Control method for inhibiting buffeting of electric steering engine servo system

Abstract

The invention relates to the technical field of servo control, in particular to a control method for restraining buffeting of an electric steering engine servo system. The control method comprises the following steps: step 1, establishing a transition process mathematical model, and obtaining a transited steering engine instruction; 2, an angular position signal of the electric steering engine is measured and fed back, the angular position signal is compared with a steering engine instruction after input transition, an error signal is formed, and the error signal comprises a rotation angle error e and an error change rate ec; and step 3, performing fuzzification processing according to the error signal, performing fuzzy reasoning through a fuzzy rule, and performing defuzzification, so that a fuzzy controller outputs PID control parameter real-time variation, and the purpose of suppressing the buffeting phenomenon of the electric steering engine servo system is achieved. Therefore, the influence of the existing nonlinear link on the servo system of the electric steering engine is solved, and the buffeting phenomenon of the electric steering engine is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of servo control, and in particular to a control method for suppressing the vibration of an electric steering gear servo system. Background Art

[0002] Due to the significant nonlinear links inside the electric steering gear, there are gaps in the transmission mechanisms such as gears and screws during the transmission process. The transmission structural parts will produce micro-deformations after being subjected to torque. Moreover, under the joint action of the rudder surface inertia, the stiffness of the electric steering gear servo system will be reduced, which can easily cause the steering gear to vibrate. The current method to overcome the vibration of electric steering gears mainly relies on increasing structural damping. The friction of the system during the transmission process is increased by adding damping rings during the transmission process, adding gaskets at both ends of the screw, and increasing the screw preload, so as to suppress the vibration of the electric steering gear.

[0003] The existing method of suppressing electric servo vibration has obvious defects. Since increasing friction is equivalent to adding additional load, this method will cause a certain degree of performance degradation. And as the structural parts wear, the friction will decrease, reducing the vibration suppression effect. The vibration phenomenon will gradually reappear as the structural parts wear, and the vibration suppression effect is unstable. In addition, this method requires additional structural parts, which increases product costs.

[0004] Among them, there must be gaps in the coordination process of the transmission parts such as the internal gears and lead screws of the electric servo. As the servo wears during operation, the gap will further increase. When the servo moves through the gap, it will cause impact and easily cause different degrees of fluttering, and even self-excited oscillation in severe cases. The fluttering phenomenon will have a serious adverse effect on the performance of the servo and reduce the service life of the servo. Summary of the invention

[0005] In order to solve the problem of the influence of existing nonlinear links on the electric steering gear servo system and reduce the electric steering gear jitter phenomenon, the present invention provides a control method for suppressing the jitter of the electric steering gear servo system. The method improves the PID control algorithm and reduces the steering gear jitter by combining the transition process of instruction arrangement with fuzzy control method.

[0006] In a first aspect, the present invention provides a control method for suppressing the vibration of an electric steering gear servo system, comprising the following steps:

[0007] Step 1: Establish a mathematical model of the transition process and obtain the steering gear instructions after the transition;

[0008] Step 2: Measure the angular position signal of the electric servo for feedback, compare it with the servo command after the input transition, and form an error signal, wherein the error signal includes the angular error e and the error change rate ec;

[0009] Step 3: Perform fuzzy processing on the error signal, perform fuzzy reasoning through fuzzy rules, and then defuzzify to achieve the real-time change of the PID control parameters output by the fuzzy controller, so as to achieve the purpose of suppressing the vibration phenomenon of the electric steering gear servo system.

[0010] In some embodiments, in step 1, the transition process mathematical model is:

[0011]

[0012] Where r is the speed coefficient; m0 is the bandwidth coefficient; d, a, a0, a1, a2, Fh and y are the intermediate variables of the operation; x1 is the filtered signal; x2 is the analyzed differential signal.

[0013] In some embodiments, in step 2, the angular position signal of the electric servo is measured and the angular error and the error change rate are constructed; the angular position feedback signal y is used to perform feedback comparison with the servo command r after the electric servo input transition to obtain the angular error e, e=e(k)=r(k)-y(k), where k is the kth value in the discrete state; the angular error e(k) at this moment is compared with the angular error e(k-1) at the previous moment to obtain the error change rate ec, ec=ec(k)=e(k)-e(k-1).

[0014] In some embodiments, in step 3, the fuzzification process includes: using the rotation angle error e and the error change rate ec as the fuzzification input, and the membership degree u i (e) and u j (ec) is the fuzzy output, and the membership function of the input and output variables is established; among them, i, j∈{0, 1, 2, 3, 4, 5, 6}, the membership function of the angular error e and the error change rate ec is directly drawn through the program instruction function of Matlab.

[0015] In some embodiments, in step 3, the fuzzy reasoning is: using fuzzy rules to calculate the fuzzy reasoning output, and the fuzzy reasoning output is: The fuzzy rules are:

[0016] Rule ij:IF e=u i and ec=u j THEN u=u ij .

[0017] In some embodiments, in step 3, the defuzzification is: increasing the speed coefficient α to adjust the adjustment speed of the fuzzy controller on the controller parameters; the fuzzy controller output is:

[0018] In order to solve the problem of the influence of the existing nonlinear link on the electric steering gear servo system and reduce the problem of electric steering gear flutter, the present invention has the following advantages:

[0019] By adopting the technical solution of the present invention, a transition process is arranged for the steering gear command to improve the tracking characteristics of the electric steering gear;

[0020] Through the technical solution of the present invention, the control parameters of the fuzzy controller are dynamically adjusted to reduce system overshoot and suppress the vibration of the electric steering gear. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 A schematic diagram of a process for suppressing the vibration of an electric steering gear servo system is shown;

[0022] Figure 2 A schematic diagram of the working principle of a servo system for suppressing an electric steering gear is shown;

[0023] Figure 3 Shows Figure 2 The schematic diagram of the fuzzy controller operation process shown in;

[0024] Figure 4 Shows Figure 2 Schematic diagram of the step response of the electric servo shown in;

[0025] Figure 5 A schematic diagram showing the comparison of the command and command speed of the electric steering gear servo system before and after the transition process;

[0026] Figure 6 is the membership function of the fuzzy controller;

[0027] Figure 7 is a schematic diagram of the fuzzy controller output surface;

[0028] Figure 8 It is a schematic diagram of the vibration suppression effect of the electric steering gear servo system. DETAILED DESCRIPTION

[0029] The present disclosure will now be discussed with reference to several exemplary embodiments. It should be understood that these embodiments are discussed only to enable those skilled in the art to better understand and thus implement the present disclosure, rather than implying any limitation on the scope of the present disclosure.

[0030] As used herein, the term "including" and its variants are to be interpreted as open-ended terms meaning "including but not limited to". The term "based on" is to be interpreted as "based at least in part on". The terms "one embodiment" and "an embodiment" are to be interpreted as "at least one embodiment". The term "another embodiment" is to be interpreted as "at least one other embodiment". The orientation or position relationship indicated by the terms "upper", "lower", "left", "right", "front", "back", "top", "bottom", "inner", "outer", "vertical", "horizontal", "lateral", "longitudinal" and the like is based on the orientation or position relationship shown in the accompanying drawings. These terms are mainly for better describing the present application and its embodiments, and are not used to limit the indicated devices, elements or components to have a specific orientation, or to be constructed and operated in a specific orientation. In addition, in addition to being used to indicate an orientation or position relationship, some of the above terms may also be used to indicate other meanings, such as the term "upper" may also be used to indicate a certain dependency or connection relationship in some cases. For those of ordinary skill in the art, the specific meanings of these terms in this application can be understood according to the specific circumstances. In addition, the terms "install", "set", "provided with", "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral structure; it can be a mechanical connection, or an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, or it can be an internal connection between two devices, elements or components. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to the specific circumstances. In addition, the terms "first", "second", etc. are mainly used to distinguish different devices, elements or components (the specific types and structures may be the same or different), and are not used to indicate or imply the relative importance and quantity of the indicated devices, elements or components. Unless otherwise specified, "plurality" means two or more.

[0031] This embodiment discloses a control method for suppressing the vibration of an electric steering gear servo system. Figures 1 to 3 As shown, the method comprises the following steps:

[0032] Step 1: Establish a mathematical model of the transition process and obtain the steering gear instructions after the transition;

[0033] Step 2: Measure the angular position signal of the electric servo for feedback, compare it with the servo command after the input transition, and form an error signal, wherein the error signal includes the angular error e and the error change rate ec;

[0034] Step 3: Perform fuzzy processing on the error signal, perform fuzzy reasoning through fuzzy rules, and then defuzzify to achieve the real-time change of the PID control parameters output by the fuzzy controller, so as to achieve the purpose of suppressing the vibration phenomenon of the electric steering gear servo system.

[0035] In this embodiment, a control method for suppressing the chattering of an electric servo servo system is provided. This method adds a transition process link after the electric servo servo system receives the input of the servo command, and outputs the transitioned command to the servo system after processing the command. When the electric servo receives a step command before the improvement, due to the sudden change of the command angle, the speed signal of the command is discontinuous. When the error signal e is solved by the PID controller to control the electric servo to follow the command, it is easy to cause chattering. By arranging the transition process for the command, the chattering of the servo caused by the sudden change of the command can be reduced, and the overshoot of the electric servo can be reduced.

[0036] In addition, this method adds a fuzzy controller before the PID operation. The fuzzy controller adjusts the PID internal control parameters in real time according to the current system state to suppress the servo vibration. The response curve of the servo when the vibration occurs is shown in Figure 4 As shown in the figure, in the AB segment, the system changes are consistent with expectations, and the control parameters can be appropriately reduced; in the BC segment, the system is far away from the expected motion trajectory, and the parameters need to be appropriately increased to quickly pull the curve back. The fuzzy control algorithm enables the electric servo to adaptively adjust the control parameters when vibration occurs, thereby suppressing vibration, reducing the number of oscillations, and reducing the overshoot of the electric servo servo system.

[0037] In some embodiments, in step 1, the transition process mathematical model is:

[0038]

[0039] Where r is the speed coefficient; m0 is the bandwidth coefficient; d, a, a0, a1, a2, Fh and y are the intermediate variables of the operation; x1 is the filtered signal; x2 is the analyzed differential signal.

[0040] In this embodiment, a transition process is arranged for the steering gear command. The transition process can change the sudden step signal into a continuously changing transition command. The differential speed signal of the step signal has a large sudden change, which is not conducive to the controller's solution. The differential speed signal of the transition process is arranged to change continuously, which is conducive to improving the tracking characteristics of the electric steering gear servo system. Figure 5 In this application, the speed coefficient r in the transition process algorithm can adjust the speed of the transition process to track the command. By adjusting the appropriate parameter r, the control effect of the electric steering gear servo system can be optimized and the system overshoot and jitter can be reduced.

[0041] In some embodiments, in step 2, the angular position signal of the electric servo is measured and the angular error and the error change rate are constructed; the angular position feedback signal y is used to perform feedback comparison with the servo command r after the electric servo input transition to obtain the angular error e, e=e(k)=r(k)-y(k), where k is the kth value in the discrete state; the angular error e(k) at this moment is compared with the angular error e(k-1) at the previous moment to obtain the error change rate ec, ec=ec(k)=e(k)-e(k-1).

[0042] In this embodiment, through the above settings, the rotation angle error and the error change rate after the input transition can be obtained and input into the fuzzy controller, so that the electric steering gear servo system enters the fuzzy processing process.

[0043] In some embodiments, in step 3, the fuzzification process includes: taking the rotation angle error e and the error change rate ec as the fuzzification input, and the membership degree u i (e) and u j (ec) is the fuzzy output, and the membership function of the input and output variables is established; among them, i, j∈{0, 1, 2, 3, 4, 5, 6}, the membership function of the angular error e and the error change rate ec is directly drawn through the program instruction function of Matlab.

[0044] In this embodiment, determining the fuzzy language variables is the first step in designing fuzzy control. When selecting the language variable values, the flexibility and meticulousness of the control rules should be considered, and the simplicity and ease of implementation should be taken into account. Generally, when designing fuzzy control, for language variables such as error, error change rate and change of control quantity, "positive large (PB)", "positive middle (PM)", "positive small (PS)", "zero (Z)", "negative small (NS)", "negative middle (NM)" and "negative large (NB)" are usually used to describe them.

[0045] In this embodiment, the domain of the angular error e is defined as {-15, -5, -2, 0, 2, 5, 15}, and the domain of the error change rate ec is defined as {-15, -5, -2, 0, 2, 5, 15}. In order to better linearize the system, the same membership function is used, and the membership function adopts a linear function, which can greatly reduce the complexity of the operation. Therefore, the same graphical description can be used. The membership function is as follows: Figure 6 shown.

[0046] When the fuzzy controller is running, the current angular error e and error change rate ec can be fuzzified according to the membership function to obtain the membership of the fuzzy subset corresponding to the current e and ec: i (e) and u j (ec), where i, j∈{0, 1, 2, 3, 4, 5, 6}.

[0047] In some embodiments, in step 3, the fuzzy reasoning is: using fuzzy rules to calculate the fuzzy reasoning output, and the fuzzy reasoning output is: The fuzzy rules are:

[0048] Rule ij:IF e=u i and ec=u j THEN u=u ij .

[0049] In this embodiment, through the above settings, fuzzy rules are used to calculate the fuzzy reasoning output, and the center of gravity method is used to perform defuzzification calculation when the fuzzy output is output, so the output of the fuzzy controller can be calculated.

[0050] According to the fuzzy rule table, see Table 1.

[0051] Table 1 Fuzzy rule design

[0052]

[0053] Among them, the surface diagram of the change of the fuzzy controller output control parameter is shown in Figure 7 In this application, the fuzzy controller solves the input error e and the error change rate ec, outputs the real-time change of the PID control parameter, and suppresses the chattering by adjusting the control parameter size online according to the system state.

[0054] In some embodiments, in step 3, the defuzzification is: increasing the speed coefficient α to adjust the adjustment speed of the fuzzy controller on the controller parameters; the fuzzy controller output is:

[0055] In this embodiment, in order to facilitate parameter setting, a speed coefficient α is added to the fuzzy controller algorithm to adjust the speed at which the fuzzy controller adjusts the controller parameters. Therefore, the final fuzzy controller output is: Among them, by adjusting the speed coefficient α of the fuzzy controller, the real-time change rate of the PID control parameters can be adjusted to adjust the vibration and overshoot suppression effect of the electric servo system. Experiments have shown that parameter tuning can achieve a better vibration suppression effect. The control effect comparison before and after the improvement by this method is shown in Figure 8 By comparing the control effects, it can be seen that the proposed method can significantly suppress the overshoot and jitter of the electric servo step response.

[0056] In summary, through the technical solution of the present invention, a transition process is arranged for the steering gear command to improve the tracking characteristics of the electric steering gear;

[0057] Through the technical solution of the present invention, the control parameters of the fuzzy controller are dynamically adjusted to reduce system overshoot and suppress the vibration of the electric steering gear.

[0058] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the present invention can be implemented in other specific forms without departing from the spirit or essential features of the present invention. Therefore, the embodiments should be considered exemplary and non-restrictive in all respects, and the scope of the present invention is defined by the appended claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims be included in the present invention.

[0059] In addition, it should be understood that although the present specification is described according to embodiments, not every embodiment contains only one independent technical solution. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation methods that those skilled in the art can understand.

Claims

1. A control method for suppressing the chattering of an electric steering gear servo system, characterized in that: The steps include: Step 1: Establish a mathematical model of the transition process and obtain the steering gear instructions after the transition; Step 2: Measure the angular position signal of the electric servo for feedback, compare it with the servo command after the input transition, and form an error signal, wherein the error signal includes the angular error e and the error change rate ec; Step 3: Perform fuzzy processing on the error signal, perform fuzzy reasoning through fuzzy rules, and then defuzzify to achieve the real-time change of the PID control parameters output by the fuzzy controller, so as to achieve the purpose of suppressing the vibration phenomenon of the electric steering gear servo system.

2. A control method for suppressing the chattering of an electric steering gear servo system as claimed in claim 1, characterized in that: In step 1, the transition process mathematical model is: Where r is the speed coefficient; m0 is the bandwidth coefficient; d, a, a0, a1, a2, Fh and y are the intermediate variables of the operation; x1 is the filtered signal; x2 is the analyzed differential signal.

3. A control method for suppressing the chattering of an electric steering gear servo system as claimed in claim 1, characterized in that: In the step 2, the angular position signal of the electric servo is measured and the angular error and the error change rate are constructed; the angular position feedback signal y is used to perform feedback comparison with the servo command r after the electric servo input transition to obtain the angular error e, e=e(k)=r(k)-y(k), where k is the kth value in the discrete state; the angular error e(k) at this moment is compared with the angular error e(k-1) at the previous moment to obtain the error change rate ec, ec=ec(k)=e(k)-e(k-1).

4. A control method for suppressing the chattering of an electric steering gear servo system as claimed in claim 1, characterized in that: In step 3, the fuzzy processing includes: taking the rotation angle error e and the error change rate ec as the fuzzy input, and the membership degree u i (e) and u j (ec) is the fuzzy output, and the membership function of the input and output variables is established; among them, i, j∈{0, 1, 2, 3, 4, 5, 6}, the membership function of the angular error e and the error change rate ec is directly drawn through the program instruction function of Matlab.

5. A control method for suppressing the chattering of an electric steering gear servo system as claimed in claim 4, characterized in that: In step 3, the fuzzy reasoning is: using fuzzy rules to calculate the fuzzy reasoning output, and the fuzzy reasoning output is: The fuzzy rules are: Rule ij:IF e=u i and ec=u j THEN u=u ij 。 6. A control method for suppressing the chattering of an electric steering gear servo system as claimed in claim 5, characterized in that: In step 3, the defuzzification is: increasing the speed coefficient α to adjust the adjustment speed of the fuzzy controller to the controller parameters; the output of the fuzzy controller is:

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