:

(1) Since the network delay is related to factors such as network topology, communication protocol, network load, network bandwidth, and data packet size, it is necessary to establish accurate prediction and estimation for network delays greater than several or even dozens of sampling periods Or identification of mathematical models is currently almost impossible.

(2) The network delay that occurs in the process of transmitting network data from the previous node to the next node, no matter what prediction or estimation method is used in the previous node, it is impossible to know in advance the subsequent network delay Accurate value. Time delay leads to system performance degradation and even system instability, and also brings difficulties to the analysis and design of the control system.

(3) In the network cascade control system, it is unrealistic to completely synchronize the clock signals of all nodes in different distribution locations.

For the network cascade control system shown in Figure 2 where the network only exists in the feedback path of the outer loop and the feedback and forward paths of the entire inner loop, the closed-loop transfer between the input R(s) and the output Y ₁ (s) letter for

$\frac{{\mathrm{<span\; class="notranslate">\; Y</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; R</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; e</span>}}^{<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; \&tau;</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\mathrm{<span\; class="notranslate">\; the\; s</span>}}{\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; e</span>}}^{<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; \&tau;</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\mathrm{<span\; class="notranslate">\; the\; s</span>}}{\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; e</span>}}^{<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; \&tau;</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; e</span>}}^{<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; \&tau;</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\mathrm{<span\; class="notranslate">\; the\; s</span>}}{\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; e</span>}}^{<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; \&tau;</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}\mathrm{<span\; class="notranslate">\; the\; s</span>}}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

In the formula: C ₁ (s) is the main controller, C ₂ (s) is the secondary controller; G ₁ (s) is the main controlled object, G ₂ (s) is the secondary controlled object; τ ₁ represents the network The non-deterministic network delay caused by data transmission from the main transmitter node to the main (secondary) controller node through the external feedback network path; τ ₂ represents the network data from the main (secondary) controller node through the inner forward network The non-deterministic network delay generated by the path transmission to the actuator node; τ ₃ represents the non-deterministic network time generated by transmitting the network data from the auxiliary transmitter node to the main (secondary) controller node through the internal feedback network path Delay.

和

时延的存在将恶化系统的控制性能质量，甚至导致系统失去稳定性，严重时可使系统出现故障.Since the denominator of the closed-loop transfer function shown in equation (1) contains the exponential terms of the network delay τ ₁ , τ ₂ and τ ₃

and

The existence of time delay will deteriorate the control performance quality of the system, and even cause the system to lose stability, and in severe cases, the system may fail.

和

从等式(1)的分母中去除，即实现系统闭环特征方程中不包含所有网络时延的指数项，进而实现对网络时延的补偿.然而，要实现对网络时延的补偿，首先必须知道网络时延的大小.目前，国内外通常采用的方法是通过对网络时延τ₁，τ₂和τ₃的测量，来补偿时延τ₁，τ₂和τ₃对系统稳定性的影响.但是，由于对网络时延τ₁，τ₂和τ₃的准确测量需要满足节点时钟信号同步的要求，若采用硬件来实现节点时钟信号完全同步，则需要较大的经济投入；若采用软件校正时钟信号，则由于校正信号在节点间传输时，可能遭遇网络时延的影响，难以实现节点时钟完全同步.若采用对网络时延进行估计、观测、辨识或预测的方法来获得网络时延的大小，则首先必须知道网络时延的准确概率分布，或准确的数学模型，但由于网络时延的大小与具体的网络协议、网络负载大小以及网络拓扑结构等因素有关，对网络时延的估计、观测、辨识或预测都可能存在偏差.The key to reducing the impact of delay on system stability is whether the exponential terms of the non-deterministic network delay τ ₁ , τ ₂ and τ ₃ can be realized

and

It is removed from the denominator of equation (1), that is, the exponential term of all network delays is not included in the closed-loop characteristic equation of the system, and then the compensation of network delay is realized. However, to realize the compensation of network delay, first, Know the size of the network time delay. At present, the method usually adopted at home and abroad is to compensate the influence of the time delay τ ₁ , τ ₂ and τ ₃ on the system stability by measuring the network time delay τ ₁ , τ ₂ and τ ₃ .However, since the accurate measurement of network delay τ ₁ , τ ₂ and τ ₃ needs to meet the requirements of node clock signal synchronization, if hardware is used to realize node clock signal complete synchronization, a large economic investment is required; if software Correcting the clock signal, because the correction signal may encounter the influence of network delay when it is transmitted between nodes, it is difficult to achieve complete synchronization of the node clock. If the method of estimating, observing, identifying or predicting the network delay is used to obtain the network delay The size of the network delay must first know the exact probability distribution, or an accurate mathematical model, but because the size of the network delay is related to factors such as specific network protocols, network load, and network topology, the network delay There may be bias in estimation, observation, identification or prediction.

Therefore, how to avoid the requirement of node clock signal synchronization, how to avoid the estimation, observation, identification or prediction of the network delay between nodes, and at the same time obtain the accurate delay value between nodes, and then realize the cascade control of the network The feedback path of the outer loop of the system and the compensation function of the non-deterministic network delay in the feedback path of the entire inner loop and the forward path have become one of the key problems to be solved in the network cascade control system.

Contents of the invention

In order to solve the above-mentioned technical problems, the present invention provides a dynamic compensation method involving the non-deterministic network delay of the network cascade control system in the network only in the feedback path of the outer loop, and in the feedback and forward paths of the entire inner loop.

Purpose of the present invention:

Aiming at the problem of "inaccurate measurement" of network time delay in the network cascade control system, the present invention proposes a method that eliminates the need to control the main transmitter node, the main (secondary) controller node, the auxiliary transmitter node and the actuator node. The clock signal synchronization requirement is also exempted from measuring, estimating or identifying the non-deterministic network delay between nodes (outer loop feedback path, and the entire inner loop feedback and forward path), and realizing network delay Segmented, real-time, online and dynamic compensation and control.

The method that the present invention adopts is:

Step 1: Use the real network data transmission process between the secondary transmitter node and the main (secondary) controller node to replace the compensation model of the network delay in between, and realize the compensation model of the system without the network delay in the structure. No matter how complex and uncertain the network path from the sub-transmitter node to the main (sub-) controller node is, and no matter how many routers or (and) intermediate links are involved, the network delay experienced by the information flow It is the real network delay in the control process, and the compensation function for the delay has been realized in the process of information flow transmission.

Step 2: Use the real network data transmission process between the primary (secondary) controller node and the actuator node to replace the compensation model of the network delay in between, and realize the compensation model of the system without the network delay in the structure. No matter from How complex and uncertain is the network path between the primary (secondary) controller node and the actuator node, and no matter how many routers or (and) intermediate links are involved, the network delay experienced by the information flow is the control process. Real network delay, the delay compensation function has been realized in the process of information flow transmission.

The third step: replace the compensation model of the network delay between the main transmitter node and the main (secondary) controller node by the real network data transmission process, and realize the compensation model without the network delay in the system structurally. No matter how complex and uncertain the network path from the main transmitter node to the main (secondary) controller node is, and no matter how many routers or (and) intermediate links there are, the network delay experienced by the information flow It is the real network delay in the control process, and the compensation function for the delay has been realized in the process of information flow transmission.

Step 4: For the network cascade control system shown in Figure 2, the network delay compensation structure implementing the method of the present invention is shown in Figure 3.

In Fig. 3, the closed-loop transfer function between the input R(s) and the output Y ₁ (s) of the slave system is

$\frac{{\mathrm{<span\; class="notranslate">\; Y</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; R</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; =</span>\frac{\frac{{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; e</span>}}^{<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; \&tau;</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\mathrm{<span\; class="notranslate">\; the\; s</span>}}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>}}{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>\frac{{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; m</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; m</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; m</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; m</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; m</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; +</span>\frac{{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; e</span>}}^{<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; \&tau;</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\mathrm{<span\; class="notranslate">\; the\; s</span>}}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; m</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ]</span>{\mathrm{<span\; class="notranslate">\; e</span>}}^{<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; \&tau;</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}\mathrm{<span\; class="notranslate">\; the\; s</span>}}}{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

When the estimated model of the primary and secondary controlled objects is equal to its real model, that is, G _1m (s) = G ₁ (s), G _2m (s) = G ₂ (s), the secondary controller satisfies C _2m (s) = C ₂ (s), formula (2) can be simplified as

$\frac{{\mathrm{<span\; class="notranslate">\; Y</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; R</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; e</span>}}^{<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; \&tau;</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\mathrm{<span\; class="notranslate">\; the\; s</span>}}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$

和

即实现了闭环特征方程1+C₂(s)G₂(s)+C₁(s)C₂(s)G₂(s)G₁(s)＝0中不包含网络时延的指数项，从而消除了网络时延对系统稳定性的影响，提高了系统的控制性能质量，实现了对非确定性网络时延的补偿功能.The denominator of the closed-loop transfer function of the network cascade control system shown in formula (3) does not include the exponential terms of the network delay τ ₁ , τ ₂ and τ ₃

and

That is, the closed-loop characteristic equation 1+C ₂ (s)G ₂ (s)+C ₁ (s)C ₂ (s)G ₂ (s)G ₁ (s)＝0 does not include the exponential term of network delay , thereby eliminating the influence of network delay on system stability, improving the control performance quality of the system, and realizing the compensation function for non-deterministic network delay.

Scope of application of the present invention:

Applicable to the known mathematical models of the primary and secondary controlled objects, the network delay can be greater than several or even dozens of sampling periods, and the network only exists in the non-deterministic network delay in the external feedback and internal loop network paths of the network cascade control system dynamic compensation and control.

The invention is characterized in that the method comprises the steps of:

1. When the main transmitter node is triggered by the sampling period h ₁ , it will work in mode A;

2. When the main transmitter node transmits the model error signal w ₁ (s) to the main (secondary) controller node through the external feedback network path, it will work in mode B;

3. When the auxiliary transmitter node is triggered by the sampling period h ₂ , it will work in mode C;

4. When the auxiliary transmitter node transmits the output signal Y ₂ (s) of the auxiliary controlled object G ₂ (s) to the main (auxiliary) controller node through the internal feedback network path, it will use mode D to work;

5. When the primary (secondary) controller node is triggered by w ₁ (s) or (and) Y ₂ (s), it will work in mode E;

6. When the primary (secondary) controller node transmits the error signal e ₂ (s) to the actuator node through the internal forward network path, it will work in mode F;

7. When the actuator node is triggered by the error signal e ₂ (s), it will work in mode G.

The steps of method A include:

A1: The main transmitter node works in a time-driven mode, and its trigger sampling period is h ₁ ;

A2: After the main transmitter node is triggered, the output signal Y ₁ (s) of the main controlled object G ₁ (s) and the output signal y _1m (s) of the estimated model G _1m (s) of the main controlled object ) for sampling;

A3: Subtract Y ₁ (s) and y _1m (s) to obtain the model error signal w ₁ (s).

The steps of method B include:

B1: The main transmitter node transmits the model error signal w ₁ (s) to the main (secondary) controller node through the external feedback network path.

The steps of method C include:

C1: The sub-transmitter node works in the time-driven mode, and its trigger sampling period is h ₂ ;

C2: After the auxiliary transmitter node is triggered, the output signal Y ₂ (s) of the auxiliary controlled object G ₂ (s) is sampled.

The steps of method D include:

D1: The secondary transmitter node transmits the sampling signal of the output Y ₂ (s) of the secondary controlled object G ₂ (s) to the primary (secondary) controller node through the internal feedback network path.

The steps of method E include:

E1: The primary (secondary) controller node works in event-driven mode;

E2: The primary (secondary) controller node is triggered by w ₁ (s) or (and) Y ₂ (s);

E3: Subtract the system given signal R(s) from w ₁ (s) and m ₁ (s) to obtain the outer loop system error signal e ₁ (s);

F4: Implement the main controller C ₁ (s) operation on e ₁ (s) to obtain the control signal u ₁ (s);

E5: U ₁ (s) is used as a given signal to act on the negative feedback loop formed by the sub-controller prediction algorithm C _2m (s) and the sub-controlled object prediction model G _2m (s), and its output is y _cg2m (s); then apply y _cg2m (s) to G _1m (s), and its output is m ₁ (s);

E6: Add and subtract u ₁ (s) and Y ₂ (s) from the inner feedback network path to obtain the inner loop error signal e ₂ (s).

The steps of method F include:

F ₁ : The primary (secondary) controller node transmits the error signal e ₂ (s) to the actuator node through the inner forward network path.

The steps of mode G include:

G1; Actuator nodes work in event-driven mode;

G2: The actuator node is triggered by the error signal e ₂ (s);

G3: Subtract e ₂ (s) from the Y ₂ (s) signal from the on-site auxiliary transmitter to obtain the error signal e ₃ (s);

G4: Carry out C ₂ (s) control operation on e ₃ (s), and its output signal is u ₂ (s);

G5: Use u ₂ (s) as the driving signal to implement control on the secondary controlled object G ₂ (s); thereby changing the state of G ₂ (s), and then changing the state of G ₁ (s), realizing the control of G ₁ ( s) and the control effect of G ₂ (s).

8. The delay compensation method of the present invention is characterized in that the primary (secondary) controller node is composed of a secondary controller C ₂ (s) embedded in the primary controller C ₁ (s). That is, the primary controller and The secondary controllers share the same node to form the primary (secondary) controller node, and the primary (secondary) controller node adopts the event-driven trigger mode (the trigger signal is signal w ₁ (s) or (and) Y ₂ (s) ).

9. The delay compensation method of the present invention is characterized in that the system includes a main transmitter node, a secondary transmitter node, a main (secondary) controller node, an actuator node, a main controlled object and a secondary controlled object Each unit works according to its own set working mode and function.

10. The time delay compensation method of the present invention is characterized in that the network data transmission process of the external loop feedback network path from the main transmitter node to the main (secondary) controller node is used to replace the network time delay compensation therebetween Model, so as to realize the compensation model of the system without network delay in the structure.

11. The time delay compensation method of the present invention is characterized in that the network data transmission process of the inner loop forward network path from the main (secondary) controller node to the actuator node is used instead of the network time delay compensation model in between , so as to realize the compensation model in which the system does not include the network delay in the structure.

12. The time delay compensation method of the present invention is characterized in that the network data transmission process of the inner loop feedback network path from the auxiliary transmitter node to the main (secondary) controller node is used to replace the network time delay compensation in between Model, so as to realize the compensation model of the system without network delay in the structure.

13. The delay compensation method of the present invention is characterized in that the measurement, observation, estimation or identification of the network delay from the main transmitter node to the main (secondary) controller node is exempted from the structure.

14. The time delay compensation method of the present invention is characterized in that it is structurally exempt from measuring, observing, estimating or identifying the network time delay between the primary (secondary) controller node and the actuator node.

15. The delay compensation method according to the present invention is characterized in that the measurement, observation, estimation or identification of the network delay between the secondary transmitter node and the primary (secondary) controller node is exempted from the structure.

16. The time delay compensation method of the present invention is characterized in that the requirement for clock signal synchronization of the main transmitter node, the auxiliary transmitter node, the main (sub) controller node and the actuator node is exempted from the structure.

17. The time delay compensation method of the present invention is characterized in that the implementation of the network time delay compensation method has nothing to do with the selection of specific control strategies C ₁ (s) and C ₂ (s) from a structural point of view.

18. The time delay compensation method of the present invention is characterized in that the implementation of the network time delay compensation method has nothing to do with the selection of specific network communication protocols in terms of structure.

19. The delay compensation method of the present invention is characterized in that when the primary and secondary controlled objects G ₁ (s), G ₂ (s) are equal to their estimated models G _1m (s), G _2m (s) and the secondary control When the controller C ₂ (s) is equal to its estimated model C _2m (s), it can realize the complete compensation for the external feedback of the network cascade control system and the non-deterministic network delay of the inner loop network path, and improve the control performance quality of the system.

20. The time delay compensation method of the present invention is characterized in that it adopts a "soft" compensation method for changing the structure of the control system, without adding any hardware equipment, and using the software that comes with the intelligent nodes of the existing network cascade control system resources, it is sufficient to realize its compensation function.

21. The delay compensation method of the present invention is characterized in that mode A is suitable for periodic sampling of the main transmitter node and processing the signal.

22. The delay compensation method described in the present invention is characterized in that mode B is suitable for the main transmitter node to transmit network data.

23. The time delay compensation method of the present invention is characterized in that mode C is suitable for periodic sampling of auxiliary transmitter nodes and processing of signals.

24. The delay compensation method described in the present invention is characterized in that the method D is applicable to the transmission network data of the auxiliary transmitter node.

25. The time delay compensation method of the present invention is characterized in that the method E is suitable for the master (secondary) controller node to implement the control algorithm and process the signal.

26. The time delay compensation method of the present invention is characterized in that the method F is suitable for the transmission of network data by the primary (secondary) controller node.

27. The delay compensation method of the present invention is characterized in that the mode G is suitable for the actuator node to control the secondary controlled object G ₂ (s) and process the signal.

The present invention has the following advantages:

1. Since the measurement, observation, estimation or identification of the non-deterministic network delay in the external loop feedback path and the entire inner loop feedback and forward path is eliminated from the structure, and the requirement for node clock signal synchronization is also eliminated, thereby avoiding It eliminates the estimation error caused by the inaccurate time delay estimation model, avoids the waste of node storage resources required for time delay identification, and also avoids the compensation caused by "empty sampling" or "multiple sampling" caused by time delay error.

2. Since it has nothing to do with the choice of specific network communication protocols in terms of structure, it is not only suitable for network cascade control systems using wired network protocols, but also for network cascade control systems using wireless network protocols; It is also suitable for non-deterministic network protocols.

3. Since the structure has nothing to do with the choice of specific network communication protocols, it is not only suitable for heterogeneous network cascade control systems based on wired network protocols, but also suitable for heterogeneous network cascade control systems based on wireless network protocols , and it is also suitable for delay compensation of heterogeneous (such as mixed wired and wireless) network cascade control systems.

4. Since it has nothing to do with the selection of the control strategy of the specific main (sub) controller from the structure, it can be used not only for the network cascade control system using conventional control, but also for the network cascade control system using intelligent control or complex control strategy. Network cascade control system.

5. Since the present invention adopts a "soft" compensation method for changing the structure of the control system, there is no need to add any hardware devices during its implementation, and it is sufficient to use the software resources that come with the intelligent nodes of the existing network cascade control system Realize its compensation function, thus saving hardware investment and facilitating promotion and application.

Description of drawings

Figure 1 is a block diagram of the network cascade control system in which the network only exists in the feedback path of the outer loop and the feedback and forward paths of the entire inner loop.

Figure 2 is a network cascade control system structure diagram in which the network only exists in the feedback path of the outer loop and the feedback and forward paths of the entire inner loop.

Fig. 3 is a structural diagram of the external feedback and internal loop non-deterministic delay compensation method of the network cascade control system according to the present invention

In the block diagram of Figure 1, the system consists of input signal (R), main controlled object (G ₁ ), main transmitter (S ₁ ), external loop feedback network path, main (sub) controller (C ₁ /C ₂ ); sub-controlled object (G ₂ ), sub-transmitter (S ₂ ), inner loop feedback network path, inner loop forward network path, actuator (A) and other units.

The main transmitter (S ₁ ) node works in a time-driven manner, the trigger period is h ₁ , and the main controlled object (G ₁ ) is periodically sampled, and the sampled signal is processed.

The primary (secondary) controller (C ₁ /C ₂ ) node is composed of the secondary controller (C ₂ ) embedded in the primary controller (C ₁ ), that is, the primary controller (C ₁ ) and the secondary controller (C ₂ ) Share the same node. The node works in an event-driven manner, and the output signal of the main transmitter (S ₁ ) node passes through the external feedback network path or (and) the output signal of the secondary transmitter (S ₂ ) through the internal The loop feeds back into the network path to trigger.

The secondary transmitter (S ₂ ) node works in a time-driven manner, the trigger period is h ₂ , and the secondary controlled object (G ₂ ) is periodically sampled, and the sampled signal is processed.

The actuator (A) node works in an event-driven manner, triggered by the control signal of the main (secondary) controller node through the inner loop forward network path, and drives the actuator to change the state of the secondary controlled object (G ₂ ), Then change the state of the main controlled object (G ₁ ).

The main transmitter (S ₁ ) node, auxiliary transmitter (S ₂ ) node, main (sub) controller (C ₁ /C ₂ ) node and actuator (A) node of the system in Figure 1 are all intelligent nodes , not only have storage computing functions and communication functions, but also have software configuration and control functions. These nodes include the common intelligent nodes or intelligent equipment and other hardware.

In the system shown in Figure 2, the non-deterministic network delay in data transmission has a significant impact on the stability of the system and the quality of control performance. The data transmission of the network cascade control system experiences feedback from the main transmitter node through the external The non-deterministic network delay τ ₁ generated by the network path transmission to the primary (secondary) controller node, and the non-deterministic network time generated by the transmission from the primary (secondary) controller node to the actuator node through the internal forward network path Delay τ ₂ , and the influence of non-deterministic network delay τ ₃ generated from the transmission from the auxiliary transmitter node to the main (secondary) controller node through the internal feedback network path. The delay is related to the specific network protocol and network load And network topology and other factors, the measurement, or estimation, or observation, or identification of network delay has become a key prerequisite for its compensation. However, the distribution of each node connected through the network makes the network cascade control It is difficult for each node in the system to meet the requirements of clock signal synchronization. At the same time, due to the non-deterministic and bursty nature of network delay, it is impossible to accurately predict each step.

和

从分母中消除，即实现闭环特征方程中不包含网络时延τ₁，τ₂和τ₃的指数项，从而降低了时延对系统稳定性的影响，提高了系统的控制性能质量，实现对非确定性网络时延的补偿与控制.In the system in Figure 3, the network delay estimation model transmitted from the main transmitter node to the main (secondary) controller node through the external feedback network path is not included, nor is the network delay estimation model from the main (secondary) controller node The network delay estimation model transmitted from the internal forward network path to the actuator node, and the network delay estimation model transmitted from the auxiliary transmitter node to the main (secondary) controller node through the internal feedback network path Model. It eliminates the measurement, estimation, observation or identification of non-deterministic network time delay τ ₁ , τ ₂ and τ ₃ , and also eliminates the need for (main transmitter, auxiliary transmitter, main (sub) controller , executor) node clock signal synchronization requirements. When the primary and secondary controlled object prediction model is equal to its real model, and the secondary controller and its prediction model are equal, the input signal R(s) from the system to the output of the system can be realized In the closed-loop transfer function of the signal Y ₁ (s), the exponential terms of the network delays τ ₁ , τ ₂ and τ ₃

and

It is eliminated from the denominator, that is, the closed-loop characteristic equation does not include the exponential items of network delay τ ₁ , τ ₂ and τ ₃ , thereby reducing the impact of delay on system stability, improving the control performance quality of the system, and realizing the Compensation and control of non-deterministic network delay.

Detailed ways

An exemplary embodiment of the present invention will be described in detail below with reference to accompanying drawing 3, so that those of ordinary skill in the art will be more aware of the above-mentioned and other features and advantages of the present invention.

The specific implementation steps are as follows:

The first step: the output signal Y ₁ (s) of the main transmitter node working in the time-driven mode to the main plant G ₁ (s) and the output signal y _1m (s) of its prediction model G _1m (s) ) to conduct periodic sampling (sampling period is h ₁ ), and perform subtraction operation on Y ₁ (s) and y _1m (s), to obtain model error signal w ₁ (s);

Step 2: The main transmitter node transmits w ₁ (s) to the main (secondary) controller node through the external loop feedback network path;

Step 3: The sub-transmitter node working in the time-driven mode periodically samples the output signal Y ₂ (s) of the sub-controlled object G ₂ (s) (sampling period is h ₂ );

Step 4: The secondary transmitter node transmits Y ₂ (s) to the primary (secondary) controller node through the inner loop feedback network path;

Step 5: The main (secondary) controller node working in the event-driven mode is triggered by the signal w ₁ (s) or (and) Y ₂ (s); the main (secondary) controller node according to the given signal R of the system (s), subtract w ₁ (s) from the output signal m ₁ (s) of the compensation unit in the node to obtain the error signal e ₁ (s); implement C ₁ (s) control on e ₁ (s), and its output The signal is u ₁ (s): on the one hand, take u ₁ (s) as the node composed of the estimated model C _2m (s) of the secondary controller and the estimated model G _2m (s) of the secondary controlled object The given input signal of the negative feedback loop; on the other hand, the error signal e 2 (s) is obtained _by adding and subtracting u ₁ (s) and Y ₂ (s);

Step 6: The primary (secondary) controller node transmits the error signal e ₂ (s) to the actuator node through the inner loop forward network path;

Step 7: The actuator node works in the event-triggered mode, and after being triggered by the error signal e ₂ (s); subtract the signal Y ₂ (s) from the on-site secondary transmitter of e ₂ (s) to obtain the error signal e ₃ (s), and implement the control algorithm C ₂ (s) for e ₃ (s), its output u ₂ (s) is directly used to drive the actuator, thereby changing the state of the secondary controlled object G ₂ (s), and then Change the state of the main plant G ₁ (s);

Step 8: Return to the first step.

The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of the present invention. within the scope of protection.

The content not described in detail in this specification belongs to the prior art known to those skilled in the art.

Claims (16)

1. network cascade control system external feedback and inner looping uncertainty network delay penalty method is characterized in that this method may further comprise the steps:

(1). when main transmitter node is sampled cycle h ₁During triggering, will adopt mode A to carry out work;

(2). when main transmitter node with model error signal w ₁(s) pass through the external feedback network path when master's (pair) controller node transmits, will adopt mode B to carry out work;

(3). when secondary transmitter node is sampled cycle h ₂During triggering, will adopt mode C to carry out work;

(4). when secondary transmitter node with secondary controlled device G ₂(s) output signal Y ₂(s) by the internal feedback network path when master's (pair) controller node transmits, will adopt mode D to carry out work;

(5). when master's (pair) controller node by w ₁(s) or (with) Y ₂When (s) triggering, will adopt mode E to carry out work;

(6). when master's (pair) controller node by interior feedforward network path with error signal e ₂(s) when the actuator node transmits, will adopt mode F to carry out work;

(7). when the actuator node by error signal e ₂When (s) triggering, will adopt mode G to carry out work.

2. compensation method according to claim 1 is characterized in that the step of described mode A comprises:

A1: main transmitter node works in the time type of drive, and it triggers the sampling period is h ₁

A2: after main transmitter node is triggered, to main controlled device G ₁(s) output signal Y ₁(s) and the prediction model G of main controlled device _1m(s) output signal y _1m(s) sample;

A3: to Y ₁(s) and y _1m(s) implement additive operation, obtain model error signal w ₁(s).

3. compensation method according to claim 1 is characterized in that the step of described mode B comprises:

B1: main transmitter node is with model error signal w ₁(s), transmit to master's (pair) controller node by the external feedback network path.

4. compensation method according to claim 1 is characterized in that the step of described mode C comprises:

C1: secondary transmitter node works in the time type of drive, and it triggers the sampling period is h ₂

C2: after secondary transmitter node is triggered, to secondary controlled device G ₂(s) output signal Y ₂(s) sample.

5. compensation method according to claim 1 is characterized in that the step of described mode D comprises:

D1: secondary transmitter node is with secondary controlled device G ₂(s) output Y ₂(s) sampled signal is transmitted to master's (pair) controller node by the internal feedback network path.

6. compensation method according to claim 1 is characterized in that the step of described mode E comprises:

E1: main (pair) controller node works in event driven manner;

E2: main (pair) controller node is by w ₁(s) or (with) Y ₂(s) trigger;

E3: with given signal R of system (s) and w ₁(s) and m ₁(s) implement additive operation, obtain external loop systematic error signal e ₁(s);

E4: to e ₁(s) implement master controller C ₁(s) computing, controlled signal u ₁(s);

E5: with u ₁(s), act on submaster controller predictive algorithm C as given signal _2m(s) with secondary controlled device prediction model G _2m(s) negative feedback loop of Gou Chenging, it is output as Y _Cg2m(s); Again with Y _Cg2m(s) act on G _1m(s), it is output as m ₁(s);

E6: with u ₁(s) with from the Y of internal feedback network path ₂(s) add and subtract mutually, obtain the inner looping error signal e ₂(s).

7. compensation method according to claim 1 is characterized in that the step of described mode F comprises:

F ₁: main (pair) controller node by interior feedforward network path with error signal e ₂(s) transmit to the actuator node.

8. compensation method according to claim 1 is characterized in that the step of described mode G comprises:

G1: the actuator node works in event driven manner;

G2: the actuator node is by error signal e ₂(s) trigger;

G3: with e ₂(s) with from the Y of the secondary transmitter in scene ₂(s) signal subtraction obtains error signal e ₃(s);

G4: to e ₃(s) carry out C ₂(s) control computing, its output signal is u ₂(s);

G5: with u ₂(s) as drive signal, to secondary controlled device G ₂(s) implement control; Thereby change G ₂(s) state, and then change G ₁(s) state is realized G ₁(s) and G ₂Control action.

9. method according to claim 1 is characterized in that main (pair) controller node is by master controller C ₁(s) be embedded in submaster controller C ₂(s) form. be the shared same node of master controller and submaster controller, constitute main (pair) controller node, and main (pair) controller node adopts the event-driven triggered mode of operation, and (trigger pip is signal w ₁(s) or (with) Y ₂(s)).

10. method according to claim 1, it is characterized in that system comprises unit such as main transmitter node, secondary transmitter node, master's (pair) controller node, actuator node, main controlled device and secondary controlled device, each unit carries out work according to working method and the function set separately.

11. method according to claim 1, it is characterized in that using really, the network data transmission process from main transmitter node to external loop feedback network path master's (pair) controller node replaces network delay compensation model therebetween; Replace network delay compensation model therebetween with the network data transmission process from master's (pair) controller node to inner looping feedforward network path the actuator node really; Replace network delay compensation model therebetween with the network data transmission process from secondary transmitter node to inner looping feedback network path master's (pair) controller node really, thereby the system that structurally realizes does not comprise the compensation model of network delay.

12. method according to claim 1, it is characterized in that from structure exempt to from main transmitter node to master's (pair) controller node, from master's (pair) controller node to the actuator node, and measurement, observation, estimation or identification from secondary transmitter node to network delay master's (pair) controller node; Release is to main transmitter node, secondary transmitter node, master's (pair) controller node and the synchronous requirement of actuator node clock signal.

13. method according to claim 1 is characterized in that realizing from structure the enforcement and concrete control strategy C of network delay compensation method ₁(s) and C ₂(s) selection is irrelevant, and is irrelevant with the selection of concrete network communication protocol.

14. method according to claim 1 is characterized in that as major-minor controlled device G ₁(s), G ₂(s) with its prediction model G _1m(s), G _2m(s) equate and submaster controller C ₂(s) with its prediction model C _2mWhen (s) equating, can realize full remuneration, improve the control performance quality of system network cascade control system external feedback and inner looping network path uncertainty network delay.

15. method according to claim 1, what it is characterized in that adopting is the compensation method that " soft " changes the control system structure, need not increases any hardware device again, and the software resource that utilizes existing network cascade control system intelligent node to carry is realized its compensate function.

16. method according to claim 1, the mode A of it is characterized in that is applicable to main transmitter node periodic sampling and signal is handled; Mode B is applicable to main transmitter node transmitting network data; Mode C is applicable to secondary transmitter node periodic sampling and signal is handled; Mode D is applicable to secondary transmitter node transmitting network data; Mode E is applicable to main (pair) controller node enforcement control algolithm, and signal is handled; Mode F is applicable to main (pair) controller node transmitting network data; Mode G is applicable to that the actuator node is to secondary controlled device G ₂(s) implement control, and signal is handled.

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