CN106059413A - Flywheel system rotation speed control method driven by direct current motor - Google Patents

Abstract

The present invention provides a flywheel system rotation speed control method driven by a direct current motor. A given target rotation speed and a real rotation speed are used for calculating error amount, and then a sliding modal variable is calculated; the sliding modal variable is modulated by a low pass filter to obtain equivalent control signals which are taken as input, and a dual-layer self-adaptive algorithm is designed for performing control gain online regulation; and the sliding modal variable and the control gain are inputted into the designed supercoiling control algorithm to obtain the control voltage. Because the closed loop system controlled by the method provided by the invention can be stably regulated to a target rotation speed in a limited time so as to have good robustness and control precision. An effective means is provided for the engineering of the high-precision rotation speed control of a flywheel system.

Description

A kind of fly wheel system method for controlling number of revolution of DC motor Driver

Technical field

The present invention relates to automatic control technology field, be specifically related to the fly wheel system rotating speed control of a kind of DC motor Driver Method processed.

Background technology

Fly wheel system is the active control system being used widely.Modern spacecraft to the precision of attitude control system, Life and reliability requires more and more higher, generally uses the three-axis stabilization system of fly wheel system composition to meet its performance requirement. Fly wheel system does not consume working medium, only needs consuming electric power；Can produce more accurate control moment, control accuracy relatively thruster exceeds one The individual order of magnitude；Be suitable to absorb the impact of PERIODIC INTERFERENCE.Therefore, the spacecraft of long-term work on middle and high track at present, be all It is mounted with the three axis stabilized spacecraft of fly wheel system.

The operation principle of fly wheel system is exactly that the time is led by the aggregated momentum moment vector of " moment of momentum theorem ", i.e. spacecraft Number, equal to acting on spaceborne moment of face vector sum.By changing the high-speed rotary part of fly wheel system on spacecraft The angular momentum vector of (i.e. rotor), thus produce the control moment being directly proportional to rotor angular momentum rate of change, act on spacecraft On pedestal so that it is the moment of momentum changes accordingly, this process is referred to as moment of momentum exchange.

According to construction features and working method, fly wheel system can be divided into: flying wheel, control-moment gyro and framework momentum Wheel three types.If the supporting of fly wheel system is connected with spacecraft, the rotary shaft of flywheel rotor is constant relative to spacecraft pedestal, But the rotating speed of rotor can change, such flywheel is known as " flying wheel ".Rotate if rotor remains a constant speed and be installed in On framework, and framework can rotate relative to spacecraft pedestal, and the most this flywheel is called " control-moment gyro ".If controlled On the basis of moment gyro, make the rotating speed of rotor to change, just obtained " framework momenttum wheel ".

From operation principle and the working method of fly wheel system it can be seen that the rotating speed of rotor is the pass realizing moment of momentum exchange Key physical quantity.Rotor is high speed rotating under the driving of motor, according to the difference of working method, keeps constant rotational speed or follows the tracks of change Rotating speed of target.Accordingly, it would be desirable to the rotating speed of rotor is control effectively.At present, the control method of rotating speed mainly there is PID (ratio, integration and differential) controls and sliding formwork controls.PID controls by measuring speed error, through ratio in parallel, integration and micro- Produce motor driving moment after subchannel, act on and on rotor, realize rotating speed control.Control effect then to depend on whether have chosen Suitably " proportional gain, storage gain and the differential gain " three control parameters.PID controls to have that calculating is simple, be prone to engineering The advantage realized, is widely used.But from theory, PID controls effect to multipotency and reaches " Asymptotic Stability ", I.e. actual speed can only be infinitely close to rotating speed of target, but can not be equal to rotating speed of target.Especially, rotor is in real work , such as, between rotating shaft and support, there is friction in the impact of the moment that will necessarily be interfered in environment, or in space flight after rotor magnetization By electromagnetic force etc. in device electromagnetic environment.Now, PID control effect only can only achieve " uniform bound ", i.e. actual speed Can enter in the neighborhood comprising rotating speed of target, controlling error will exist always.To this end, part researcher begins attempt to use Rotor speed is controlled by sliding-mode control.Sliding formwork controls, by structure sliding variable, to force rotor motion state to enter Sliding formwork is dynamic, enters moving the impact of interference-free moment of sliding formwork dynamically rear rotor, can make reality in finite time Rotating speed is equal to rotating speed of target.But sliding formwork control law comprises first term function, after rotor motion entrance sliding formwork is dynamic, controls Device will produce discontinuous high frequency and buffet signal, not only bring the difficulty in Project Realization, also add the energy needed for control Consumption.

Summary of the invention

For solving above-mentioned technical problem, the invention provides the fly wheel system rotating speed controlling party of a kind of DC motor Driver Method.

The present invention provides the Control system architecture of method as it is shown in figure 1, it with the fly wheel system under DC motor Driver is Controlled device, controlling target is that the actual speed making fly wheel system rotary part is consistent with desired rotating speed of target.Devise one Planting superhelix control algolithm, the control voltage of generation is as the control input signal driving motor, it is achieved that uncertain to model Property and the robust control of external disturbance；For the buffeting that effectively suppression first term function causes, make in superhelix control algolithm simultaneously Control parameter realize Automatic adjusument, with low pass filter output equivalent control signals for input, with superhelix control calculate The control gain of method is output, devises two tier adaptive algorithm, is filtered the sampling of sliding mode variable by low pass filter Ripple, on-line tuning controls gain；Wherein, sliding mode variable calculates according to the margin of error, and the margin of error is that rotating speed of target turns with actual The difference of speed.The closed loop system controlled by the method stable regulation to rotating speed of target, can have good Shandong in finite time Rod and control accuracy.The Project Realization controlled for fly wheel system high accuracy rotating speed provides effective means.

The invention provides the fly wheel system method for controlling number of revolution of a kind of DC motor Driver, comprise the following steps:

Step S100: the actual speed obtained by rotating speed of target and measurement calculates rotating speed of target and the margin of error of actual speed E, then calculates sliding mode variable；

Step S200: obtain equivalent control signals, with equivalent control after being modulated by low-pass filtered for sliding mode variable device Signal for input, with control gain for output, by two tier adaptive algorithms selection auto-adaptive parameter, obtain control gain；Its In this step be referred to as two tier adaptive algorithm design, gained two tier adaptive algorithm flow is as shown in Figure 2.

Step S300: set up the fly wheel system rotating speed model of DC motor Driver, with the sliding die described in step S200 State variable is input, in conjunction with the control gain described in gained, designs superhelix control algolithm, adjusts and control parameter, obtain motor Control voltage；This step S300 is superhelix control algorithm design.

In actual application, the actual speed of flywheel rotor is measured by speed probe measurement, and the method will be had to be calculated Control voltage be input to drive motor, driven by motor flywheel rotor can realize rotating speed control.

Wherein, the margin of error between rotating speed of target and actual speed described in the step s 100, its computational methods are:

E=Ω_C-Ω (1)

Ω_CFor rotating speed of target, Ω is actual speed.

Wherein, sliding mode variable described in step s 200, its computational methods are

$s=\stackrel{\·}{e}+|e{|}^{1/2}\mathrm{sgn}\left(e\right)+ke---\left(2\right)$

Function sgn (e) is sign function, is defined as

$sgn\left(e\right)=\left\{\begin{array}{cc}1,& e>0\\ 0,& e=0\\ -1,& e<0\end{array}\right.---\left(3\right)$

Parameter k is the constant more than zero.

Wherein, design two tier adaptive algorithm described in step s 200, its method is as follows:

1) equivalent control signals is calculated

Utilizing low pass filter to obtain equivalent control signals, its computational methods are as follows:

$\begin{array}{c}\stackrel{\&CenterDot;}{\mathrm{\&sigma;}}=\frac{1}{\mathrm{\&tau;}}(\mathrm{sgn}\left(s\right)-\mathrm{\&sigma;})\\ {\hat{u}}_{eq}=\mathrm{\&beta;}\left(t\right)\mathrm{\&sigma;}+\mathrm{\&kappa;}\left(t\right)s\end{array}---\left(4\right)$

In formula, τ is filter time constant, and value meets 0 < τ ＜ ＜ 1, and s is that the sliding mode described in step S200 becomes Amount, σ is low-pass filter signal, and sgn (s) is sign function,For the equivalent control signals described in step S200, β (t) and κ T () is time-varying control parameter, computational methods are as follows

β (t)=L (t) β₀ (5)

κ (t)=L²(t)κ₀ (6)

β₀And κ₀For controlling parameter.

2) design two tier adaptive algorithm

L (t) in formula (5) and (6) is the control gain described in step S200, and its computational methods are as follows

L (t)=l₀+l(t) (7)

In formula, l₀For the constant value auto-adaptive parameter more than 0, l (t) is time-varying auto-adaptive parameter, and its computational methods are as follows

$\stackrel{\&CenterDot;}{l}\left(t\right)=\stackrel{\&CenterDot;}{L}\left(t\right)=-\mathrm{\&rho;}\left(t\right)\mathrm{sgn}\left(\mathrm{\&delta;}\right)---\left(8\right)$

In formula, the computational methods of δ are as follows

$\mathrm{\&delta;}\left(t\right)=L\left(t\right)-\frac{1}{{\mathrm{a\&beta;}}_0}\left|{\hat{u}}_{eq}\left(t\right)\right|-\mathrm{\&epsiv;}---\left(9\right)$

Wherein, a>0 is constant value auto-adaptive parameter, meets 0<a β simultaneously₀< 1, β₀It it is i.e. the control parameter in formula (5)；ε > 0 is The least constant value auto-adaptive parameter；The computational methods of the ρ (t) in formula (8) are as follows

ρ (t)=r₀+r(t) (10)

r₀> 0 it is constant value auto-adaptive parameter；The computational methods of time-varying part r (t) are

$\stackrel{\&CenterDot;}{r}\left(t\right)=\mathrm{\&gamma;}\left|\mathrm{\&delta;}\left(t\right)\right|---\left(11\right)$

γ > 0 is constant value auto-adaptive parameter.

In the present invention, the calculation process of two tier adaptive algorithm is as shown in Figure 2.

Wherein, the design superhelix control algolithm described in step S300, its method is as follows:

1) the fly wheel system rotating speed model of DC motor Driver is set up

As shown in Figure 4, its operation principle is as shown in Figure 5 for the fly wheel system structure of DC motor Driver.In Fig. 4, motor drives Rotating shaft, rotating shaft is arranged with rotor, and rotating shaft drives rotor, and the other end of rotor arranges the bearing class A of geometric unitA of supporting rotating shaft.Fig. 5 In, load the rotor for being connected, rotating shaft and supporting member with motor output shaft, motor is direct current generator, including successively with electricity Inductance, resistance and the armature that source is in series.The voltage of power supply used is controlled.Purpose of design controls voltage for design, it is achieved to electricity The control of machine rotor rotating speed.According to Fig. 4 and Fig. 5, the Differential of Speed equation that can derive fly wheel system is:

$T_1\stackrel{\&CenterDot;\&CenterDot;}{\mathrm{\&Omega;}}+T_2\stackrel{\&CenterDot;}{\mathrm{\&Omega;}}+\mathrm{\&Omega;}=K_m{u}_a-K_1{\stackrel{\&CenterDot;}{M}}_c-K_2{M}_c---\left(12\right)$

In formula, u_aFor being input to the control voltage of motor, M_cFor the total load torque being folded on motor reel,For folding The first differential of the total load torque closed on motor reel,For the first differential of rotating speed,For the second-order differential of rotating speed, T₁ And T₂For the electromechanical time constant of motor, its computational methods are as follows

$T_1=\frac{L_a{J}_m}{R_a{f}_m+C_m{C}_e}---\left(13\right)$

$T_2=\frac{L_a{f}_m+R_a{J}_m}{R_a{f}_m+C_m{C}_e}---\left(14\right)$

K_m、K₁And K₂For motor carry-over factor, its computational methods are as follows

$K_m=\frac{C_m}{R_a{f}_m+C_m{C}_e}---\left(15\right)$

$K_1=\frac{L_a}{R_a{f}_m+C_m{C}_e}---\left(16\right)$

$K_2=\frac{R_a}{R_a{f}_m+C_m{C}_e}---\left(17\right)$

Formula (13) in formula (17), R_aIt is the resistance of armature circuit, L_aIt is the inductance of armature circuit, J_mBe motor and The rotary inertia that load is folded on motor shaft, f_mIt is motor and the viscous friction coefficient that is folded on motor shaft of load, C_mIt it is electricity Machine moment coefficient, C_eIt it is winding back emf coefficient.

2) design superhelix control algolithm

The Differential of Speed equation that formula (12) represents is the fly wheel system rotating speed model of DC motor Driver, and this is one two Rank linear differential equation, in Practical Project, T₁、T₂、K_m、K₁、K₂、M_cWithThese model parameters and disturbance all can not be accurate Obtain, it is therefore necessary to consider parameter and the uncertain design speed control algolithm of disturbance, obtain controlling voltage.

Utilize the sliding mode variable s in step S200, design following superhelix control algolithm:

$\left\{\begin{array}{c}{u}_a=\frac{T_1^{*}}{K_m^{*}}\&lsqb;\mathrm{\&alpha;}\left(t\right)|s{|}^{1/2}sgn\left(s\right)+\mathrm{\&eta;}\left(t\right)s-z-\mathrm{\&phi;}\&rsqb;\\ \stackrel{\&CenterDot;}{z}=-\mathrm{\&beta;}\left(t\right)sgn\left(s\right)-\mathrm{\&kappa;}\left(t\right)s\end{array}\right.---\left(18\right)$

In formula,WithIt is respectively electromechanical time constant T₁With motor carry-over factor K_mNominal value, by motor factory Business provides, and the computational methods such as formula (5) and (6) of time-varying control parameter beta (t) and κ (t) are described, the calculating side of α (t) and η (t) Method is as follows

$\mathrm{\&alpha;}\left(t\right)=\sqrt{L\left(t\right)}{\mathrm{\&alpha;}}_0---\left(19\right)$

η (t)=L (t) η₀ (20)

Constant value controls parameter alpha₀、β₀、η₀And κ₀Value to meet following constraint

$\begin{array}{c}{\mathrm{\&alpha;}}_0>5^{1/4},{\mathrm{\&eta;}}_0>\mathrm{0,}{\mathrm{\&beta;}}_0>1,\\ {\mathrm{\&kappa;}}_0>\frac{8{\mathrm{\&eta;}}_0^2{\mathrm{\&beta;}}_0+22{\mathrm{\&eta;}}_0^2+9{\mathrm{\&alpha;}}_0^2{\mathrm{\&eta;}}_0^2}{4({\mathrm{\&beta;}}_0-1)}\end{array}---\left(21\right)$

The computational methods of addition Item φ are

$\mathrm{\&phi;}(s,L)=-\frac{\stackrel{\&CenterDot;}{L}\left(t\right)}{L\left(t\right)}s\left(t\right)---\left(22\right)$

Control gain L (t) andCalculate according to step S200.

In the present invention, superhelix control algolithm calculation process is as shown in Figure 3；The fly wheel system structure of DC motor Driver is such as Shown in Fig. 4；The fly wheel system schematic diagram of DC motor Driver is as shown in Figure 5.

Control engineer can give arbitrary target according to the mission requirements of actual fly wheel system in application process and turn Speed, and the control voltage obtained by the method transmission is realized rotating speed control to direct current generator.

The technique effect of the present invention:

1) the fly wheel system method for controlling number of revolution of the DC motor Driver that the present invention provides, is controlled with Speed of Reaction Wheels model Object, it is contemplated that model parameter uncertainty and the probabilistic coupling of load torque, improves the adaptability of system；

2) the fly wheel system method for controlling number of revolution of the DC motor Driver that the present invention provides have employed and has Second Order Sliding Mode The super-twisting algorithm of characteristic so that closed loop system has good robust to parameter uncertainty and the external disturbance of controlled device Property；

3) the fly wheel system method for controlling number of revolution of the DC motor Driver that the present invention provides, calculates by employing superhelix Method, compares existing sliding formwork and controls, can produce continuous print control signal, solve chattering phenomenon present in sliding formwork control；

4) the fly wheel system method for controlling number of revolution of the DC motor Driver that the present invention provides devises for fly wheel system Two tier adaptive algorithm, can be with self_adaptive adjusting gain, while keeping sliding formwork motion to exist so that control gain Value the least, and then make control energy consumption relatively low.

Specifically refer to the various realities that the fly wheel system method for controlling number of revolution of the DC motor Driver according to the present invention proposes Execute the described below of example, by apparent for the above and other aspect making the present invention.

Accompanying drawing explanation

The Control system architecture signal of the fly wheel system method for controlling number of revolution of the DC motor Driver that Fig. 1 provides for the present invention Figure；

Two tier adaptive algorithm in the fly wheel system method for controlling number of revolution of the DC motor Driver that Fig. 2 provides for the present invention Schematic flow sheet；

Superhelix control algolithm stream in the fly wheel system method for controlling number of revolution of the DC motor Driver that Fig. 3 provides for the present invention Journey schematic diagram；

The direct current generator controlled in the fly wheel system method for controlling number of revolution of the DC motor Driver that Fig. 4 provides by the present invention The fly wheel system structure chart driven；

In the fly wheel system method for controlling number of revolution of the DC motor Driver that Fig. 5 provides for the present invention, handled direct current generator drives Dynamic fly wheel system schematic diagram；

Fig. 6 is to use pid control algorithm that the fly wheel system rotating speed of DC motor Driver is controlled result figure；

Fig. 7 is to use sliding mode control algorithm that the fly wheel system rotating speed of DC motor Driver is controlled result figure；

Fig. 8 is that the preferred embodiment of the present invention controls result figure to the fly wheel system rotating speed superhelix of DC motor Driver.

In figure, literary composition, symbol description is as follows:

Ω_CRotating speed of target for flywheel rotor；

Ω is the actual speed of flywheel rotor；

E is the margin of error between rotating speed of target and actual speed；

S is sliding mode variable；

For equivalent control signals；

L (t) is for controlling gain；

For controlling the first differential of gain；

u_aFor driving the control voltage of motor；

τ is the time constant of low pass filter；

a、ε、γ、r₀And l₀For auto-adaptive parameter；

α₀、η₀、β₀And κ₀For controlling parameter；

WithIt is respectively electromechanical time constant and the nominal value of motor carry-over factor.

Σ is summation operation；

∫ is integral operation；

K is sliding formwork coefficient；

Du/dt is for differentiating；

| | for signed magnitude arithmetic(al)；

Sgn () is symbolic operation；

∫|u_e(t) | dt represents controlling voltage u_eAbsolute value quadrature, can be used for measure control method energy consumption.

Detailed description of the invention

The accompanying drawing of the part constituting the application is used for providing a further understanding of the present invention, and the present invention's is schematic real Execute example and illustrate for explaining the present invention, being not intended that inappropriate limitation of the present invention.

Below in conjunction with instantiation, the method providing the present invention is described in detail.

The fly wheel system method for controlling number of revolution of a kind of DC motor Driver, it specifically comprises the following steps that

Step one: given rotating speed of target also measures actual speed

Given rotating speed of target is Ω_C=1rad, initial time actual speed is Ω=0rad.

Step 2: the margin of error calculates

Calculating rotating speed of target and the direct margin of error of actual speed: e=Ω_C-Ω。

Step 3: sliding mode variable calculates

Calculating sliding mode variable:The present embodiment takes k=2.

Step 4: two tier adaptive algorithm designs

1) equivalent control signals is calculated

$\left\{\begin{array}{c}\stackrel{\&CenterDot;}{\mathrm{\&sigma;}}=\frac{1}{\mathrm{\&tau;}}\left(sgn\right(s)-\mathrm{\&sigma;})\\ {\hat{u}}_{eq}=\mathrm{\&beta;}\left(t\right)\mathrm{\&sigma;}+\mathrm{\&kappa;}\left(t\right)s\\ \mathrm{\&beta;}\left(t\right)=L\left(t\right){\mathrm{\&beta;}}_0\\ \mathrm{\&kappa;}\left(t\right)=L^2\left(t\right){\mathrm{\&kappa;}}_0\end{array}\right.---\left(23\right)$

The present embodiment takes τ=10^-3。

2) design two tier adaptive algorithm

$\left\{\begin{array}{c}L\left(t\right)=l_0+l\left(t\right)\\ \stackrel{\&CenterDot;}{l}\left(t\right)=\stackrel{\&CenterDot;}{L}\left(t\right)=-\mathrm{\&rho;}\left(t\right)sgn\left(\mathrm{\&delta;}\right)\\ \mathrm{\&rho;}\left(t\right)=r_0+r\left(t\right)\\ \stackrel{\&CenterDot;}{r}\left(t\right)=\mathrm{\&gamma;}\left|\mathrm{\&delta;}\left(t\right)\right|\\ \mathrm{\&delta;}\left(t\right)=L\left(t\right)-\frac{1}{{\mathrm{a\&beta;}}_0}\left|{\hat{u}}_{eq}\left(t\right)\right|-\mathrm{\&epsiv;}\end{array}\right.---\left(24\right)$

In the present embodiment, take l₀=0.1, r₀=0.1, γ=10, a=0.8636, ε=0.05.Thereby is achieved time-varying Control gain L (t).

Step 5: superhelix control algorithm design

1) the fly wheel system rotating speed model of DC motor Driver is set up

$\stackrel{\&CenterDot;\&CenterDot;}{\mathrm{\&Omega;}}+\frac{T_2}{T_1}\stackrel{\&CenterDot;}{\mathrm{\&Omega;}}+\frac{1}{T_1}\mathrm{\&Omega;}=\frac{K_m}{T_1}{u}_a-\frac{K_1{\stackrel{\&CenterDot;}{M}}_c+K_2{M}_c}{T_1}---\left(25\right)$

In the present embodiment, fly wheel system rotating speed model is realized by numerical simulation, and in phantom, the value of parameter is

2) design superhelix control algolithm

$\left\{\begin{array}{c}{u}_a=\frac{T_1^{*}}{K_m^{*}}\&lsqb;\mathrm{\&alpha;}\left(t\right)|s{|}^{1/2}\mathrm{sgn}\left(s\right)+\mathrm{\&eta;}\left(t\right)s-z-\mathrm{\&phi;}\&rsqb;\\ \stackrel{\&CenterDot;}{z}=-\mathrm{\&beta;}\left(t\right)\mathrm{sgn}\left(s\right)-\mathrm{\&kappa;}\left(t\right)s\\ \mathrm{\&alpha;}\left(t\right)=\sqrt{L\left(t\right)}{\mathrm{\&alpha;}}_0\\ \mathrm{\&eta;}\left(t\right)=L\left(t\right){\mathrm{\&eta;}}_0\\ \mathrm{\&phi;}(s,L)=-\frac{\stackrel{\&CenterDot;}{L}\left(t\right)}{L\left(t\right)}s\left(t\right)\end{array}\right.---\left(26\right)$

The control parameter alpha occurred in formula (23) and (26)₀、β₀、η₀And κ₀Value constraints to be met

$\begin{array}{c}{\mathrm{\&alpha;}}_0>5^{1/4},{\mathrm{\&eta;}}_0>0,{\mathrm{\&beta;}}_0>1\\ {\mathrm{\&kappa;}}_0>\frac{8{\mathrm{\&eta;}}_0^2{\mathrm{\&beta;}}_0+22{\mathrm{\&eta;}}_0^2+9{\mathrm{\&alpha;}}_0^2{\mathrm{\&eta;}}_0^2}{4({\mathrm{\&beta;}}_0-1)}\end{array},$

In the present embodiment, takeβ₀=1.1, η₀=0.5, κ₀=68.75, thereby is achieved control Voltage u processed_a(t)。

In order to the control method with the present invention contrasts, under the same conditions, it is respectively adopted and provides method with the present invention Different PID control method and sliding-mode control are controlled emulation to the fly wheel system model of DC motor Driver.Wherein Pid control algorithm is:

$u_a\left(t\right)=K_{p}e+K_I\&Integral;edt+K_D\stackrel{\&CenterDot;}{e}---\left(27\right)$

This comparative example 1 takes K_p=50, K_I=10, K_D=0.1.

Sliding mode control algorithm is:

u_a(t)=λ s+k_m sgn(s) (28)

In this comparative example 2, take λ=1, k_m=10.

The fly wheel system rotating speed of above example and documents 1～2 gained DC motor Driver control result such as Fig. 6～ Shown in 8.Fig. 6 gives the control result using pid control algorithm (formula (27)), and Fig. 7 gives employing sliding mode control algorithm The control result of (formula (28)), Fig. 8 gives the two tier adaptive algorithm and superhelix control algolithm using the present invention to propose Control result.As seen from Figure 8: method for controlling number of revolution proposed by the invention can make fly wheel system rotating speed be exactly adjusted to Rotating speed of target, illustrates the effectiveness of the method；By with Fig. 6 and Fig. 7 carry out contrast visible: the present invention offer method dynamic Steadily, control accuracy is high in response, and the control signal continuous and derivable of generation effectively eliminates chattering phenomenon, the energy consumption needed for control Minimum.

Those skilled in the art will understand that the scope of the present invention is not restricted to example discussed above, it is possible to carries out it Some changes and amendment, the scope of the present invention limited without deviating from appended claims.Although oneself is through in accompanying drawing and explanation Book illustrates and describes the present invention in detail, but such explanation and description are only explanations or schematic, and nonrestrictive. The present invention is not limited to the disclosed embodiments.

By to accompanying drawing, the research of specification and claims, when implementing the present invention, those skilled in the art are permissible Understand and realize the deformation of the disclosed embodiments.In detail in the claims, term " includes " being not excluded for other steps or element, And indefinite article " " or " a kind of " are not excluded for multiple.Some measure quoted in mutually different dependent claims The fact does not means that the combination of these measures can not be advantageously used.It is right that any reference marker in claims is not constituted The restriction of the scope of the present invention.

Claims (3)

1. the fly wheel system method for controlling number of revolution of a DC motor Driver, it is characterised in that comprise the following steps:

Step S100: the actual speed obtained by rotating speed of target and measurement calculates rotating speed of target and margin of error e of actual speed, so Rear calculating sliding mode variable；

Step S200: obtain equivalent control signals, with equivalent control signals after being modulated by low-pass filtered for sliding mode variable device For input, to control gain for output, build two tier adaptive algorithm and also set auto-adaptive parameter, obtain controlling gain

Step S300: set up the fly wheel system rotating speed model of DC motor Driver, with the sliding mode variable in step S200 be Input, in conjunction with the control gain described in gained, builds superhelix control algolithm, adjusts and control parameter, obtains the control electricity of motor Pressure；

Described in described step S200, two tier adaptive algorithm obtains according to the following steps:

1) equivalent control signals is calculated

Utilize low pass filter obtain equivalent control signals:

$\begin{array}{c}\stackrel{\&CenterDot;}{\mathrm{\&sigma;}}=\frac{1}{\mathrm{\&tau;}}\left(\mathrm{sgn}\right(s)-\mathrm{\&sigma;})\\ {\hat{u}}_{eq}=\mathrm{\&beta;}\left(t\right)\mathrm{\&sigma;}+\mathrm{\&kappa;}\left(t\right)s\end{array}---\left(4\right)$

In formula, τ is filter time constant, and value meets 0 < τ ＜ ＜ 1, and s is the sliding mode variable described in step S200, σ For low-pass filter signal, sgn (s) is sign function,For the equivalent control signals described in step S200, β (t) and κ (t) it is Time-varying control parameter, is calculated by formula (5)～(6):

β (t)=L (t) β₀ (5)

κ (t)=L²(t)κ₀ (6)

β₀And κ₀For controlling parameter；

2) two tier adaptive algorithm is built

L (t) in formula (5) and (6) is the control gain described in step S200, calculates by formula (7):

L (t)=l₀+l(t) (7)

In formula, l₀For the constant value auto-adaptive parameter more than 0, l (t) is time-varying auto-adaptive parameter, calculates by formula (8):

$\stackrel{\&CenterDot;}{l}\left(t\right)=\stackrel{\&CenterDot;}{L}\left(t\right)=-\mathrm{\&rho;}\left(t\right)\mathrm{sgn}\left(\mathrm{\&delta;}\right)---\left(8\right)$

In formula, δ presses formula (9) and calculates:

$\mathrm{\&delta;}\left(t\right)=L\left(t\right)-\frac{1}{{\mathrm{a\&beta;}}_0}\left|{\hat{u}}_{eq}\left(t\right)\right|-\mathrm{\&epsiv;}---\left(9\right)$

Wherein, a>0 is constant value auto-adaptive parameter, meets 0<a β simultaneously₀< 1, β₀It it is i.e. the control parameter in formula (5)；ε > 0 is very Little constant value auto-adaptive parameter；

ρ (t) in formula (8) presses formula (10) and calculates:

ρ (t)=r₀+r(t) (10)

r₀> 0 it is constant value auto-adaptive parameter；Time-varying part r (t) is pressed formula (11) and is calculated:

$\stackrel{\&CenterDot;}{r}\left(t\right)=\mathrm{\&gamma;}\left|\mathrm{\&delta;}\left(t\right)\right|---\left(11\right)$

γ > 0 is constant value auto-adaptive parameter；

Described in described step S300, superhelix control algolithm is obtained by following steps:

1) the fly wheel system rotating speed model of DC motor Driver is set up

The structure of the fly wheel system according to handled DC motor Driver derives the Differential of Speed equation of fly wheel system:

$T_1\stackrel{\&CenterDot;\&CenterDot;}{\mathrm{\&Omega;}}+T_2\stackrel{\&CenterDot;}{\mathrm{\&Omega;}}+\mathrm{\&Omega;}=K_m{u}_a-K_1{\stackrel{\&CenterDot;}{M}}_c-K_2{M}_c---\left(12\right)$

In formula, u_aFor being input to the control voltage of motor, M_cFor the total load torque being folded on motor reel,For being folded to The first differential of the total load torque on motor reel,For the first differential of rotating speed,For the second-order differential of rotating speed, T₁And T₂ Press formula (13) for the electromechanical time constant of motor to calculate:

$T_1=\frac{L_a{J}_m}{R_a{f}_m+C_m{C}_e}---\left(13\right)$

$T_2=\frac{L_a{f}_m+R_a{J}_m}{R_a{f}_m+C_m{C}_e}---\left(14\right)$

K_m、K₁And K₂Press formula (15) for motor carry-over factor～(17) calculate:

$K_m=\frac{C_m}{R_a{f}_m+C_m{C}_e}---\left(15\right)$

$K_1=\frac{L_a}{R_a{f}_m+C_m{C}_e}---\left(16\right)$

$K_2=\frac{R_a}{R_a{f}_m+C_m{C}_e}---\left(17\right)$

In formula (13) to formula (17), R_aIt is the resistance of armature circuit, L_aIt is the inductance of armature circuit, J_mIt is that motor is with negative Carry the rotary inertia being folded on motor shaft, f_mIt is motor and the viscous friction coefficient that is folded on motor shaft of load, C_mIt it is motor Moment coefficient, C_eIt it is winding back emf coefficient；

2) design construction superhelix control algolithm

According to the sliding mode variable s in step S200, obtain the superhelix control algolithm as shown in formula (18):

$\left\{\begin{array}{c}{u}_a=\frac{T_1^{*}}{K_m^{*}}\&lsqb;\mathrm{\&alpha;}\left(t\right){\left|s\right|}^{1/2}sgn\left(s\right)+\mathrm{\&eta;}\left(t\right)s-z-\mathrm{\&phi;}\&rsqb;\\ \stackrel{\&CenterDot;}{z}=-\mathrm{\&beta;}\left(t\right)sgn\left(s\right)-\mathrm{\&kappa;}\left(t\right)s\end{array}\right.---\left(18\right)$

In formula,WithIt is respectively electromechanical time constant T₁With motor carry-over factor K_mNominal value, time-varying control parameter beta (t) and The computational methods of κ (t) such as formula (5) and (6) are described, and α (t) and η (t) presses formula (19)～(20) calculate:

$\mathrm{\&alpha;}\left(t\right)=\sqrt{L\left(t\right)}{\mathrm{\&alpha;}}_0---\left(19\right)$

η (t)=L (t) η₀ (20)

Constant value controls parameter alpha₀、β₀、η₀And κ₀Value to meet the constraints as shown in formula (21):

α₀>5^1/4,η₀>0,β₀>1,

${\mathrm{\&kappa;}}_0>\frac{8{\mathrm{\&eta;}}_0^2{\mathrm{\&beta;}}_0+22{\mathrm{\&eta;}}_0^2+9{\mathrm{\&alpha;}}_0^2{\mathrm{\&eta;}}_0^2}{4({\mathrm{\&beta;}}_0-1)}---\left(21\right)$

Addition Item φ presses formula (22) and calculates:

$\mathrm{\&phi;}(s,L)=-\frac{\stackrel{\&CenterDot;}{L}\left(t\right)}{L\left(t\right)}s\left(t\right)---\left(22\right)$

Wherein, control gain L (t) andIt is calculated according to step S200.

The fly wheel system method for controlling number of revolution of DC motor Driver the most according to claim 1, it is characterised in that described step The margin of error between rotating speed of target and described actual speed described in rapid S100, is calculated by formula (1):

E=Ω_C-Ω (1)

Wherein, Ω_CFor rotating speed of target, Ω is actual speed.

The fly wheel system method for controlling number of revolution of DC motor Driver the most according to claim 1, it is characterised in that described step Sliding mode variable described in rapid S200 is pressed formula (2) and is calculated:

$s=\stackrel{\&CenterDot;}{e}+|e{|}^{1/2}\mathrm{sgn}\left(e\right)+ke---\left(2\right)$

Wherein, function sgn (e) is sign function, is defined as:

$sgn\left(e\right)=\left\{\begin{array}{cc}1,& e>0\\ 0,& e=0\\ -1,& e<0\end{array}\right.---\left(3\right)$

Wherein, parameter k is the constant more than zero.