Self-decrement system incremental PID parameter single-phase relay feedback self-tuning method

Abstract

The application provides a self-decrement system incremental PID parameter single-phase relay feedback self-tuning method, which is different from the traditional relay feedback self-tuning method, and a new solution is provided for the incremental PID control parameter self-tuning of the self-decrement electric drive control system which can only be controlled in one direction in the mobile bearing platform, so that the design efficiency of the control parameter and the accuracy and accuracy of the control are greatly improved. The application comprises the following contents: the system enters the single-phase relay feedback self-tuning method, and the controller is switched to the single-phase relay feedback controller; the single-phase relay feedback controller controls the system to continuously oscillate in a preset interval according to the measured value; the register records the waveform data after the system generates a usable waveform; the solver calculates the optimal control amount according to the register waveform result; and finally, the calculated optimal control amount is input into the incremental PID controller to verify whether the result meets the requirements.

Description

Technical Field

[0001] This invention relates to the field of drive control technology, and in particular to a self-tuning method for incremental PID parameters of a self-fading system using single-sequence electrical feedback. Background Technology

[0002] Mobile platforms contain numerous different electric drive control systems. Adjusting the control parameters of these many systems requires technicians with extensive theoretical knowledge and a thorough understanding of the tuning process. This is undoubtedly a massive and nearly impossible task to complete accurately. Due to the diverse operating environments of mobile platforms, such as driving on surfaces with varying friction coefficients, braking at different ambient temperatures, and loading different targets, a single control parameter cannot adapt to such complex and variable conditions. Therefore, designing an adaptive tuning method for control parameters that can adapt to multiple drive control systems is of great significance.

[0003] A unidirectional self-fading system refers to a system that can only receive a positive control input during the control process, and whose state decays automatically when no control input is received. Traditional relay feedback methods are generally used for ordinary systems capable of both forward and reverse control. However, for unidirectional self-fading systems, traditional relay feedback methods are almost ineffective in obtaining correct solutions. Mobile load-bearing platforms differ from traditional relay feedback methods. Mobile load-bearing platforms can only employ unidirectional self-fading electric drive control systems. In the longitudinal control of mobile load-bearing platforms, throttle acceleration and braking deceleration are independently controlled, both being unidirectional self-fading electric drive control systems. The throttle can only accelerate; during the tuning process, deceleration relies on the self-fading of driving resistance, causing system oscillations. During braking tuning, a fixed speed is given; deceleration is controlled by braking, and acceleration relies on a fixed speed, causing system oscillations. Summary of the Invention

[0004] This invention proposes a solution for improving the design efficiency of control parameters and enhancing the precision and accuracy of control in the incremental PID control parameter self-tuning of a self-fading electric drive control system in a mobile platform that can only be controlled in one direction.

[0005] This invention provides a method for self-tuning incremental PID parameters of a self-fading system using single-sequence electrical feedback, the method comprising the following steps:

[0006] Step 1: Convert the controller to a single-sequence electrical feedback controller and initialize the system parameters;

[0007] Step 2: The controller controls the system to oscillate continuously within a preset range based on the feedback measurement value, and controls the relay to switch on and off by comparing the measurement value with the upper and lower limits of oscillation to make the system oscillate continuously;

[0008] Step 3: Convert the oscillation waveform collected by the system into a symmetrical relay characteristic oscillation;

[0009] Step 4: After the data acquisition unit obtains usable waveform data, the controller disconnects to stop the system. The solver then calculates the ideal K based on the waveform data. p K i K d value.

[0010] Furthermore, in step 1, the system parameters include an upper limit for oscillation, a lower limit for oscillation, a sampling period, and a maximum value for the control quantity.

[0011] Furthermore, in step 2, the process of causing the system to oscillate continuously also includes the following steps:

[0012] Step 21: When the system state quantity is less than the maximum value of the preset interval, the input value x of the single-phase relay feedback controller is the difference between the preset upper limit and the measured value. According to the characteristics of the single-phase relay, the control quantity y output by the controller is H. The self-attenuating system receives positive excitation, and the system state quantity increases.

[0013] Step 22: When the system state quantity is greater than the maximum value of the preset interval, the input value x of the single-phase relay feedback controller is the difference between the preset lower limit and the measured value. According to the characteristics of the single-phase relay, the control quantity y output by the controller is 0, and the self-attenuation system attenuates according to its own self-attenuation rate.

[0014] Step 23: When the system state variable is lower than the minimum value of the preset interval, repeat steps 21 and 22. After the system generates stable oscillations, the data acquisition device collects the time t1 required for the system's rising edge, the time t2 required for the falling edge, and the actual maximum oscillation value H of the system. max The actual minimum oscillation value H of the system min .

[0015] Furthermore, in step 3, the rising edge data of the oscillation waveform is obtained as the solution, and a ΔH correction amplitude is added to eliminate the influence of the self-fading effect on the control quantity calculation. The falling edge is the simulated reverse relay control data after eliminating the self-fading effect, and the converted oscillation period is 2t1; the correction amplitude is:

[0016]

[0017] t1 is the time required for the rising edge, t2 is the time required for the falling edge, and H max H represents the actual maximum oscillation value of the system. min This represents the actual minimum oscillation value of the system.

[0018] Furthermore, in step 4, the output signal is subjected to Fourier series expansion for harmonic analysis:

[0019]

[0020] a0 represents the constant component in the Fourier coefficients, a n b represents the amplitude of the nth harmonic cosine component in the Fourier coefficients. n ω0 represents the amplitude of the nth harmonic sinusoidal component in the Fourier coefficients, t represents time, and n represents the index of the Fourier series term.

[0021] When a sinusoidal input signal is defined, the ratio of the first harmonic component to the complex number of the input signal in the steady-state output of the nonlinear element is the describing function of the nonlinear element, denoted by N(x):

[0022]

[0023] x represents the input value, a1 represents the first cosine component of the Fourier series, and b1 represents the first sine component of the Fourier series.

[0024] Furthermore, in step 4, the controller relay characteristics in the standard relay feedback self-tuning method are as follows:

[0025]

[0026] When the relay switches at a fixed frequency, the input signal can be considered as a sinusoidal signal:

[0027]

[0028] Where A is the amplitude of the output signal.

[0029] Furthermore, in step 4, in the frequency domain, when the frequency equals the crossover frequency, the system is in a critical state, and the theoretical value of the critical gain is:

[0030]

[0031] G p ω represents the system transfer function. c This indicates the critical oscillation frequency.

[0032] When the system is critically stable, the Nyquist stability criterion yields:

[0033] G p (jω c N(x) = -1

[0034] Therefore, the critical gain and critical period of the system are:

[0035]

[0036]

[0037] T u Indicates the critical period.

[0038] Based on the obtained critical gain and critical period of the system, the control quantity of the system controller can be obtained by the ZN method as follows:

[0039] K p =0.6K u

[0040]

[0041]

[0042] T represents the sampling period.

[0043] The beneficial effects achieved by this invention are:

[0044] The incremental PID parameter self-tuning method for self-fading systems provided by this invention enables self-tuning of PID parameters for self-fading systems, overcoming the limitation of the limited applicability of traditional relay feedback PID self-tuning methods. This allows for adaptive tuning of all controlled components in complex systems (such as mobile carrier platforms), especially self-fading systems that can only be controlled unidirectionally, greatly improving the efficiency of configuration and debugging of complex systems, and enhancing the design efficiency and control accuracy of control system parameters. Attached Figure Description

[0045] Figure 1 This is a flowchart of the tuning process of the single-sequence feedback self-tuning method of the present invention.

[0046] Figure 2 This is a schematic diagram of the system controller switching for the single-sequence electrical feedback self-tuning method of the present invention.

[0047] Figure 3 This is a schematic diagram of the single-sequence electrical feedback control in the single-sequence electrical feedback self-tuning method of the present invention.

[0048] Figure 4 This is a waveform transformation diagram of the single-sequence electrical feedback self-tuning method of the present invention.

[0049] Figure 5 This diagram illustrates the conversion of the single-sequence electrical feedback result of the self-degrading system into the standard relay feedback result in the single-sequence electrical feedback self-tuning method of the present invention. Detailed Implementation

[0050] The technical solution of the present invention will be described in more detail below with reference to the accompanying drawings. The present invention includes, but is not limited to, the following embodiments.

[0051] As attached Figure 1As shown, this invention provides a self-tuning method for incremental PID parameters in a self-fading system using single-sequence electrical feedback, comprising the following steps:

[0052] Step 1: The system controller is converted into a single-sequence electrical feedback controller, and the system parameter definitions are initialized;

[0053] System parameters include the upper limit of oscillation, the lower limit of oscillation, the sampling period, and the maximum value of the control quantity.

[0054] Since the self-tuning of control parameters for mobile platform engineering needs to be carried out within a specific site area, considering the size of the site and the safety of the tuning process, the upper and lower limits of oscillation cannot exceed the electronic fence range defined by the mobile platform. This solution controls the system to oscillate within a safe range by setting upper and lower limits for oscillation. The oscillation range is selected as a safe area extending 80% outward from the center of the electronic fence range, improving upon the safety issues caused by the inability to estimate the oscillation amplitude in traditional relay feedback methods.

[0055] Step 2: The controller controls the system to oscillate continuously within a preset range based on the measured values ​​fed back by the sensor, and controls the relay to switch on and off by comparing the measured values ​​with the upper and lower limits of oscillation to make the system oscillate continuously.

[0056] For standard systems in mobile carrier platforms where the control input can be positive or negative and there is no significant self-attenuation trend, the adaptive tuning process can be directly calculated using the steps described in step 4.

[0057] As attached Figure 2-3 As shown, for a self-attenuation system in a mobile carrier platform that can only receive unidirectional input, the self-attenuation control system requires that the control input be positive, and the system state self-attenuates when the system control input is 0. This manifests as a throttle system on the mobile carrier platform.

[0058] Since the system control input can only be positive at this time, it exhibits the following single-sequence electrical characteristics:

[0059]

[0060] x represents the relay input, y represents the relay output, and H represents the system control input.

[0061] As attached Figure 4 As shown, unlike the characteristics of a standard relay process, its describing function is also altered, making it impossible to calculate the critical gain and critical period of the system using the derivation of the standard process. In such systems, the relay output is 0 when x < 0, the system has no control input and exhibits self-decay. Due to the relatively slow self-decay speed, the rise and fall times differ within one oscillation cycle, making it impossible to convert the system into a single-harmonic system when performing harmonic analysis.

[0062] The self-tuning method provided by this invention includes a data acquisition unit and a solver; the data acquisition unit analyzes the system waveform data, records the waveform data when the controller is input, that is, the time length of the rising part of the system, and symmetrically fills in the missing half-cycle length at the end of the oscillation to obtain an approximate standard relay feedback characteristic waveform curve.

[0063] The solver calculates the control parameters based on the converted waveform data to obtain the optimal positional PID control parameters.

[0064] The control process for continuous oscillation includes the following steps:

[0065] Step 21: When the system state quantity is less than the maximum value of the preset interval, the input value x of the single-phase relay feedback controller is the difference between the preset upper limit and the measured value. According to the characteristics of the single-phase relay, the control quantity y output by the controller is H. The self-attenuating system receives positive excitation, and the system state quantity increases.

[0066] Step 22: When the system state quantity is greater than the maximum value of the preset interval, the input value x of the single-phase relay feedback controller is the difference between the preset lower limit and the measured value. According to the characteristics of the single-phase relay, the control quantity y output by the controller is 0, and the self-attenuation system attenuates according to its own self-attenuation rate.

[0067] Step 23: When the system state variable is lower than the minimum value of the preset interval, repeat steps 21 and 22. After the system generates stable oscillations, the data acquisition device collects the time t1 required for the system's rising edge, the time t2 required for the falling edge, and the actual maximum oscillation value H of the system. max The actual minimum oscillation value H of the system min .

[0068] Because the self-attenuation system has a significant self-attenuation effect, the actual results collected by the data acquisition unit are non-standard relay feedback control results, which are not conducive to the calculation by the solver. Therefore, the data needs to be processed and converted into standard relay feedback control result waveform data.

[0069] Step 3: Convert the oscillation waveform collected by the system into a symmetrical relay characteristic oscillation;

[0070] like Figure 5 As shown, the oscillation waveform acquired by the system is the waveform under asymmetric relay characteristic control, which is not conducive to solving PID control parameters. Since the control quantity in actual PID control is mainly affected by the rising edge, this invention mainly uses the rising edge data for calculation, and adds ΔH correction amplitude to eliminate the influence of self-fading effect on the calculation of control quantity. The falling edge is the simulated reverse relay control data after eliminating the self-fading effect. The converted oscillation period is 2t1. Wherein:

[0071]

[0072] After converting the asymmetric relay characteristic oscillation into a symmetric relay characteristic oscillation, the PID control parameter calculation stage begins.

[0073] Step 4: After the data acquisition unit obtains usable waveform data, the controller disconnects to stop the system. The solver then calculates the ideal K based on the waveform data. p K i K d Value; where the available waveform is a periodic signal that the system has continuously generated at least two complete cycles under relay control.

[0074] The input-output description of the adaptive tuning stage is as follows:

[0075] y = f(x)

[0076] Perform harmonic analysis by performing Fourier series expansion on the output signal:

[0077]

[0078] a0 represents the constant component in the Fourier coefficients, a n b represents the amplitude of the nth harmonic cosine component in the Fourier coefficients. n ω0 represents the amplitude of the nth harmonic sinusoidal component in the Fourier coefficients, t represents time, and n represents the index of the Fourier series term.

[0079] Among them, constant components:

[0080]

[0081] T0 represents the period;

[0082] Cosine component amplitude:

[0083]

[0084] Sine component amplitude:

[0085]

[0086] The nth harmonic component is:

[0087]

[0088] in,

[0089] If the constant component is equal to 0 and n>1, then Y n If both are very small, then the sinusoidal response of the nonlinear element can be approximated as having only a first harmonic component:

[0090]

[0091] Where x represents the input value, a1 represents the first cosine component of the Fourier series, and b1 represents the first sine component of the Fourier series.

[0092] As can be seen from the above derivation, when a sinusoidal input signal is defined, the ratio of the first harmonic component to the complex number of the input signal in the steady-state output of the nonlinear element is the describing function of the nonlinear element, denoted by N(a):

[0093]

[0094] Where x represents the input value.

[0095] The controller relay characteristics in the standard relay feedback self-tuning method are as follows:

[0096]

[0097] When the relay switches at a fixed frequency, the input signal can be considered as a sinusoidal signal:

[0098]

[0099]

[0100]

[0101]

[0102] Substituting into the describing function, we get:

[0103]

[0104] Where A is the amplitude of the output signal.

[0105] In the frequency domain, the system is in a critical state when the frequency equals the crossover frequency. This is because the system's step response curve oscillates with constant amplitude during adaptive tuning, and the relay's describing function coincides with the negative real part of the real axis. Therefore, the critical frequency equals the crossover frequency, meaning the frequency at the intersection of the Nyquist curve of the controlled object and the negative reciprocal of the describing function coincides with the crossover frequency. Thus, the theoretical value of the critical gain is:

[0106]

[0107] G p ω represents the system transfer function. c This indicates the critical oscillation frequency.

[0108] When the system is critically stable, the Nyquist stability criterion yields:

[0109] G p (jω cN(a)=-1

[0110] Therefore, the critical gain and critical period of the system are:

[0111]

[0112]

[0113] T u Indicates the critical period.

[0114] Based on the obtained critical gain and critical period of the system, the control quantity of the system controller can be obtained by the ZN method as follows:

[0115] K p =0.6K u

[0116]

[0117]

[0118] T represents the sampling period.

[0119] Finally, the tuning result K p K i K d The input positional PID controller was used to verify whether the tuning results could accurately control the system under different operating conditions.

[0120] This invention is not limited to the specific embodiments described above. Those skilled in the art can implement this invention using various other specific embodiments based on the disclosed content of the embodiments and accompanying drawings. Therefore, any design that adopts the design structure and concept of this invention and makes some simple changes or modifications falls within the protection scope of this invention.

Claims

1. A self-damping system incremental PID parameter single-phase relay feedback self-tuning method, characterized in that, The self-damping system incremental PID parameter single-phase relay feedback self-tuning method comprises the following steps: Step 1, the controller is converted into a single-phase relay feedback controller, and system parameters are initialized; Step 2, the controller controls the system to continuously oscillate in a preset interval according to the feedback measurement value, and controls the on-off of the relay by comparing the measurement value with the upper and lower limit values of the oscillation to make the system continuously oscillate; Step 3, the oscillation waveform collected by the system is converted into a symmetrical relay characteristic oscillation; Step 4, after the collector gets the available waveform data, the controller disconnects to stop the system, and the solver calculates the ideal value according to the waveform data ; In step 3, the rising edge data of the oscillation waveform is obtained as a solution, and is added The amplitude is corrected to eliminate the influence of the self-attenuation effect on the control quantity calculation. The falling edge is the simulated inverse relay control data after eliminating the self-attenuation effect. The converted oscillation period is 2 ; and the corrected amplitude is: ； time required for the rising edge, time required for the falling edge, actual maximum oscillation value of the system, actual minimum oscillation value of the system.

2. The self-adjusting method for incremental PID parameters of a self-fading system with single-passive electrical feedback according to claim 1, characterized in that, In step 1, the system parameters include the upper limit value of the oscillation, the lower limit value of the oscillation, the sampling period, and the maximum value of the control quantity.

3. The method of claim 1, wherein the PID parameters are incrementally updated based on the error signal and the derivative signal. In step 2, the system continuously oscillates, which further comprises the following steps: Step 21, when the state quantity of the system is less than the maximum value of the preset interval, the input value x of the single-phase relay feedback controller is the difference between the preset upper limit and the measurement value, according to the single-phase relay characteristic, the control quantity y output by the controller is H, the self-damping system receives positive excitation, and the state quantity of the system rises; Step 22, when the state quantity of the system is greater than the maximum value of the preset interval, the input value x of the single-phase relay feedback controller is the difference between the preset lower limit and the measurement value, according to the single-phase relay characteristic, the control quantity y output by the controller is 0, and the self-damping system attenuates according to its own self-attenuation rate; Step 23, when the system state quantity is lower than the preset interval minimum value, repeat steps 21 and 22, and the collector collects the time required for the system to generate stable oscillation after the rising edge of the system , the time required for the falling edge , the actual maximum oscillation value of the system , the actual minimum oscillation value of the system .

4. The self-adjusting method for incremental PID parameters of a self-fading system with single-passive electrical feedback according to claim 1, characterized in that, In step 4, the output signal is subjected to Fourier series expansion for harmonic analysis: ； denotes the constant component in the Fourier coefficients, denotes the amplitude of the n-th harmonic cosine component in the Fourier coefficients, denotes the amplitude of the n-th harmonic sine component in the Fourier coefficients, denotes the fundamental frequency, denotes the time, denotes the order of the Fourier series term, ​ When defining the sinusoidal input signal, the complex ratio of the first harmonic component in the steady-state output of the non-linear element to the input signal is the describing function of the non-linear element, denoted by ​ ； denotes an input value, denotes the first cosine component of the Fourier series, denotes the first sine component of the Fourier series.

5. The self-adjusting method for incremental PID parameters of a self-fading system with single-passive electrical feedback according to claim 4, characterized in that, In step 4, the relay characteristic of the controller in the standard relay feedback self-tuning method is: ； When the relay is converted at a fixed frequency, the input signal can be regarded as a sinusoidal signal: ； Wherein, A is the amplitude of the output signal.

6. The self-adjusting method for incremental PID parameters of a self-fading system with single-passive electrical feedback according to claim 5, characterized in that, In step 4, in the frequency domain, when the frequency is equal to the crossover frequency, the system is in a critical state, and the theoretical value of the critical gain is: ； represents a system transfer function, represents a critical oscillation frequency; When the system is in a critical stable state, according to the Nyquist stability criterion: ； Therefore, the critical gain and the critical period of the system are: ； ； denotes the critical period; According to the critical gain and the critical period of the system obtained, the control quantity of the system controller can be obtained by the Z-N method: ； ； ； T represents the sampling period.

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