Self-adaptive shafting centering control method for complex air bag vibration isolation system

Abstract

The invention discloses a self-adaptive shafting centering control method for a complex air bag vibration isolation system, and the method comprises the steps: initializing a data set D into an empty set, setting an upper limit P1 and a lower limit Pu of a safe working pressure value of each air bag vibration isolator, and determining a control target gamma and an optimal control target gamma < opt > of the air bag vibration isolators; acquiring air bag pressure and control target information of the N air bag vibration isolators at the current moment t, and adding the acquired data into a data set D; updating the correlation coefficient matrix R; judging whether an optimal control target Gamma < opt > is reached in a current system state, selecting a control target needing to be controlled, performing security constraint check according to the control target needing to be controlled, and selecting an airbag vibration isolator number needing to be controlled according to a correlation coefficient; according to the method, a complex system model does not need to be established, the correlation coefficient between the control object and the control target is generated according to the collected data, then the system control is adaptively completed by following the security constraint, and the adaptability to variable working conditions and operating environments is high.

Description

Technical Field

[0001] The invention relates to the field of industrial control technology, and in particular to an adaptive shaft alignment control method for a complex airbag vibration isolation system. Background Art

[0002] In recent years, airbag vibration isolation systems have been widely used in the ship field due to their efficient mechanical noise reduction and vibration isolation performance. Airbag vibration isolation systems usually consist of a group of airbag isolators and a control system. Airbag isolators have the characteristics of low natural frequency and adjustable height, and can provide efficient broadband vibration isolation performance. The control system can monitor the status of the system and actively adjust the airbag pressure according to the control strategy to achieve goals such as posture adjustment of the load-bearing equipment. In particular, when the load-bearing equipment is a ship shafting equipment, the control system can assist in completing high-precision shafting alignment control by monitoring the alignment status, effectively solving the problem of difficulty in taking into account shafting alignment in ship shafting vibration isolation.

[0003] However, with the increasing demand for vibration isolation, the vibration isolation system is showing an integrated development trend. From single-machine vibration isolation to whole-cabin vibration isolation, the types of load-bearing objects are diversified and the excitation sources are also complicated, which puts higher requirements on the intelligence level of vibration isolation devices. Large and complex vibration isolation systems usually have factors such as raft deformation, complex changes in the combined working conditions of load-bearing equipment, and equipment aging, making the centering control of complex airbag vibration isolation systems a challenge.

[0004] On the one hand, in the existing airbag vibration isolation system centering control method, it is generally assumed that the system is a linear time-invariant system. And the control response mechanism model of the system is established based on the center of mass position, weight and other information of the load-bearing equipment. However, the center of mass position, weight and other information of the load-bearing equipment are often not accurately obtained, and with factors such as equipment aging, the physical characteristics of the load-bearing equipment will change. Therefore, the constructed mechanism model itself will have a certain deviation from the actual system, resulting in inaccurate centering control or non-convergence of control. On the other hand, the existing control method is based on pre-set rules to carry out control. When the operating conditions or environment change significantly, the established rules cannot adapt to the dynamically changing environment, and the control effect will also deteriorate accordingly. Summary of the invention

[0005] In order to overcome the above technical defects, the present invention provides an adaptive centering control method for a complex airbag vibration isolation system with strong adaptability and good control effect.

[0006] The present invention provides an adaptive shaft alignment control method for a complex airbag vibration isolation system, wherein the airbag vibration isolation system includes N airbag vibration isolators, each of which is inflated and deflated by controlling a solenoid valve; the alignment control method is specifically as follows:

[0007] S0) Initialize the data set D to an empty set and set the upper limit of the safe working pressure value P of each airbag isolator l and the lower limit P u , determine the control target Γ and the optimal control target Γ of the airbag isolator opt ;

[0008] The control target Γ includes M control targets, which can be expressed as:

[0009] Γ={τ1,…,τ M};

[0010] Optimal control objective Γ opt Expressed as: opt ={τ1 opt ,…,τ M opt};

[0011] The upper and lower limits of the pressure value are P l = {p1 l ,…,p N l}、P u = {p1 u ,…,p N u};

[0012] S1) Obtain the airbag pressure P(t) of N airbag isolators at the current time t = {p1,…,p N} and control target information Γ(t)={τ1,…,τ M}; and add the collected data to the data set D;

[0013] S2) updating the correlation coefficient matrix R;

[0014] S3) Determine whether the optimal control target Γ has been achieved in the current system state opt , if the optimal control target Γ has been achieved opt Then jump to step S1, otherwise jump to step S4;

[0015] S4) Selecting a control object: Selecting a control target to be controlled, performing a safety constraint check based on the control target to be controlled, and selecting the number of the airbag isolator to be controlled based on the correlation coefficient;

[0016] S5) Execute the control action and then jump to step S1.

[0017] Further, in step S2), the correlation coefficient is expressed as:

[0018] R = {r ij |1≤i≤N,1≤j≤M}

[0019] Among them, r ij represents the correlation between the pressure of the i-th airbag isolator and the j-th control target;

[0020] If the data set D = {(P1,Γ1),…,(P K ,Γ K The number of data entries K in )} is less than the set threshold K T , then set the correlation coefficient to r ij =1;

[0021] Otherwise, when K ≥ K T The function formula for calculating the correlation coefficient is:

[0022]

[0023] in, Denotes the data set D = {(P1,Γ1),…,(P K ,Γ K )}, the i-th airbag isolator pressure value in the k-th data, represents the average value of the pressure of the ith airbag isolator in the data set; represents the jth control target component in the kth data in the data set D, Represents the average value of the jth control target of the data set.

[0024] Furthermore, in step S3), the optimal control target is achieved. The condition is expressed as:

[0025]

[0026] That is, each variable in the control objective should satisfy the accuracy constraint, where ξ j Is a constant.

[0027] Furthermore, the specific process of step S4) is as follows:

[0028] S41) Calculate the difference between the current control target and the optimal control target:

[0029]

[0030] S42) Select the control target with the largest absolute value of deviation between the control target and the optimal control target, denoted as Δτ m =max{|Δτ j |},1≤j≤M, where m represents the sequence number in the set;

[0031] S43) Formulate control strategies based on the safety constraints of the system:

[0032] If Δτ m <0, the inflation action is performed first: First, the maximum control target deviation Δτ is calculated m The corresponding auxiliary inflation decision value is recorded as The calculation method is as follows:

[0033]

[0034] if If the elements in are not all zero, set the flag flag charge = 0, and calculate the probability distribution of auxiliary inflation decision The calculation method is as follows:

[0035]

[0036] if All elements in are zero, and the maximum control target deviation Δτ is calculated m The corresponding auxiliary deflation decision value is recorded as The calculation method is as follows:

[0037]

[0038] if If the elements in are not all zero, set the flag flag charge =1, and calculate the probability distribution of auxiliary deflation decision The calculation method is as follows:

[0039]

[0040] if If all the elements in are zero, set the flag flag charge =2;

[0041] If Δτ m > 0, the deflation action is performed first: First, the maximum control target deviation Δτ is calculated m The corresponding auxiliary deflation decision value is recorded as The calculation method is as follows:

[0042]

[0043] if If the elements in are not all zero, set the flag flag charge =1, and calculate the probability distribution of auxiliary deflation decision The calculation method is as follows:

[0044]

[0045] if If all the elements in are zero, then the maximum control target deviation Δτ is calculated m The corresponding auxiliary inflation decision value is recorded as The calculation method is as follows:

[0046]

[0047] if If the elements in are not all zero, set the flag flag charge = 0, and calculate the probability distribution of auxiliary inflation decision The calculation method is as follows:

[0048]

[0049] if If all the elements in are zero, set the flag flag charge =2.

[0050] Furthermore, in step S5), if flag charge =0, execute the inflation action; according to The probability distribution value of selects the number of the airbag isolator that needs to be inflated. Assuming that the selected airbag isolator is No. i, the airbag isolator is inflated with Δp; Δp is a preset fixed value;

[0051] If flag charge =1, execute deflation action; according to The probability distribution value of selects the number of the airbag isolator that needs to be deflated. Assuming that the selected airbag isolator is No. i, the airbag isolator is deflated by Δp, where Δp is a preset fixed value;

[0052] If flag charge =2, the control action cannot be executed and an exception is reported.

[0053] The present invention adopts the correlation coefficient to describe the relationship between the control object and the control target, avoiding the problem of inaccurate modeling of complex models. By collecting operating data, updating the correlation coefficient in real time, and feeding it back to the control algorithm for real-time adjustment, the optimal control strategy can be adaptively calculated.

[0054] This application has the following technical effects:

[0055] 1) The airbag vibration isolation system adaptive control method provided by the present invention does not need to establish a complex system model. It generates the correlation coefficient between the control object and the control target based on the collected data, and then adaptively completes the system control in accordance with the safety constraints. It has strong adaptability to variable working conditions and operating environments;

[0056] 2) The correlation coefficient used in the present invention is updated in real time through the collected system operation data, without the need for manual intervention, and has a high degree of intelligence;

[0057] 3) The control method provided by the present invention has a simple structure, small amount of calculation, easy implementation and deployment, and good control effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a schematic diagram of the composition of a typical airbag vibration isolation system;

[0059] Figure 2 It is a schematic flow chart of the control method of the present invention;

[0060] Figure 3 It is a training curve of the control effect of the present invention in a simulation environment. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0062] like Figure 1 As shown, a typical airbag vibration isolation system usually includes a group of airbag vibration isolators and a control system. The airbag vibration isolators can directly or indirectly support the load-bearing equipment through the raft. The control system mainly includes an acquisition module, a calculation module and a control module. The acquisition module is responsible for collecting the operating status of the system, the working condition of the equipment, etc., for example, it can collect the alignment status of the shafting equipment. The calculation module is responsible for logical operations and control strategy formulation. The control module is responsible for executing control actions, such as completing the inflation / deflation action of the airbag vibration isolator through the inflation / deflation control unit, realizing the attitude control of the raft, and then adjusting the alignment status of the shafting equipment.

[0063] Adaptive shaft alignment control method for complex airbag vibration isolation system, such as Figure 3 The steps shown include:

[0064] S0) is initialized. The initial data set D is an empty set. Assume that the airbag vibration isolation system includes 8 airbag vibration isolators, and each airbag vibration isolator is inflated and deflated by controlling the solenoid valve. Then, the combination of airbag pressure values ​​is expressed as P = (p1,...,p8); for the safe working pressure of the airbag, a safety constraint is set. Assuming that the upper and lower limits of the pressure values ​​of all airbag vibration isolators are the same, respectively: 2.0Mpa and 0.8Mpa, the safety constraint can be expressed as P l = {p1 l ,…,p8 l}={0.8Mpa,…,0.8Mpa}、P u= {p1 u ,…,p8 u}={2.0Mpa,…,2.0Mpa}. Determine the control target Γ and the optimal control target Γ opt Taking the axis alignment control as an example, the control target is generally four components: vertical offset τ1, horizontal offset τ2, vertical skew τ3 and horizontal skew τ4, expressed as: Γ = {τ1, τ2, τ3, τ4}, the optimal control target offset value and skew value are both 0, that is: Γ opt ={0,0,0,0}.

[0065] S1) Obtain the airbag pressure P(t) = {p1, ..., p8} and the corresponding control target information Γ(t) = {τ1, ..., τ4} of the airbag vibration isolation system at the current time t; and add the collected data to the data set D.

[0066] S2) Update the correlation coefficient matrix R. There are 8 airbag isolators and 4 centering state components in the system. Therefore, the correlation between the pressure value of the airbag isolator and the 4 centering states is calculated. The correlation coefficient is expressed as:

[0067] R = {r ij |1≤i≤8,1≤j≤4}

[0068] Among them, r ij Represents the correlation between the pressure of the i-th airbag and the j-th control target component.

[0069] If the data set D = {(P1,Γ1),…,(P K ,Γ K The number of data entries K in )} is less than the set threshold K T , then set the correlation coefficient to r ij =1.

[0070] Otherwise, when K ≥ K T The function formula for calculating the correlation coefficient is:

[0071]

[0072] in, Denotes the data set D = {(P1,Γ1),…,(P K ,Γ K )}, the i-th airbag isolator pressure value in the k-th data, Represents the average pressure value of the i-th airbag isolator in the data set. represents the jth control target component in the kth data in the data set D, Represents the average value of the jth control target component of the data set. In a typical airbag vibration isolation system prototype, the updated correlation matrix is:

[0073]

[0074] Among them, r 11 =-0.12 indicates that there is a negative correlation between the pressure of airbag isolator No. 1 and the vertical displacement, and the correlation value is 0.12.

[0075] S3) Determine whether the optimal control target Γ has been achieved in the current system state opt , if the optimal control target Γ has been reached opt Then jump to step S1, otherwise jump to step S4;

[0076] Achieve optimal control goals The condition is expressed as:

[0077]

[0078] That is, each variable in the control objective should satisfy the accuracy constraint, where ξ j is a constant. In engineering applications, it is generally believed that when the vertical / horizontal offset is less than 0.5mm and the vertical / horizontal deflection is less than 0.5mm / m, the system is in the center state. Therefore, ξ is set j =0.5.

[0079] S4) Select the control object. Select the control target sub-item to be controlled. Perform a safety constraint check based on the target component to be controlled, and select the airbag isolator number to be controlled based on the correlation coefficient.

[0080] S41) Calculate the difference between the current control target and the optimal control target:

[0081]

[0082] Assume that the difference between the current centering state and the optimal centering state is: ΔΓ={2.04,-2.40,0.12,3.71}.

[0083] S42) Select the component with the largest absolute value of the deviation between the control target and the optimal control target, denoted as Δτ m =max{|Δτ j |},≤1j≤M, where m represents the sequence number in the set. At this time, the fourth component has the largest absolute value offset, that is, the horizontal skew Δτ4=3.71, m=4.

[0084] S43) formulates a control strategy based on the safety constraints of the system. At this time, if Δτ m =3.71>0, the deflation action is performed first. First, calculate the maximum target deviation Δτ m The corresponding auxiliary deflation decision value is recorded as The calculation method is as follows:

[0085]

[0086] According to the maximum offset and correlation matrix, and the current airbag isolator pressure value is: P = {1.5,1.5,1.5,1.5,1.5,1.5,1.5}, it can be calculated that:

[0087]

[0088] because If the elements in are not all zero, set the flag flag charge =1, and calculate the probability distribution of auxiliary deflation decision The calculation method is as follows:

[0089]

[0090] The probability distribution of auxiliary deflation decision is obtained:

[0091]

[0092] S5) Execute the control action and then jump to step S1.

[0093] If flag charge =0, execute the inflation action. The probability distribution value of is used to select the number of the airbag isolator that needs to be inflated. Assuming that the airbag isolator No. i is selected, the airbag isolator is inflated by Δp, where Δp is a preset fixed value.

[0094] If flag charge =1, execute deflation action. The probability distribution value of is used to select the number of the airbag isolator that needs to be deflated. Assuming that the airbag isolator No. i is selected, the airbag isolator is deflated by Δp, where Δp is a preset fixed value.

[0095] If flag charge =2, the control action cannot be executed and an exception is reported.

[0096] Considering the flag obtained in step S4 charge =1, here we use The probability distribution of the airbag isolator number to be deflated is selected. The probability of No. 1 airbag isolator being selected is 31%, the probability of No. 2 airbag isolator being selected is 26%, and so on. Assuming that the airbag isolator selected here is No. 2, the airbag isolator No. 2 is deflated to reduce its air pressure by Δp = 0.1Mpa.

[0097] Figure 3 The implementation results shown are the control process of using the adaptive control algorithm to control the airbag vibration isolation system. Assuming that the control is performed once per second, it can be seen that in about 60 seconds, the controller can quickly achieve the centering control from the shaft misalignment state and achieve the control target, and the control effect is relatively stable.

Claims

1. An adaptive shaft alignment control method for a complex airbag vibration isolation system, wherein the airbag vibration isolation system comprises N airbag vibration isolators, each of which is inflated and deflated by controlling a solenoid valve; the method is characterized in that: The centering control method is specifically as follows: S0) Initialize the data set D to an empty set and set the upper limit of the safe working pressure value P of each airbag isolator l and the lower limit P u , determine the control target Γ and the optimal control target Γ of the airbag isolator opt ; The control target Γ includes M control targets, which can be expressed as: C={τ1,…,τ M }; Optimal control objective Γ opt Expressed as: opt ={τ1 opt ,…,τ M opt }; The upper and lower limits of the pressure value are P l = {p1 l ,…,p N l }、P u = {p1 u ,…,p N u }; S1) Obtain the airbag pressure P(t) of N airbag isolators at the current time t = {p1,…,p N } and control target information Γ(t)={τ1,…,τ M }; and add the collected data to the data set D; S2) updating the correlation coefficient matrix R; S3) Determine whether the optimal control target Γ has been achieved in the current system state opt , if the optimal control target Γ has been achieved opt Then jump to step S1, otherwise jump to step S4; S4) Selecting a control object: Selecting a control target to be controlled, performing a safety constraint check based on the control target to be controlled, and selecting the number of the airbag isolator to be controlled based on the correlation coefficient; S5) Execute the control action and then jump to step S1.

2. According to the adaptive shaft alignment control method for complex airbag vibration isolation system according to claim 1, in step S2), the correlation coefficient is expressed as: R={r ij |1≤i≤N,1≤j≤M} in, r ij represents the correlation between the pressure of the i-th airbag isolator and the j-th control target; If the data set D = {(P1,Γ1),…,(P K ,Γ K The number of data entries K in )} is less than the set threshold K T , then set the correlation coefficient to r ij =1; Otherwise, when K ≥ K T The function formula for calculating the correlation coefficient is: in, Denotes the data set D = {(P1,Γ1),…,(P K ,Γ K )}, the i-th airbag isolator pressure value in the k-th data, represents the average value of the pressure of the ith airbag isolator in the data set; represents the jth control target component in the kth data in the data set D, Represents the average value of the jth control target of the data set.

3. According to the adaptive shaft alignment control method for complex airbag vibration isolation system in claim 2, in step S3), the optimal control target is achieved. The condition is expressed as: That is, each variable in the control objective should satisfy the accuracy constraint, where ξ j Is a constant.

4. According to the adaptive shaft alignment control method for complex airbag vibration isolation system according to claim 3, the specific process of step S4) is: S41) Calculate the difference between the current control target and the optimal control target: S42) Select the control target with the largest absolute value of deviation between the control target and the optimal control target, denoted as Δτ m =max{|Δτ j |},1≤j≤M, where m represents the sequence number in the set; S43) Formulate control strategies based on the safety constraints of the system: If Δτ m <0, the inflation action is performed first: First, the maximum control target deviation Δτ is calculated m The corresponding auxiliary inflation decision value is recorded as The calculation method is as follows: if If the elements in are not all zero, set the flag flag charge = 0, and calculate the probability distribution of auxiliary inflation decision The calculation method is as follows: if All elements in are zero, and the maximum control target deviation Δτ is calculated m The corresponding auxiliary deflation decision value is recorded as The calculation method is as follows: if If the elements in are not all zero, set the flag flag charge =1, and calculate the probability distribution of auxiliary deflation decision The calculation method is as follows: if If all the elements in are zero, set the flag flag charge =2; If Δτ m > 0, the deflation action is performed first: First, the maximum control target deviation Δτ is calculated m The corresponding auxiliary deflation decision value is recorded as The calculation method is as follows: if If the elements in are not all zero, set the flag flag charge =1, and calculate the probability distribution of auxiliary deflation decision The calculation method is as follows: if If all the elements in are zero, then the maximum control target deviation Δτ is calculated m The corresponding auxiliary inflation decision value is recorded as The calculation method is as follows: if If the elements in are not all zero, set the flag flag charge = 0, and calculate the probability distribution of auxiliary inflation decision The calculation method is as follows: if If all the elements in are zero, set the flag flag charge =2.

5. According to the adaptive shaft alignment control method for complex airbag vibration isolation system according to claim 4, in step S5), if flag charge =0, execute the inflation action; according to The probability distribution value of selects the number of the airbag isolator that needs to be inflated. Assuming that the selected airbag isolator is No. i, the airbag isolator is inflated with Δp; Δp is a preset fixed value; If flag charge =1, execute deflation action; according to The probability distribution value of selects the number of the airbag isolator that needs to be deflated. Assuming that the selected airbag isolator is No. i, the airbag isolator is deflated by Δp, where Δp is a preset fixed value; If flag charge =2, the control action cannot be executed and an exception is reported.

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