TWI546636B - An intelligent adaptive control system - Google Patents

Description

Intelligent adjustment control system

The present invention relates to a control system, and more particularly to a control system with intelligent adjustment.

Most of the current control systems use the traditional Proportional-Integral-Derivative Control (PID). The input and output values have not only the disadvantage of large error, but also the control parameters cannot be self-contained. Adjustment, therefore, will cause the system to perform inefficiently, and because the control parameters cannot be self-adjusted, the control system must be modified under different control targets (such as different target temperature control), that is, the original settings are good. The control parameters must be re-set in order to respond to different control objectives, which will also result in cost.

In addition, the target controlled body usually has multiple physical coupling characteristics, so the output value of the control system is often affected by environmental instability, causing delays in the control system. For example, if the control system is a heating system, Then heating the stage will delay the control system and produce an unstable output due to environmental factors such as mass, heat radiation, and convection.

In view of this, the present invention provides an improved control system that has the effect of self-adjusting control parameters and can address the instability of system delays, thereby solving the above problems.

An object of the present invention is to provide a control system with intelligent adjustment, comprising: an input unit for acquiring an input signal input by a user; and an error calculation unit for calculating the input signal and an output signal to generate An error signal; a feedforward operation unit, performing a feedforward control rule on the input signal; a feedback operation unit performing a feedback control law related to the error signal on the input signal; and an optimization unit for Adjusting the feedforward control rule and the feedback control rule; and an operation combining unit, generating a controller output according to the operation result of the feedforward operation unit and the feedback operation unit, and transmitting the controller output to a receiver a control unit; wherein the optimization unit adjusts the feedforward control law and the feedback control rule according to the error signal. It can be seen that, by adjusting the optimization unit, the control system of the present invention has the function of self-adjusting parameters, thereby solving the problem that the traditional PID must be reset under different control objectives.

In an embodiment, the optimization unit performs a feedforward control method for the feedforward operation unit and an optimization adjustment performed by the feedback control rule of the feedback operation unit based on a Lyapunov function.

In an embodiment, the intelligent adjustment control system further includes a compensation unit, that is, a second operation combination unit, the compensation unit is configured to perform operation on the controller output to eliminate delay of the system, and the second operation combination unit The result of outputting the controller through the controlled body is combined with the operation result of the control output through the compensation unit, and is transmitted back to the error calculating unit. Thereby, the delay term of the system can be eliminated through continuous feedback, so that the output of the system is stable.

1‧‧‧Control system

10, 100‧‧‧ input unit

12, 120‧‧‧ error calculation unit

14, 140‧‧‧ feedforward computing unit

15‧‧‧Feed-for-control law

16, 160‧‧‧Return arithmetic unit

17‧‧‧Reward control law

18, 180‧‧‧Optimization unit

20, 200‧‧‧ computing combination unit

22, 220‧‧‧ Output unit

240‧‧‧Compensation unit

260‧‧‧Second operation combining unit

Yd‧‧‧Input signal

e‧‧‧Error signal

y _old ‧‧‧Output signal generated by previous execution

y‧‧‧Output signal

e _new ‧‧‧ new error signal

Prediction transfer function G ‧‧‧

Y ‧‧‧Control output

U ‧‧‧Control input

M, C, K‧‧‧Reciprocal of system parameters

u‧‧‧Controller output

U‧‧‧Control input

u _ff ‧‧‧Feed-for-control law

u _fb ‧‧‧ feedback control law

Ym‧‧‧Reward signal

α _k , α _c , α _M , β _K , β _C , β _M , α _i , α _p , α _d , β _i , β _p , β _d ‧‧‧adaptive gain parameters

x ₁ ‧ ‧ integral of error signal e over time

G _m ‧‧‧ special transfer function

x ₃ ‧‧‧Error signal e to time differentiation

e ^{-Ts ‧‧‧delay} parameters

ym _old ‧‧‧ previous execution generated feedback signal

S21~S28‧‧‧Steps

S51~S58‧‧‧Steps

k _p ‧‧‧Proportional control gain

k _d ‧‧‧ differential control gain

k _i ‧‧‧Integral control gain

1 is a schematic diagram of a system architecture of a first embodiment of a control system with intelligent adjustment according to the present invention.

Figure 2 is a system execution flow chart of the first embodiment of the present invention.

Figure 3 (A) is a schematic diagram of simulated data of a conventional PID control system under temperature control.

Figure 3 (B) is a schematic diagram of another analog data of a conventional PID control system under temperature control.

FIG. 3(C) is a schematic diagram of simulation data of the control system 1 with intelligent adjustment according to the present invention under temperature control.

FIG. 3(D) is a schematic diagram of another simulation data of the control system 1 with intelligent adjustment according to the present invention under temperature control.

4 is a schematic diagram of a system architecture of a second embodiment of the intelligent control system 1 of the present invention.

Figure 5 is a system execution flow diagram of a second embodiment of the present invention.

Fig. 6(A) is a schematic view showing the simulation data of the second embodiment of the control system 1 with intelligent adjustment according to the present invention under temperature control.

Fig. 6(B) is a schematic view showing another simulation data of the second embodiment of the intelligent control system 1 of the present invention under temperature control.

1 is a schematic diagram of a system architecture of a first embodiment of a control system 1 with intelligent adjustment according to the present invention. As shown in FIG. 1, the control system 1 with intelligent adjustment includes an input unit 10 and an error calculation unit. 12. A feedforward operation unit 14, a feedback operation unit 16, an optimization unit 18, an operation combining unit 20, and an output unit 22. The input unit 10 is coupled to the error calculation unit 12 and the feedforward operation unit 14, and the error calculation unit 12 is coupled to the feedback control operation unit 16, and the feedforward The computing unit 14 continues to be coupled to the computing unit 16 and the computing unit 20. Thereafter, a signal output by the computing unit 20 controls a controlled object, and the controlled result of the controlled object is controlled. The output unit 22 is output, and the output unit continues to be coupled to the error calculation unit 12 to transmit the controlled result to the error calculation unit 12. In addition, the error calculation unit 12 is also coupled to the optimization unit 18, which is continuously coupled to the feedforward operation unit 14 and the feedback operation unit 16.

In a preferred embodiment, the various units of the present invention are comprised of algorithms and are executed by a device having a microprocessor.

In an embodiment, the input unit 10 is configured to obtain an input signal y _d input by a user. For example, if the intelligent control system 1 of the present invention is used for temperature control, the input is The signal y _d is a target temperature value set by the user, and the controlled object can be controlled to reach the target temperature value, and if the control system 1 of the present invention is used for position control, the input signal y _d That is, a target position set by the user can be controlled to reach the target position. The error calculation unit 12 is an operation program for subtracting the input signal y _d from an output signal y _old generated by the previous execution of the control system 1 to obtain an error signal e, and the error signal e It is transmitted to the feedback arithmetic unit 16. The feedforward computing unit 14 is a feedforward controller for performing an operation on the input signal y _d according to a feedforward control law 15 for the purpose of feedforward control. The feedback computing unit 16 is a feedback controller, and the error signal e is obtained by the error calculating unit 12, and an operation is performed on the error signal e according to a feedback control law 17 to achieve the purpose of feedback control. . The operation combining unit 20 is an arithmetic program that generates a controller output u according to the operation result of the feedforward operation unit 14 and the feedback operation unit 16, and controls the controlled body by using the controller output u. After the controlled body receives the control of the controller output u, the output unit 22 outputs the actual control result to generate a new output signal y, and the output signal y is transmitted back to the error calculating unit by the output unit 22. At 12, a new addition and subtraction operation is performed, and a new error signal e _{new is} generated, and then the error signal e _{new is} again subjected to the feedback operation unit 16 for another feedback operation.

It is worth noting that the present invention is further provided with the optimization unit 18. The optimization unit 18 can produce an adaptive control of the overall system, so that the system achieves the effect of self-regulating parameters. In operation, the optimization unit 18 obtains the error signal e from the error calculation unit 12, and the feedforward algorithm 15 and the feedback operation unit 16 of the feedforward operation unit 14 according to the error signal e. The feedback algorithm 17 is adjusted. In other words, since the control system 1 generates a new error signal e _new to replace the original error signal e every time the control flow is executed, the feedforward algorithm 15 of the present invention The feedback algorithm 17 will constantly change according to the change of the error signal e. Thereby, the effect of the control will be more accurate and reach the target value faster.

Preferably, the feedforward computing unit 14, the feedback computing unit 16, and the optimization unit 18 are loaded into the computer system in the form of a program software, and the software is executed by the computer for control purposes. .

Wherein, a predictive transfer function of the control system 1 of the present invention is G , which can be expressed as a relationship between the control output Y of the control system 1 and the control input U. The predicted transfer function G is related to the configuration of the controlled object. For example, if used under temperature control, the predicted transfer function G may be a transfer function of a tube with a controlled substance and a transfer of a heating piece. Function related. The configuration of the controlled object takes into account that the predicted transfer function is G , and a plurality of related parameters M, C, and K (for example, the reciprocal of the system parameters) of the control system 1 can be obtained through arithmetic operations. Wherein, the control input U can be expressed as: Where u is the control input of the system, y is the output signal, and M, C, and K are system parameters related to the configuration of the controlled object, and can be operated by a plurality of sets of input signals u and output signals y via a least squares method Find out.

It is worth noting that the control input u of the system can be regarded as the control of the controlled object by the control system 1, in other words, the control input u of the system can be regarded as the controller output u.

In a preferred embodiment, the feedforward algorithm 15 performed by the feedforward operation unit 14 conforms to the following equation: Where u _ff is the feedforward control law 15, y _d is the input signal.

The feedback algorithm 17 executed by the feedback arithmetic unit 16 is preferably related to at least one of proportional control, integral control, and differential control. For example, the feedback algorithm 17 can be a separate proportional control, integral control, or differential control, or a combination of any of the three controls, or a combination of the three controls. This feedback algorithm 17 is dependent on the application of the control system 1 of the present invention. Therefore, the feedback algorithm 17 may have the following conditions.

In the case of the feedback algorithm 17 system proportional control, the feedback algorithm 17 can be expressed as: u _fb = k _p e ; where u _fb is the feedback control law 17, e is the error signal, k _p is the proportional control gain.

In the case where the feedback algorithm is 17-integral control, the feedback algorithm 17 can be expressed as:

Where k _i is the integral control gain.

In the case of the feedback algorithm 17 series differential control, the feedback algorithm 17 can be expressed as:

Where k _d is the differential control gain.

In the case where the feedback algorithm 17 must have both proportional control, integral control, and differential control, the feedback algorithm 17 is a combination of three types of control, that is, the feedback algorithm 17 can be expressed as:

Similarly, when the feedback control law 17 has two kinds of controls, it can also be regarded as a combination of the two types of control. In order to clarify the description of the present invention, the case where the feedback control algorithm 17 includes proportional control, integral control, and differential control will be described later.

The operation combining unit 20 is an operation combining program, and the controller output u generated by the controller is the result of the feed signal yd passing through the feedforward algorithm 15 executed by the feedforward operation unit 14 and the error signal e. The results after the feedback algorithm 17 executed by the feedback arithmetic unit 16 are combined and applied to the controlled body for control. The controller output u generated by the operation combining unit 20 can be expressed as: u = u _ff + u _fb .

When the controlled body receives the control of the controller output u, the actual output signal y' generated by the output unit 22 will be transmitted back to the error calculating unit 12, and replaces the output signal previously executed by the control system 1. y _old and the subtraction operation is performed again with the input signal yd, and the error signal e _new generated after the subtraction operation replaces the original error signal e and is transmitted to the optimization unit 18 to adjust the feedforward algorithm 15 and The feedback algorithm 17 is also transmitted to the feedback arithmetic unit 16 for a new feedback operation.

It is to be noted that the optimization unit 18 continually optimizes and adjusts the algorithms 15 and 17 executed by the feedforward operation unit 14 and the feedback operation unit 16 according to the change of the error signal e. Among them, the optimized feedforward algorithm 15 and the feedback algorithm 17 will satisfy the Lyapunov stability.

The plurality of operational parameters of the feedforward control rule 15 adjusted by the optimization unit 18 are in accordance with the following formula: Where α _k , α _c , α _M , β _K , β _C and β _M are adaptive gain parameters which must be positive, and R is a positive definite matrix representation of the error signal e.

The plurality of operational parameters of the feedback control rule 17 adjusted by the optimization unit 18 conform to the following formula: Where α _i , α _p , α _d , β _i , β _p and β _d are adaptive gain parameters which must be positive, x _{1 is} the integral of the error signal e with respect to time, and x _{2 is} the error signal e, x _{3 is} the differentiation of the error signal e from time.

Wherein, the adaptive gain parameters combine the controller output u and the control input U into a state space form (matrix form), and then substitute it into an error reference model to obtain an adaptive error differential. The equation is then substituted into the Lyapunov criterion to ensure that the error generated by the system can be converged to zero, that is, the output signal y' can follow the set input signal yd. Since the derivation process of the above adaptive gain parameters is a mathematical operation that can be understood by those skilled in the art, the derivation process will not be described in detail herein.

The control system 1 will continually repeat the above-described input unit 10, the error calculation unit 12, the feedforward operation unit 14, the feedback operation unit 16, the optimization unit 18, the operation combining unit 20, and the output unit 22. It operates until the value of the error signal e generated by the error calculating unit 12 is zero. Since the input signal yd will be equivalent to the output signal y when the error value is 0, that is, the actual output of the controlled object is equal to the target value input by the user. Thereby, the present invention can make the system continuously adjust the operation of the feedforward operation unit 14 and the feedback operation unit 16 to change the control input u of the system (ie, the controller output u), so that the controlled object can be faster. The ground reaches the target value.

2 is a system execution flow chart of the first embodiment of the present invention, which is used as an example for the control system of the present invention for temperature control, but it is noted that the present invention is not limited to temperature control, and the present invention is actually It can be applied to all types of controls. First, step S21 is executed. The input unit 12 receives the input signal yd input by the user, wherein the input signal yd represents a target temperature value that the user desires the controlled object to reach. Then, step S22 is executed, and the error calculating unit 12 compares the input signal yd representing the target temperature value with the output signal y _old representing the previous execution result of the system, and generates the error signal e. Thereafter, step S23 is executed, and the optimization unit 18 adjusts the feedforward algorithm 15 performed by the feedforward operation unit 14 and the feedback algorithm 17 performed by the feedback operation unit 16 based on the error value. Then, step S24 is executed. The feedforward operation unit 14 performs a feedforward operation on the input signal yd according to the optimized feedforward algorithm 15 and transmits the operation result to the operation combining unit 20. At the same time, step S25 is executed, and the feedback operation unit 16 performs a feedback operation on the error signal e according to the optimized feedback control rule 17, and transmits the operation result to the operation combining unit 20. Thereafter, step S26 is executed, and the operation combining unit 20 combines the operation result of the feedforward operation and the operation result of the feedback operation to generate the controller output u. Thereafter, step S27 is executed, and the control system 1 performs temperature control on the controlled body according to the controller output u. Thereafter, step S28 is executed, and the output unit 22 returns the output signal y representing the actual temperature value controlled by the controlled body to the error calculating unit 12. Since the optimization unit 18 optimizes the feedforward operation and the feedback operation of the system according to the Lyapunov stability, and repeats the steps S22 to S28, the error signal e will gradually approach 0, so that the actual The temperature value can be the same as the target temperature value.

Figures 3(A) and 3(B) are diagrams showing the results of a conventional PID control system under temperature control. Among them, the horizontal axis system performs the time, and the vertical axis system outputs the result. As can be seen from FIG. 3(A), when the target temperature is 100 degrees, the conventional PID control system must make the controlled object reach the target temperature after 1500 seconds and tend to be stable. As can be seen from Fig. 3(B), when the target PID temperature is 120 degrees, the control system cannot achieve the target temperature even if it is executed for a long time.

3(C) and 3(D) are diagrams showing the results of the control system 1 with intelligent adjustment according to the present invention under temperature control. As can be seen from Fig. 3(C), the control system 1 of the present invention can bring the controlled object to the target temperature after the time is about 1500 seconds when the target temperature is 100 degrees. As can be seen from Fig. 3(D), the control system 1 of the present invention can bring the controlled object to the target temperature when the target temperature is 120 degrees and only takes about 2000 seconds.

Referring again to FIGS. 3(A) to 3(D), whether the conventional PID control system or the control system 1 with intelligent adjustment of the present invention, the output values are still in an unstable state after reaching the target temperature. These unstable signals are often caused by the delay of the control system caused by the influence of the control environment variables. Therefore, if the output signal needs to be stabilized, the problem of system delay must be dealt with.

4 is a schematic diagram of a system architecture of a second embodiment of the intelligent control system 1 of the present invention. Similar to the first embodiment, the second embodiment of the present invention also includes an input unit 100 and an error. The calculation unit 120, a feedforward operation unit 140, a feedback operation unit 160, an optimization unit 180, an operation combination unit 200, and an output unit 220. In addition, the second implementation of the control system 1 further includes a compensation unit 240 and a second operation combining unit 260.

In a preferred embodiment, the various units described above are comprised of algorithms and are executed by a device having a microprocessor.

Similarly, the input unit 100 is coupled to the error calculation unit 120 and the feedforward operation unit 140. The error calculation unit 120 is coupled to the feedback control operation unit 160. The feedforward operation unit 140 continues with the feedback operation. The unit 160 is coupled to the calculation combining unit 200. The error calculating unit 120 is also coupled to the optimization unit 180. The optimization unit 180 is continuously coupled to the feedforward computing unit 140 and the feedback computing unit 160. Different from the first embodiment, the operation combining unit 200 is connected to the compensation unit 240 in addition to the output unit 220 via the controlled object. In addition, the second operation combining unit 260 is coupled to the compensation unit 240 and the output unit 220 and coupled to the error calculating unit 120.

The adaptive control performed by the input unit 100, the feedforward operation unit 140, the feedback operation unit 160, and the optimization unit 180 is the same as that of the first embodiment, and therefore will not be described in detail herein.

The error calculation unit 120 compares an input signal yd (target value) with a feedback signal ym _old to generate an error signal e. The feedback signal ym _old is a combination of an output signal y _old generated by the previous execution of the system and one or more signals generated by the compensation unit 240.

The compensation unit 240 is used to solve the problem of system delay. When the compensation unit 240 obtains the controller output u from the operation combining unit 200, the compensation unit 240 performs an operation on the controller output u, and performs an operation. The result is transmitted to the second operation combining unit 260. In one embodiment, the compensation unit 240 of the system using a particular transfer function G _m and a delay parameter e ^-Ts performs operation on the controller output u. Preferably, the compensation unit 240 is a Smith estimator. Wherein the transfer function G _m special function using the least squares method based achieved, which is an optimum system-based measurements by a plurality of sets of the identified transfer function.

The second operation combining unit 260 combines the output signal y of the controlled object from the output unit 220 with the operation result from the compensation unit 240, and transmits the combined feedback signal ym to the error calculation unit. 120.

The operation result of the compensation unit 240 can be expressed as: G _m e ^-Ts , where G _m can be regarded as an optimal system transfer function obtained by the least squares method.

It should be noted that in the second embodiment, an error signal e generated by the error calculation unit 120 is a difference between the input signal yd and the combined feedback signal ym. The combined signal ym is continuously transmitted back to the error calculation unit 120 for calculation. When the error signal e is 0, the delay of the system can be eliminated.

In still another preferred embodiment, the transfer function after the control system eliminates the system delay can be expressed as:

among them, The control system eliminates the transfer function after the system delay, G is the control system does not eliminate the predicted transfer function before the system delay, G _m is the optimal system transfer function obtained by the least squares method, and e ^-Ts is the delay The parameter, T is the delay time of the system, and s is the Laplacian operator or the differential operator.

5 is a system execution flow chart of a second embodiment of the present invention, which is used as an example for controlling the temperature control system of the present invention, but it is noted that the present invention is not limited to temperature control, and the present invention is practical. It can be applied to all types of controls. First, step S51 is executed, and the input unit 100 receives the input signal yd representing the target temperature value. Then, step S52 is executed, and the error calculation unit 120 compares the input signal yd representing the target temperature value with the feedback signal ym _old generated by the previous execution, and generates an error signal e. Thereafter, step S53 is executed, and the optimization unit 180 adjusts the feedforward algorithm 15 performed by the feedforward operation unit 140 and the feedback algorithm 17 performed by the feedback operation unit 160 according to the error signal e. Then, the step S54 is executed, and the feedforward operation unit 140 performs a feedforward operation on the input signal yd according to the optimized feedforward algorithm 15 and transmits the operation result to the operation combining unit 200. At the same time, step S55 is executed, and the feedback operation unit 160 performs a feedback operation on the error signal e according to the optimized feedback control rule 17, and transmits the operation result to the operation combining unit 200. Thereafter, step S56 is executed, and the operation combining unit 200 combines the operation result of the feedforward operation and the operation result of the feedback operation to generate the controller output u. Thereafter, step S57 is executed, and the control system 1 performs temperature control on the controlled body according to the controller output u, and generates the output signal y. At the same time, step S58 is executed, the compensation unit 240 obtains the controller output u, and performs an operation on the controller output u. Then, the step S59 is executed, and the second operation combining unit 260 combines the output signal y and the operation result of the compensation unit 240 to generate a new feedback signal ym, and returns the error signal to the error calculation unit 120 to generate a new one. the error signal e _new. Thereby, the delay of the system will be gradually eliminated under the continuous operation of the compensation unit 240.

6(A) and 6(B) are diagrams showing the results of the second embodiment of the control system 1 with intelligent adjustment according to the present invention under temperature control. Please refer to FIGS. 3(C) and 3(D) together. 6(A) and 6(B), when the second embodiment of the control system 1 of the present invention is operated by the compensation unit 240, the target temperature is 100 degrees or 120 degrees, and the state is unstable. Can be eliminated. It can be seen that the control system 1 of the present invention continuously processes and processes the feedback signal ym, so that unstable system delay factors can be quickly eliminated.

Accordingly, the present invention provides a control system capable of automatically adjusting feedforward control and feedback control. By optimizing the unit to continuously adjust the feedforward control and the feedback control according to the error signal, the control effect can be more accurate, and the overall Control program execution can be faster and faster. In addition, the present invention also adds a compensation unit that removes the system delay time in the control system, so that the control system control does not cause an unstable phenomenon after reaching the target value.

The above-mentioned embodiments are merely examples for convenience of description, and the scope of the claims is intended to be limited to the above embodiments.

1‧‧‧Control system

10, 100‧‧‧ input unit

12, 120‧‧‧ error calculation unit

14, 140‧‧‧ feedforward computing unit

15‧‧‧Feed-for-control law

16, 160‧‧‧Return arithmetic unit

17‧‧‧Reward control law

18, 180‧‧‧Optimization unit

20, 200‧‧‧ computing combination unit

22, 220‧‧‧ Output unit

Claims (10)

A control system with intelligent adjustment includes: an input unit for obtaining an input signal input by a user; an error calculation unit for calculating the input signal and an output signal executed by the system before, and generating a An error feed signal; a feedforward operation unit that performs a feedforward control rule on the input signal; a feedback operation unit that performs a feedback control law related to the error signal on the input signal; and an optimization unit for adjusting The feedforward control rule and the feedback control rule; and an operation combining unit, generating a controller output according to the operation result of the feedforward operation unit and the feedback operation unit, and transmitting the controller output to a controlled The body is configured to generate an output signal that is executed by the system at a time; wherein the optimization unit adjusts the feedforward control law and the feedback control rule according to the error signal. The intelligent adjustment control system described in claim 1, wherein the optimization adjustment performed by the optimization unit is based on a Lyapunov function. For example, the intelligent adjustment control system described in claim 2, wherein the feedforward control law conforms to the following formula: Where u _ff is the feedforward control law, y _d is the input signal, and M, C and K are the reciprocals of the system parameters related to the configuration of the controlled object. For example, the control system with intelligent adjustment described in claim 3, wherein the plurality of operational parameters of the optimized feedforward control law are in accordance with the following formula: Where α _K , α _C , α _M , β _K , β _c and β _M are adaptive gain parameters which must be positive, and R is the matrix form of the error signal. For example, the control system with intelligent adjustment described in claim 2, wherein the feedback control law has at least one of proportional control, integral control and differential control. For example, the intelligent adjustment control system described in claim 2, wherein the feedback control law conforms to the following formula: Where u _fb is the feedback control law, e is the error signal, k _p is the proportional control gain, k _i is the integral control gain, and k _d is the differential control gain. For example, in the control system with intelligent adjustment described in claim 6, wherein the plurality of operational parameters of the feedback control rule adjusted by the optimization unit conform to the following formula: Where α _i , α _p , α _d , β _i , β _p and β _d are adaptive gain parameters which must be positive, x _{1 is} the integral of the error signal e with respect to time, and x _{2 is} the error signal e, x _{3 is} the differentiation of the error signal with respect to time, and R is a matrix form of the error signal. The intelligent adjustment control system described in claim 1 further includes a compensation unit having a compensation parameter and a delay term for calculating the controller output to eliminate the delay of the system. The control system with intelligent adjustment as described in claim 8 further includes a second operation combining unit, and the result of the control output passing through the controlled body is combined with the operation result of the control output through the compensation unit. And passed back to the error calculation unit. The control system with intelligent adjustment according to claim 9 is characterized in that the transfer function after the control system eliminates the system delay is: among them, The control system eliminates the transfer function after the system delay, the G system control system does not eliminate the transfer function before the system delay, G _m is the optimal system transfer function obtained by the least squares method, e ^-Ts is the delay term, s For the Laplacian operator or the differential operator, T is the delay time of the system, and M, C, and K are the reciprocals of the system parameters related to the configuration of the controlled object.