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CN106054667A - Coking furnace pressure system stable switching controller design method - Google Patents

Coking furnace pressure system stable switching controller design method Download PDF

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CN106054667A
CN106054667A CN201610372893.1A CN201610372893A CN106054667A CN 106054667 A CN106054667 A CN 106054667A CN 201610372893 A CN201610372893 A CN 201610372893A CN 106054667 A CN106054667 A CN 106054667A
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overbar
coking furnace
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张俊锋
王玉中
张日东
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Hangzhou Dianzi University
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    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B17/00Systems involving the use of models or simulators of said systems
    • G05B17/02Systems involving the use of models or simulators of said systems electric

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Abstract

The present invention discloses a coking furnace pressure system stable switching controller design method. The coking furnace pressure system stable switching controller design method is established through the means such as data collection, model establishment, optimization and the like to effectively solve the instability problem caused by the system switching and ensure that the system has good control effect in the condition of the stable system.

Description

一种焦化炉炉膛压力系统稳定切换控制器设计方法Design method of stable switching controller for coking furnace furnace pressure system

技术领域technical field

本发明属于自动化技术领域,涉及一种焦化炉炉膛压力系统稳定切换控制器设计方法。The invention belongs to the technical field of automation, and relates to a design method for a stable switching controller of a furnace pressure system of a coking furnace.

背景技术Background technique

在实际工业控制过程中,由于实际过程对象存在许多不为人所知的复杂的物理或化学特性,对系统控制过程产生干扰。在很多实际系统中都是使用系统切换,例如,生态学、工业工程学、化学工程、经济学等。众所周知,系统稳定是工业过程的基础,对于控制系统设计非常重要。切换系统是一类混合系统,通过子系统和规则进行编排实现它们之间切换,可以保证它是稳定的。对于焦化加热炉炉膛压力的动态特性,系统状态反馈具有良好的控制效果,解决了传统控制方法切换造成的不稳定性难题。In the actual industrial control process, because the actual process object has many unknown complex physical or chemical characteristics, it will interfere with the system control process. System switching is used in many practical systems, for example, ecology, industrial engineering, chemical engineering, economics, etc. It is well known that system stability is the foundation of industrial processes and is very important for control system design. The switching system is a kind of hybrid system, which can be guaranteed to be stable by orchestrating subsystems and rules to achieve switching between them. For the dynamic characteristics of the furnace pressure of the coking heating furnace, the system state feedback has a good control effect, which solves the problem of instability caused by the switching of traditional control methods.

发明内容Contents of the invention

本发明的目的是针对焦化炉炉膛压力对象的模型切换过程出现不稳定这一问题,通过数据采集、模型建立、优化等手段,提供了一种焦化炉炉膛压力系统稳定切换控制器设计方法。该方法通过采集过程对象的输入输出数据,使用切换信号优化切换过程出现不稳定。该方法具有较高的精确性,能很好的改善过程对象的动态特性。The purpose of the present invention is to solve the problem of instability in the model switching process of the coking furnace furnace pressure object, and provide a design method for the stable switching controller of the coking furnace furnace pressure system by means of data collection, model establishment, optimization and other means. The method collects the input and output data of the process object, and uses the switching signal to optimize the instability of the switching process. This method has high accuracy and can improve the dynamic characteristics of process objects very well.

本发明的技术方案是通过数据采集、模型建立、优化等手段,确立了一种焦化炉炉膛压力稳定切换控制器设计方法,利用该方法可以有效解决系统切换造成的不稳定性难题,保证系统稳定的前提下具有良好的控制效果。The technical solution of the present invention is to establish a coking furnace hearth pressure stability switching controller design method by means of data collection, model building, optimization, etc., using this method to effectively solve the problem of instability caused by system switching and ensure system stability It has a good control effect under the premise.

本发明方法的步骤包括:The steps of the inventive method comprise:

步骤1、建立焦化炉炉膛压力的状态空间模型,具体方法是:Step 1. Establish a state-space model of coking furnace furnace pressure, the specific method is:

1.1首先采集焦化炉炉膛压力的输入输出数据,利用该数据建立焦化炉炉膛压力的状态空间模型,形式如下:1.1 First collect the input and output data of the coking furnace furnace pressure, and use the data to establish the state space model of the coking furnace furnace pressure in the following form:

y(t)=Cσ(t)x(t)y(t)=C σ(t) x(t)

其中,x(t)为焦化炉系统状态,y(t)为焦化炉输出压力,uσ(t)(t)为控制挡板开度,σ(t)为切换信号表示从[0,∞)到有限集S={1,2,…,N}的映射,Aσ(t)为Metzler矩阵,对于每个σ(t)∈S有,Bσ(t)≥0,Cσ(t)≥0。Among them, x(t) is the state of the coking furnace system, y(t) is the output pressure of the coking furnace, u σ(t) (t) is the opening of the control baffle, and σ(t) is the switching signal from [0,∞ ) to the finite set S={1,2,…,N} mapping, A σ(t) is a Metzler matrix, for each σ(t)∈S, B σ(t) ≥ 0, C σ(t) ≥ 0.

步骤2、设计焦化炉炉膛压力的状态反馈控制器,具体步骤是:Step 2. Design the state feedback controller of the coking furnace furnace pressure. The specific steps are:

2.1设计切换信号σ(t)且0≤t1≤t2,满足如下条件:2.1 Design the switching signal σ(t) and 0≤t 1 ≤t 2 to meet the following conditions:

Nσ(t2,t1)≤N0+(t2-t1)/τ* N σ (t 2 ,t 1 )≤N 0 +(t 2 -t 1 )/τ *

其中,Nσ(t2,t1)为切换系统在(t1,t2)内的切换次数,τ*>0为切换信号的平均驻留时间(ADT),N0≥0。Among them, N σ (t 2 , t 1 ) is the switching times of the switching system within (t 1 , t 2 ), τ * >0 is the average dwell time (ADT) of the switching signal, and N 0 ≥0.

2.2设计Ap+BpKpCp,p∈SMetzler矩阵,Kp为增益,切换序列为0≤t0<t1<t2<…,t∈[tk,tk+1),k∈N在t∈[tk,tk+1)设计李雅普诺夫函数和其导数为:2.2 Design A p +B p K p C p , p∈SMetzler matrix, K p is the gain, the switching sequence is 0≤t 0 <t 1 <t 2 <..., t∈[t k ,t k+1 ), k∈N at t∈[t k ,t k+1 ) design Lyapunov function and its derivative are:

Vi=xTv(i),i∈SV i =x T v (i) ,i∈S

VV &CenterDot;&CenterDot; &sigma;&sigma; (( tt kk )) (( xx (( tt )) )) == xx TT AA &sigma;&sigma; (( tt kk )) TT vv (( &sigma;&sigma; (( tt kk )) )) ++ uu &sigma;&sigma; (( tt kk )) TT BB &sigma;&sigma; (( tt kk )) TT vv (( &sigma;&sigma; (( tt kk )) )) ,, tt &Element;&Element; &lsqb;&lsqb; tt kk ,, tt kk ++ 11 ))

2.3设计常数ρ>0,λ>1,和向量v(p)∈Rn,v(q)∈Rn,z(p)∈Rs使其满足如下条件:2.3 Design constants ρ>0, λ>1, And the vector v (p) ∈ R n , v (q) ∈ R n , z (p) ∈ R s make it meet the following conditions:

(( AA pp TT ++ &rho;I&rho;I nno )) vv (( pp )) ++ zz (( pp )) << 00

v(p)>0v (p) > 0

v(p)≤λv(q) v (p) ≤ λv (q)

其中,是给定的非零向量,且在ADT满足 in, is a given non-zero vector, and satisfies in ADT

2.4设计加热炉炉膛压力系统的平衡点在适当切换信号σ(t)下是全局一致指数稳定(GUES),对任意初始状态x(t0),设计常数α和β使其系统状态响应满足如下条件:2.4 Design the furnace pressure system of the heating furnace The equilibrium point of is globally uniform exponentially stable (GUES) under an appropriate switching signal σ(t). For any initial state x(t 0 ), design constants α and β so that the system state response satisfies the following conditions:

|| || xx (( tt )) || || &le;&le; &alpha;e&alpha;e -- &beta;&beta; (( tt -- tt 00 )) || || xx (( tt 00 )) || ||

&alpha;&alpha; == nno &mu;&mu; &OverBar;&OverBar; (( vv (( &sigma;&sigma; (( tt 00 )) )) )) &mu;&mu; &OverBar;&OverBar; (( vv (( &sigma;&sigma; (( tt kk )) )) )) &alpha;&alpha; &prime;&prime;

其中, in,

2.5由步骤2.4可将上式转化为:2.5 By step 2.4, the above formula can be transformed into:

xx TT (( tt )) vv (( &sigma;&sigma; (( tt kk )) )) == &Sigma;&Sigma; ii == 11 nno xx ii (( tt )) vv ii (( &sigma;&sigma; (( tt kk )) )) &GreaterEqual;&Greater Equal; &mu;&mu; &OverBar;&OverBar; (( vv (( &sigma;&sigma; (( tt kk )) )) )) &Sigma;&Sigma; ii == 11 nno xx ii (( tt )) &GreaterEqual;&Greater Equal; &mu;&mu; &OverBar;&OverBar; (( vv (( &sigma;&sigma; (( tt kk )) )) )) || || xx (( tt )) || ||

xx TT (( tt 00 )) vv (( &sigma;&sigma; (( tt 00 )) )) == &Sigma;&Sigma; ii == 11 nno xx ii (( tt 00 )) vv ii (( &sigma;&sigma; (( tt 00 )) )) &le;&le; &mu;&mu; &OverBar;&OverBar; (( vv (( &sigma;&sigma; (( tt 00 )) )) )) &Sigma;&Sigma; ii == 11 nno xx ii (( tt 00 )) &le;&le; nno &mu;&mu; &OverBar;&OverBar; (( vv (( &sigma;&sigma; (( tt 00 )) )) )) || || xx (( tt )) || ||

2.6依据步骤2.4和2.5可得如下不等式:2.6 According to steps 2.4 and 2.5, the following inequality can be obtained:

xx TT (( tt )) vv (( &sigma;&sigma; (( tt kk )) )) &le;&le; &alpha;&alpha; &prime;&prime; ee -- &beta;&beta; (( tt -- tt 00 )) xx TT (( tt 00 )) vv (( &sigma;&sigma; (( tt 00 )) ))

再结合步骤2.3,进一步可以转化为:Combined with step 2.3, it can be further transformed into:

VV &sigma;&sigma; (( tt kk )) (( xx (( tt )) )) &le;&le; ee NN &sigma;&sigma; lnln &lambda;&lambda; ee -- &rho;&rho; (( tt -- tt 00 )) VV &sigma;&sigma; (( tt kk )) (( xx (( tt 00 )) )) &le;&le; ee (( NN 00 ++ tt -- tt &tau;&tau; ** )) lnln &lambda;&lambda; ee -- &rho;&rho; (( tt -- tt 00 )) VV &sigma;&sigma; (( tt 00 )) (( xx (( tt 00 )) )) &le;&le; &alpha;&alpha; &prime;&prime; ee -- &beta;&beta; (( tt -- tt 00 )) VV &sigma;&sigma; (( tt kk )) (( xx (( tt 00 )) ))

2.7依据步骤2.3最后一个不等式,可得如下形式:2.7 According to the last inequality in step 2.3, the following form can be obtained:

VV &sigma;&sigma; (( tt kk )) (( xx (( tt )) )) &le;&le; &lambda;e&lambda; e -- &rho;&rho; (( tt -- tt kk )) VV &sigma;&sigma; (( tt kk -- 11 )) (( xx (( tt kk )) )) &le;&le; ...... &le;&le; &lambda;&lambda; kk ee -- &rho;&rho; (( tt -- tt 00 )) VV &sigma;&sigma; (( tt 00 )) (( xx (( tt 00 )) ))

进一步转化为:which further translates to:

VV &sigma;&sigma; (( tt kk )) (( xx (( tt )) )) &le;&le; &lambda;e&lambda; e -- &rho;&rho; (( tt -- tt kk )) VV &sigma;&sigma; (( tt kk -- 11 )) (( xx (( tt kk )) ))

xx TT (( tt kk )) vv (( &sigma;&sigma; (( tt kk )) )) &le;&le; &lambda;x&lambda;x TT (( tt kk )) vv (( &sigma;&sigma; (( tt kk -- 11 )) ))

由2.3可得:From 2.3:

VV &sigma;&sigma; (( tt kk )) (( xx (( tt )) )) &le;&le; ee -- &rho;&rho; (( tt -- tt kk )) VV &sigma;&sigma; (( tt kk )) (( xx (( tt kk )) )) ,, tt &Element;&Element; &lsqb;&lsqb; tt kk ,, tt kk ++ 11 ))

对以上不等式求导得到:Taking the derivative of the above inequalities, we get:

VV &CenterDot;&CenterDot; &sigma;&sigma; (( tt kk )) (( xx (( tt )) )) &le;&le; -- &rho;x&rho;x TT vv (( &sigma;&sigma; (( tt kk )) )) &le;&le; -- &rho;V&rho;V &sigma;&sigma; (( tt kk ))

再结合2.3可得:Combined with 2.3, we can get:

VV &CenterDot;&CenterDot; &sigma;&sigma; (( tt kk )) (( xx (( tt )) )) == xx TT (( AA &sigma;&sigma; (( tt kk )) TT vv (( &sigma;&sigma; (( tt kk )) )) ++ zz (( &sigma;&sigma; (( tt kk )) )) ))

2.8综合步骤2.2到步骤2.7可以得到的焦化炉炉膛压力状态反馈控制量,形式如下:2.8 Combining steps 2.2 to 2.7, the coking furnace furnace pressure state feedback control quantity can be obtained in the following form:

uu pp (( tt )) == KK pp xx (( tt )) == 11 vv &OverBar;&OverBar; (( pp )) TT BB pp TT vv (( pp )) vv &OverBar;&OverBar; (( pp )) zz (( pp )) TT xx (( tt ))

本发明提出了一种焦化炉炉膛压力系统稳定切换控制器设计方法。该方法建立了系统的状态空间模型,通过设计系统的李雅普诺夫函数来设计状态反馈控制器,保证了系统切换是稳定的。The invention proposes a design method for a stable switching controller of a furnace pressure system of a coking furnace. This method establishes the state space model of the system, and designs the state feedback controller by designing the Lyapunov function of the system, which ensures that the switching of the system is stable.

具体实施方式detailed description

以焦化炉炉膛压力为实际对象,以烟道挡板的开度为输入,以焦化炉炉膛压力为输出,来建立焦化炉炉膛压力的模型。Taking the coking furnace pressure as the actual object, taking the opening of the flue baffle as the input, and taking the coking furnace pressure as the output, the model of the coking furnace pressure is established.

本发明方法的步骤包括:The steps of the inventive method comprise:

步骤1、建立焦化炉炉膛压力的状态空间模型,具体方法是:Step 1. Establish the state space model of coking furnace furnace pressure, the specific method is:

1.1首先采集焦化炉炉膛压力的输入输出数据,利用该数据建立焦化炉炉膛压力的状态空间模型,形式如下:1.1 First collect the input and output data of the coking furnace furnace pressure, and use the data to establish the state space model of the coking furnace furnace pressure in the following form:

xx &CenterDot;&Center Dot; (( tt )) == AA &sigma;&sigma; (( tt )) xx (( tt )) ++ BB &sigma;&sigma; (( tt )) uu &sigma;&sigma; (( tt )) (( tt ))

y(t)=Cσ(t)x(t)y(t)=C σ(t) x(t)

其中,x(t)为焦化炉系统状态,y(t)为焦化炉输出压力,uσ(t)(t)为控制挡板开度,σ(t)为切换信号表示从[0,∞)到有限集S={1,2,…,N}的映射,Aσ(t)为Metzler矩阵,对于每个σ(t)∈S有,Bσ(t)≥0,Cσ(t)≥0。Among them, x(t) is the state of the coking furnace system, y(t) is the output pressure of the coking furnace, u σ(t) (t) is the opening of the control baffle, and σ(t) is the switching signal from [0,∞ ) to the finite set S={1,2,…,N} mapping, A σ(t) is a Metzler matrix, for each σ(t)∈S, B σ(t) ≥ 0, C σ(t) ≥ 0.

步骤2、设计焦化炉炉膛压力的状态反馈控制器,具体步骤是:Step 2. Design the state feedback controller of the coking furnace furnace pressure. The specific steps are:

2.1设计切换信号σ(t)且0≤t1≤t2,满足如下条件:2.1 Design the switching signal σ(t) and 0≤t 1 ≤t 2 to meet the following conditions:

Nσ(t2,t1)≤N0+(t2-t1)/τ* N σ (t 2 ,t 1 )≤N 0 +(t 2 -t 1 )/τ *

其中,Nσ(t2,t1)为切换系统在(t1,t2)内的切换次数,τ*>0为切换信号的平均驻留时间(ADT),N0≥0。Among them, N σ (t 2 , t 1 ) is the switching times of the switching system within (t 1 , t 2 ), τ * >0 is the average dwell time (ADT) of the switching signal, and N 0 ≥0.

2.2设计Ap+BpKpCp,p∈SMetzler矩阵,Kp为增益,切换序列为0≤t0<t1<t2<…,t∈[tk,tk+1),k∈N在t∈[tk,tk+1)设计李雅普诺夫函数和其导数为:2.2 Design A p +B p K p C p , p∈SMetzler matrix, K p is the gain, the switching sequence is 0≤t 0 <t 1 <t 2 <..., t∈[t k ,t k+1 ), k∈N at t∈[t k ,t k+1 ) design Lyapunov function and its derivative are:

Vi=xTv(i),i∈SV i =x T v (i) ,i∈S

VV &CenterDot;&CenterDot; &sigma;&sigma; (( tt kk )) (( xx (( tt )) )) == xx TT AA &sigma;&sigma; (( tt kk )) TT vv (( &sigma;&sigma; (( tt kk )) )) ++ uu &sigma;&sigma; (( tt kk )) TT BB &sigma;&sigma; (( tt kk )) TT vv (( &sigma;&sigma; (( tt kk )) )) ,, tt &Element;&Element; &lsqb;&lsqb; tt kk ,, tt kk ++ 11 ))

2.3设计常数ρ>0,λ>1,和向量v(p)∈Rn,v(q)∈Rn,z(p)∈Rs使其满足如下条件:2.3 Design constants ρ>0, λ>1, And the vector v (p) ∈ R n , v (q) ∈ R n , z (p) ∈ R s make it meet the following conditions:

(( AA pp TT ++ &rho;I&rho; I nno )) vv (( pp )) ++ zz (( pp )) << 00

v(p)>0v (p) > 0

v(p)≤λv(q) v (p) ≤ λv (q)

其中,是给定的非零向量,且在ADT满足 in, is a given non-zero vector, and satisfies in ADT

2.4设计加热炉炉膛压力系统的平衡点在适当切换信号σ(t)下是全局一致指数稳定(GUES),对任意初始状态x(t0),设计常数α和β使其系统状态响应满足如下条件:2.4 Design the furnace pressure system of the heating furnace The equilibrium point of is globally uniform exponentially stable (GUES) under an appropriate switching signal σ(t). For any initial state x(t 0 ), design constants α and β so that the system state response satisfies the following conditions:

|| || xx (( tt )) || || &le;&le; &alpha;e&alpha;e -- &beta;&beta; (( tt -- tt 00 )) || || xx (( tt 00 )) || ||

&alpha;&alpha; == nno &mu;&mu; &OverBar;&OverBar; (( vv (( &sigma;&sigma; (( tt 00 )) )) )) &mu;&mu; &OverBar;&OverBar; (( vv (( &sigma;&sigma; (( tt kk )) )) )) &alpha;&alpha; &prime;&prime;

其中, in,

2.5由步骤2.4可将上式转化为:2.5 By step 2.4, the above formula can be transformed into:

xx TT (( tt )) vv (( &sigma;&sigma; (( tt kk )) )) == &Sigma;&Sigma; ii == 11 nno xx ii (( tt )) vv ii (( &sigma;&sigma; (( tt kk )) )) &GreaterEqual;&Greater Equal; &mu;&mu; &OverBar;&OverBar; (( vv (( &sigma;&sigma; (( tt kk )) )) )) &Sigma;&Sigma; ii == 11 nno xx ii (( tt )) &GreaterEqual;&Greater Equal; &mu;&mu; &OverBar;&OverBar; (( vv (( &sigma;&sigma; (( tt kk )) )) )) || || xx (( tt )) || ||

xx TT (( tt 00 )) vv (( &sigma;&sigma; (( tt 00 )) )) == &Sigma;&Sigma; ii == 11 nno xx ii (( tt 00 )) vv ii (( &sigma;&sigma; (( tt 00 )) )) &le;&le; &mu;&mu; &OverBar;&OverBar; (( vv (( &sigma;&sigma; (( tt 00 )) )) )) &Sigma;&Sigma; ii == 11 nno xx ii (( tt 00 )) &le;&le; nno &mu;&mu; &OverBar;&OverBar; (( vv (( &sigma;&sigma; (( tt 00 )) )) )) || || xx (( tt )) || ||

2.6依据步骤2.4和2.5可得如下不等式:2.6 According to steps 2.4 and 2.5, the following inequality can be obtained:

xx TT (( tt )) vv (( &sigma;&sigma; (( tt kk )) )) &le;&le; &alpha;&alpha; &prime;&prime; ee -- &beta;&beta; (( tt -- tt 00 )) xx TT (( tt 00 )) vv (( &sigma;&sigma; (( tt 00 )) ))

再结合步骤2.3,进一步可以转化为:Combined with step 2.3, it can be further transformed into:

VV &sigma;&sigma; (( tt kk )) (( xx (( tt )) )) &le;&le; ee NN &sigma;&sigma; lnln &lambda;&lambda; ee -- &rho;&rho; (( tt -- tt 00 )) VV &sigma;&sigma; (( tt kk )) (( xx (( tt 00 )) )) &le;&le; ee (( NN 00 ++ tt -- tt &tau;&tau; ** )) lnln &lambda;&lambda; ee -- &rho;&rho; (( tt -- tt 00 )) VV &sigma;&sigma; (( tt 00 )) (( xx (( tt 00 )) )) &le;&le; &alpha;&alpha; &prime;&prime; ee -- &beta;&beta; (( tt -- tt 00 )) VV &sigma;&sigma; (( tt kk )) (( xx (( tt 00 )) ))

2.7依据步骤2.3最后一个不等式,可得如下形式:2.7 According to the last inequality in step 2.3, the following form can be obtained:

VV &sigma;&sigma; (( tt kk )) (( xx (( tt )) )) &le;&le; &lambda;e&lambda; e -- &rho;&rho; (( tt -- tt kk )) VV &sigma;&sigma; (( tt kk -- 11 )) (( xx (( tt kk )) )) &le;&le; ...... &le;&le; &lambda;&lambda; kk ee -- &rho;&rho; (( tt -- tt 00 )) VV &sigma;&sigma; (( tt 00 )) (( xx (( tt 00 )) ))

进一步转化为:which further translates to:

VV &sigma;&sigma; (( tt kk )) (( xx (( tt )) )) &le;&le; &lambda;e&lambda; e -- &rho;&rho; (( tt -- tt kk )) VV &sigma;&sigma; (( tt kk -- 11 )) (( xx (( tt kk )) ))

xx TT (( tt kk )) vv (( &sigma;&sigma; (( tt kk )) )) &le;&le; &lambda;x&lambda;x TT (( tt kk )) vv (( &sigma;&sigma; (( tt kk -- 11 )) ))

由2.3可得:From 2.3:

VV &sigma;&sigma; (( tt kk )) (( xx (( tt )) )) &le;&le; ee -- &rho;&rho; (( tt -- tt kk )) VV &sigma;&sigma; (( tt kk )) (( xx (( tt kk )) )) ,, tt &Element;&Element; &lsqb;&lsqb; tt kk ,, tt kk ++ 11 ))

对以上不等式求导得到:Taking the derivative of the above inequalities, we get:

VV &CenterDot;&Center Dot; &sigma;&sigma; (( tt kk )) (( xx (( tt )) )) &le;&le; -- &rho;x&rho;x TT vv (( &sigma;&sigma; (( tt kk )) )) &le;&le; -- &rho;V&rho;V &sigma;&sigma; (( tt kk ))

再结合2.3可得:Combined with 2.3, we can get:

VV &CenterDot;&Center Dot; &sigma;&sigma; (( tt kk )) (( xx (( tt )) )) == xx TT (( AA &sigma;&sigma; (( tt kk )) TT vv (( &sigma;&sigma; (( tt kk )) )) ++ zz (( &sigma;&sigma; (( tt kk )) )) ))

2.8综合步骤2.2到步骤2.7可以得到的焦化炉炉膛压力状态反馈控制量,形式如下:2.8 Combining steps 2.2 to 2.7, the coking furnace furnace pressure state feedback control quantity can be obtained in the following form:

uu pp (( tt )) == KK pp xx (( tt )) == 11 vv &OverBar;&OverBar; (( pp )) TT BB pp TT vv (( pp )) vv &OverBar;&OverBar; (( pp )) zz (( pp )) TT xx (( tt ))

Claims (1)

1. A design method of a stable switching controller of a hearth pressure system of a coking furnace is characterized by comprising the following steps:
step 1, establishing a state space model of the hearth pressure of the coking furnace, which specifically comprises the following steps:
step 1.1, firstly, acquiring input and output data of the hearth pressure of the coking furnace, and establishing a state space model of the hearth pressure of the coking furnace by using the data, wherein the form is as follows:
x &CenterDot; ( t ) = A &sigma; ( t ) x ( t ) + B &sigma; ( t ) u &sigma; ( t ) ( t )
y(t)=Cσ(t)x(t)
wherein x (t) is the system state of the coke oven, y (t) is the output pressure of the coke oven, uσ(t)(t) is the control shutter opening, σ (t) is the mapping of the switching signal representation from [0, ∞ ] to the finite set S ═ 1,2, …, N ],Aσ(t)for the Metzler matrix, there is, for each σ (t) ∈ S, Bσ(t)≥0,Cσ(t)≥0;
Step 2, designing a state feedback controller of the hearth pressure of the coking furnace, which specifically comprises the following steps:
step 2.1 design switching signal σ (t) and t is more than or equal to 01≤t2The following conditions are satisfied:
Nσ(t2,t1)≤N0+(t2-t1)/τ*
wherein N isσ(t2,t1) For switching the system in (t)1,t2) Number of inner handovers, τ*>0 is the average dwell time of the switching signal, N0≥0;
Step 2.2 design Ap+BpKpCpP ∈ SMetzler matrix, KpFor gain, the switching sequence is t is more than or equal to 00<t1<t2<…,t∈[tk,tk+1) K ∈ N at t ∈ [ t ]k,tk+1) The lyapunov function and its derivatives are designed as:
Vi=xTv(i),i∈S
V &CenterDot; &sigma; ( t k ) ( x ( t ) ) = x T A &sigma; ( t k ) T v ( &sigma; ( t k ) ) + u &sigma; ( t k ) T B &sigma; ( t k ) T v ( &sigma; ( t k ) ) , t &Element; &lsqb; t k , t k + 1 )
step 2.3 design constant ρ>0,λ>1,Sum vector v(p)∈Rn,v(q)∈Rn,z(p)∈RsSo that the following conditions are satisfied:
( A p T + &rho;I n ) v ( p ) + z ( p ) < 0
v(p)>0
v(p)≤λv(q)
wherein,is a given non-zero vectorAnd at an average residence time of
Step 2.4 design heating furnace hearth pressure systemIs globally consistent and exponentially stable under a proper switching signal sigma (t) and is used for any initial state x (t)0) Constants α and β are designed such that their system state responses satisfy the following condition:
| | x ( t ) | | &le; &alpha;e - &beta; ( t - t 0 ) | | x ( t 0 ) | |
&alpha; = n &mu; &OverBar; ( v ( &sigma; ( t 0 ) ) ) &mu; &OverBar; ( v ( &sigma; ( t k ) ) ) &alpha; &prime;
wherein,
step 2.5 from step 2.4 the above formula can be converted to:
x T ( t ) v ( &sigma; ( t k ) ) = &Sigma; i = 1 n x i ( t ) v i ( &sigma; ( t k ) ) &GreaterEqual; &mu; &OverBar; ( v ( &sigma; ( t k ) ) ) &Sigma; i = 1 n x i ( t ) &GreaterEqual; &mu; &OverBar; ( v ( &sigma; ( t k ) ) ) | | x ( t ) | |
x T ( t 0 ) v ( &sigma; ( t 0 ) ) = &Sigma; i = 1 n x i ( t 0 ) v i ( &sigma; ( t 0 ) ) &le; &mu; &OverBar; ( v ( &sigma; ( t 0 ) ) ) &Sigma; i = 1 n x i ( t 0 ) &le; &mu; &OverBar; ( v ( &sigma; ( t 0 ) ) ) | | x ( t ) | |
step 2.6 the following inequality is obtained according to steps 2.4 and 2.5:
x T ( t ) v ( &sigma; ( t k ) ) &le; &alpha; &prime; e - &beta; ( t - t 0 ) x T ( t 0 ) v ( &sigma; ( t 0 ) )
in combination with step 2.3, further transformation can be carried out:
V &sigma; ( t k ) ( x ( t ) ) &le; e N &sigma; l n &lambda; e - &rho; ( t - t 0 ) V &sigma; ( t k ) ( x ( t 0 ) ) &le; e ( N 0 + t - t &tau; * ) l n &lambda; e - &rho; ( t - t 0 ) V &sigma; ( t 0 ) ( x ( t 0 ) ) &le; &alpha; &prime; e - &beta; ( t - t 0 ) V &sigma; ( t k ) ( x ( t 0 ) )
step 2.7 the following form can be obtained according to the last inequality of step 2.3:
V &sigma; ( t k ) ( x ( t ) ) &le; &lambda;e - &rho; ( t - t k ) V &sigma; ( t k - 1 ) ( x ( t k ) ) &le; ... &le; &lambda; k e - &rho; ( t - t 0 ) V &sigma; ( t 0 ) ( x ( t 0 ) )
further conversion is as follows:
V &sigma; ( t k ) ( x ( t ) ) &le; &lambda;e - &rho; ( t - t k ) V &sigma; ( t k - 1 ) ( x ( t k ) )
x T ( t k ) v ( &sigma; ( t k ) ) &le; &lambda;x T ( t k ) v ( &sigma; ( t k - 1 ) )
from 2.3, one can obtain:
V &sigma; ( t k ) ( x ( t ) ) &le; e - &rho; ( t - t k ) V &sigma; ( t k ) ( x ( t k ) ) , t &Element; &lsqb; t k , t k + 1 )
the above inequality is derived as:
V &CenterDot; &sigma; ( t k ) ( x ( t ) ) &le; - &rho;x T v ( &sigma; ( t k ) ) &le; - &rho;V &sigma; ( t k )
and combining 2.3 to obtain:
V &CenterDot; &sigma; ( t k ) ( x ( t ) ) = x T ( A &sigma; ( t k ) T v ( &sigma; ( t k ) ) + z ( &sigma; ( t k ) ) )
step 2.8 integrates the feedback control quantity of the hearth pressure state of the coking furnace obtained from the step 2.2 to the step 2.7, and the form is as follows:
u p ( t ) = K p x ( t ) = 1 v &OverBar; ( p ) T B p T v ( p ) v &OverBar; ( p ) z ( p ) T x ( t ) .
CN201610372893.1A 2016-05-30 2016-05-30 Coking furnace pressure system stable switching controller design method Pending CN106054667A (en)

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5822740A (en) * 1996-06-28 1998-10-13 Honeywell Inc. Adaptive fuzzy controller that modifies membership functions
CN104317321A (en) * 2014-09-23 2015-01-28 杭州电子科技大学 Coking furnace hearth pressure control method based on state-space predictive functional control optimization
CN105159097A (en) * 2015-10-10 2015-12-16 杭州电子科技大学 Multivariable prediction control PID control method for oil-refining heating furnace pressure
CN105608295A (en) * 2016-01-29 2016-05-25 杭州电子科技大学 Multi-objective evolutionary algorithm (MOEA) and radial basis function (RBF) neural network optimization modeling method of coking furnace pressure

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5822740A (en) * 1996-06-28 1998-10-13 Honeywell Inc. Adaptive fuzzy controller that modifies membership functions
CN104317321A (en) * 2014-09-23 2015-01-28 杭州电子科技大学 Coking furnace hearth pressure control method based on state-space predictive functional control optimization
CN105159097A (en) * 2015-10-10 2015-12-16 杭州电子科技大学 Multivariable prediction control PID control method for oil-refining heating furnace pressure
CN105608295A (en) * 2016-01-29 2016-05-25 杭州电子科技大学 Multi-objective evolutionary algorithm (MOEA) and radial basis function (RBF) neural network optimization modeling method of coking furnace pressure

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