CN107061164B - A kind of uncertain blower variable-pitch of consideration executing agency is away from Sliding Mode Adaptive Control method - Google Patents
A kind of uncertain blower variable-pitch of consideration executing agency is away from Sliding Mode Adaptive Control method Download PDFInfo
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
- F03D—WIND MOTORS
- F03D7/00—Controlling wind motors
- F03D7/02—Controlling wind motors the wind motors having rotation axis substantially parallel to the air flow entering the rotor
- F03D7/022—Adjusting aerodynamic properties of the blades
- F03D7/0224—Adjusting blade pitch
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
- F03D—WIND MOTORS
- F03D7/00—Controlling wind motors
- F03D7/02—Controlling wind motors the wind motors having rotation axis substantially parallel to the air flow entering the rotor
- F03D7/04—Automatic control; Regulation
- F03D7/042—Automatic control; Regulation by means of an electrical or electronic controller
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
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Abstract
The invention proposes a kind of uncertain blower variable-pitch of consideration executing agency away from Sliding Mode Adaptive Control method, belongs to air-blower control technical field.The step of the method are as follows: step 1: in permanent magnet direct-drive wind power system, with blower mechanical output archetypeBased on, utilize fan transmission system model
Description
Technical Field
The invention relates to a fan variable pitch sliding mode self-adaptive control method considering uncertainty of an actuating mechanism, and belongs to the technical field of fan control.
Background
When the fan works above the rated wind speed, in order to reduce the impact of the excess power on the power grid, avoid the mechanical load of the wind power system from exceeding the limit and consider the limit of the capacity of the converter, the wind energy conversion efficiency needs to be reduced through the pitch control, and the energy captured by the fan is limited, so that the captured power is kept at the rated value.
According to an empirical formula of the wind energy utilization coefficient of the fan, the high-order strong coupling nonlinear relationship directly exists between the wind energy utilization coefficient of the fan and the input pitch angle, the fan pitch-variable actuating mechanism can be equivalent to a large-inertia system, the lag is serious, the working environment of the fan is generally severe, and the external interference is serious. Therefore, there is uncertainty in both the parameters of the wind turbine model and the pitch actuator. The control accuracy of the traditional PID control depends on accurate modeling of a controlled object, and is greatly influenced under the conditions that model parameters are uncertain and external interference is serious. In order to achieve better control effect, some intelligent control methods are applied to pitch control, such as fuzzy control. Fuzzy control does not require an accurate mathematical model of the controlled object, and the hysteresis system has strong robustness to nonlinear time variation. However, fuzzy control mainly depends on experience and trial and error in controller design, control rule design is sometimes difficult, and a fuzzy controller does not have an integration link and is not high in control precision.
Disclosure of Invention
The invention provides a synovial membrane adaptive control method of a fan variable pitch actuator with an uncertain item, aiming at solving the technical problem that the fan variable pitch actuator with the uncertain item can not be stably controlled, and the adopted technical scheme is as follows:
a sliding mode adaptive control method for a wind turbine pitch actuator having an uncertainty, the method comprising:
step 1: in a permanent magnet direct-drive wind power system, a fan mechanical power original model is usedBased on the model of the fan transmission systemObtaining a fan model with uncertain parameters of the fan model and uncertain input of a variable pitch actuating mechanism; wherein ρ is the air density; r is the radius of the wind turbine blade; v is the wind speed; cp(β, lambda) is the wind energy utilization coefficient, β is the wind turbine bladeA pitch angle; λ is the tip speed ratio.
The expression of tip speed ratio λ is:coefficient of wind energy utilization CpThe expression of (a) is:in the formula, λiThe expression of (a) is:
step 2: and (3) aiming at the fan model with uncertain parameters and uncertain input of the variable pitch actuating mechanism obtained in the step (1), obtaining the fan sliding mode self-adaptive controller with online adjustment of controller parameters on the basis of the nonsingular terminal sliding mode surface model.
Further, the step1 of obtaining the wind turbine model with uncertain parameters of the wind turbine model and uncertain input of the variable pitch actuating mechanism comprises the following steps:
the first step is as follows: original model of mechanical power of fanObtaining a mechanical torque model of the fan:
the second step is that: constant power operating point (ω) of the mechanical torque model for the first stepo，vo，βo) Linearizing the mechanical torque model of the constant-power working point to obtain a linearized constant-power working point mechanical torque model: t isω-Toα delta omega + ξ delta v + gamma delta β, wherein delta omega is (omega-omega)o)，Δv＝(v-vo)，Δβ＝(β-βo)，To＝f(ωo，vo，βo)，α, gamma, ξ are constant parameters;
the third step: and (3) enabling the linearized constant working point mechanical torque model obtained in the second step to be as follows: t isω-ToSubstituting α Δ ω + ξ Δ v + γ Δ β into the fan drive system model described in step1In the method, a linear model of the fan at a constant-power working point is obtained
The fourth step: the fan variable pitch actuating mechanism is equivalent to an inertia system, and the model of the inertia system is as follows:
and fifthly, obtaining a parameter combination with a constant parameter estimated value and an uncertain part by using the constant parameters α, gamma, wherein the parameter combination comprises the following steps:wherein,is an estimated value of the constant parameter, Δ α, Δ ξ, Δ γ is an uncertain value of the constant parameter;
and a sixth step: bringing the model of the inertial system of the fourth step and the parameter combination of the fifth step into the model of the third stepObtaining an uncertain fan model containing fan model parameters and input of a variable pitch actuating mechanism in the step 1; the fan model specifically comprises:wherein,and the constant parameter uncertain part and the actuator uncertain part represent the fan model.
Further, the step2 of obtaining the adaptive parameter model includes:
step 1: taking the derivative of the fan rotation speed error and the rotation speed error, and designing a nonsingular terminal sliding mode surface:wherein p is more than q and more than 0, and both p and q are odd numbers; e ═ Δ ω ═ ω - ωoThe deviation between the fan rotating speed and the fan rated rotating speed is obtained;
step 2: designing an upper bound of an uncertain part of a required model by the fan sliding mode adaptive controller; the upper bound being denoted by a, i.e.
Step 3: in the design process of the fan sliding mode adaptive controller, the parameters of the fan sliding mode adaptive controllerRepresenting the estimated value of a, the adaptive law and sliding mode controller thereof designs the following four models, namely an adaptive parameter model:
βc＝βceq+βcn
it can be proved that by adopting the self-adaptive law and the control rate, namely the self-adaptive parameter model, the sliding mode surface can be converged to zero in a limited time,converging to the true value a.
The invention has the beneficial effects that:
the invention provides a sliding mode self-adaptive control method of a fan variable pitch actuating mechanism with an uncertain item, which has the following beneficial effects:
1. the sliding mode self-adaptive control method provided by the invention does not need to determine the specific value of the constant parameter of the fan controller or the parameter boundary, but realizes the on-line modulation of the fan controller (the fan controller is used for controlling the actuating mechanism of the fan) by determining the sliding mode self-adaptive parameter model, thereby improving the control capability of the fan controller on the parameter change of the fan, ensuring and strengthening the anti-interference capability of the fan controller.
2. The sliding mode self-adaptive control method provided by the invention considers the influence of the uncertainty of the fan model parameters and the uncertainty of the actuating mechanism on the fan control, and determines the boundaries of each uncertain part by using the self-adaptive parameter model in a mode of combining the sliding mode variable pitch control and the self-adaptive control so as to improve the stability and the accuracy of the fan controller control process, and can quickly and accurately adjust the pitch angle of the fan according to the change of the wind speed to keep the rotating speed of the fan constant.
3. The self-adaptive method adopted by the sliding mode self-adaptive control method provided by the invention can effectively limit the energy input by a fan system under the condition of not accurately identifying the parameters of a model equation, inhibit the rotation speed disturbance according to the change of the wind speed and meet the power control requirement in a high wind section.
4. The nonsingular terminal sliding mode surface adopted by the sliding mode self-adaptive control method can ensure that the system converges to a balance point within limited time.
Drawings
FIG. 1 is a control block diagram of a sliding mode self-adaptive control method according to the present invention
FIG. 2 is a graph of random wind speed collected in an actual wind field
FIG. 3 shows the fan speed
FIG. 4 shows the input pitch angle of the pitch actuator
FIG. 5 shows the wind energy utilization coefficient of a fan
FIG. 6 shows the tip speed ratio of the fan
FIG. 7 shows the output power of the generator
Detailed Description
The present invention will be further described with reference to the following specific examples, but the present invention is not limited to these examples.
Example 1
The sliding mode variable structure control method has the characteristics of quick response, high control precision, strong robustness and the like, and is widely applied to the control of a nonlinear system with uncertain parameters and external interference, however, the sliding mode variable structure control method has the characteristic of insensitivity to the uncertainty and parameter disturbance of a fan system model after reaching a sliding mode surface. In the process of approaching the sliding mode surface, the controller stability can be ensured only if the boundary of an uncertain item is known, however, in an actual system, the boundary of an uncertain parameter cannot be accurately obtained, so that the design of the controller parameter in the control process needs to be large enough to ensure the stability of the controller, the control process is quite conservative, and the jitter of the system is increased due to the fact that the controller parameter is selected too large, and the control performance-stability is affected. On the other hand, the sliding mode variable structure control method only considers the uncertainty of the fan model parameters in the control process, and does not consider the influence of the uncertainty of the actuating mechanism on the fan control, so that the accuracy of the variable structure control method is poor. Therefore, in order to solve the problems of poor stability and poor accuracy of the variable structure control method, the embodiment provides a sliding mode self-adaptive control method of a fan pitch control actuating mechanism with an uncertainty item, and the method comprises the following steps:
step 1: in a permanent magnet direct-drive wind power system, a fan mechanical power original model is usedBased on the model of the fan transmission systemObtaining a fan model with uncertain parameters of the fan model and uncertain input of a variable pitch actuating mechanism; wherein, PωCapturing power for a fan, wherein rho is air density; r is the radius of the wind turbine blade; v is the wind speed; cp(β lambda) is the wind energy utilization coefficient, β is the pitch angle of the wind turbine blades, lambda is the tip speed ratio, J is the rotational inertia of the wind power system, and T iseFor generator electromagnetic torque, TωIs the mechanical torque of the fan.
The expression of tip speed ratio λ is:wherein ω represents fan speed; coefficient of wind energy utilization CpThe expression of (a) is:in the formula, λiThe expression of (a) is:
step 2: and (3) aiming at the fan model with uncertain parameters and uncertain input of the variable pitch actuating mechanism obtained in the step (1), obtaining an adaptive parameter model of the fan sliding mode adaptive controller on the basis of the nonsingular terminal sliding mode surface model.
Further, the step1 of obtaining the wind turbine model with uncertain parameters of the wind turbine model and uncertain input of the variable pitch actuating mechanism comprises the following steps:
the first step is as follows: original model of mechanical power of fanObtaining a mechanical torque model of the fan:
the second step is that: constant power operating point (ω) of the mechanical torque model for the first stepo，vo，βo) Linearizing the mechanical torque model of the constant-power working point to obtain a linearized constant-power working point mechanical torque model: t isω-Toα delta omega + ξ delta v + gamma delta β, wherein delta omega is (omega-omega)o)，Δv＝(v-vo)，Δβ＝(β-βo)，To＝f(ωo，vo，βo)，α, gamma, ξ is constant parameter, gamma is coefficient of pitch actuator, delta omega is increment of rotation speed, delta v is increment of wind speed, delta β is increment of pitch angle, T is increment of pitch angleo,ωo,voRespectively representing the fan torque, the fan rotating speed and the wind speed at a constant-power working point, wherein β is the real-time pitch angle of the fan;
the third step:and (3) enabling the linearized constant working point mechanical torque model obtained in the second step to be as follows: t isω-ToSubstituting α Δ ω + ξ Δ v + γ Δ β into the fan drive system model described in step1In (1), obtaining a model
The fourth step: the fan variable pitch actuating mechanism is equivalent to an inertia system, and the model of the inertia system is as follows:τβfor the time constant of the pitch actuator, βcInputting a pitch angle;
and fifthly, obtaining a parameter combination with a constant parameter estimated value and an uncertain part by using the constant parameters α, gamma, wherein the parameter combination comprises the following steps:wherein,the constant parameters α, gamma, ξ are estimated values, delta α, delta ξ, delta gamma is an uncertain value of the constant parameters α, gamma, ξ of the synovial membrane adaptive controller, and gamma is a coefficient of a pitch actuator, so that the uncertainty of gamma can cause the input uncertainty of the actuator.
And a sixth step: bringing the model of the inertial system of the fourth step and the parameter combination of the fifth step into the model of the third stepObtaining an uncertain fan model containing fan model parameters and input of a variable pitch actuating mechanism in the step 1; the fan model specifically comprises:wherein,and the constant parameter uncertain part and the actuator uncertain part represent the fan model.
Further, the step2 of obtaining the adaptive parameter model includes:
step 1: taking the rotating speed error and the derivative of the error of the fan, and designing a nonsingular terminal sliding mode surface:
the control target of the fan variable pitch actuating mechanism controller is to quickly stabilize the rotating speed at the rated rotating speed and output a pitch angle signal β, wherein p and q are sliding mode surface design parameters, and both p and q are odd numbers and satisfy p>q>0；e＝Δω＝ω-ωoThe deviation between the fan rotating speed and the fan rated rotating speed is obtained; and the derivative of the deviation of the fan speed from the fan nominal speed is
Step2, designing the adaptive controller of the sliding mode of the wind turbine needs the upper bound of the uncertain part of the model, wherein the upper bound is denoted by a, namely α is set as
Step 3: controller parameters during controller designAnd representing the estimated value of a, and designing an adaptive law and sliding mode controller as follows, namely an adaptive parameter model. It can be shown that, with the adaptive parametric model, the sliding-mode surface can converge to zero in a limited time,converge to the true value a
βc＝βceq+βcn
It can be proved that by adopting the self-adaptive law and the control rate, namely the self-adaptive parameter model, the sliding mode surface can be converged to zero in a limited time,converging to the true value a.
β thereinceqFor equivalent control, βcnFor switching control, η and k are both constants larger than zero, the adaptive parameter model is an adaptive parameter model of the sliding mode adaptive controller for the fan variable pitch actuating mechanism with an uncertain item, and the sliding mode adaptive controller for the fan variable pitch actuating mechanism can be obtained by using the adaptive parameters.
Controller stability certification:
selecting a Lyapunov function as follows:
wherein:because the output torque of the fan monotonously decreases along with the increase of the pitch angle, the output torque of the fan can be obtained
Derivation of the lyapunov function yields:
the inverse of the Lyapunov function is constantly smaller than zero, so that the stability of the designed controller is ensured. The adaptive control block diagram of the pitch-controlled sliding mode is shown in fig. 1.
When the wind speed is higher than the rated wind speed, the robust self-adaptive variable-pitch controller enables the rotating speed omega of the fan to be kept at the rated rotating speed omeganNear ω remains at ωnAnd meanwhile, the constant electromagnetic torque of the generator is controlled, and the constant power operation of the system is ensured. The parameters of the permanent magnet direct-drive wind power system are as follows: rho is 1.25kg/m3，R＝5m，Pen＝36kW，ωn＝20rad/s，J＝10kg·m2，pn＝6，ψf ＝0.8Wb，Rs＝2.875Ω，Ld＝33mH，Lq＝33mH，τβ0.2. The parameters of the robust adaptive pitch controller are: rho is air density, R is fan radius, PenFor generator rated power, omeganAt rated speed, J is the rotational inertia of the fan, pnIs the pole pair number psi of the generatorfIs a permanent magnet flux linkage, RsIs the generator equivalent resistance, LdIs d-axis inductance of the generator, LqFor generator q-axis inductance, tauβIs the pitch actuator time constant.Is an estimated value of the fan model parameter.
A group of wind speed experimental data actually measured in the wind power plant is shown in figure 2, simulation analysis is carried out, and simulation results are shown in figures 3-7.
When the wind speed of the wind field is above the rated value, under the condition that the wind speed is changed randomly, the rotating speed of the fan can be maintained near the rated rotating speed of 20rad/s as can be seen from figure 3, and the maximum value of the fluctuation of the rotating speed of the fan can be found to be within 1 percent of the rated rotating speed through numerical analysis. As can be seen from fig. 4 to 6, the blade tip speed ratio and the wind energy utilization coefficient decrease as the pitch angle increases, and the blade tip speed ratio and the wind energy utilization coefficient increase as the pitch angle decreases. Fig. 7 shows the output power of the wind power generator, and as can be seen from fig. 7, the output power of the generator can be stabilized near 36kw, and the wind power system can operate in a constant power state.
According to the simulation result, under the condition that uncertainty of parameters and uncertainty of input of a fan model are considered, the designed controller can effectively limit the power of a wind power system and inhibit fluctuation of rotating speed, and when the controller is designed, parameters are adjusted on line by adopting a self-adaptive method according to the parameters and the perturbation of the input of the controller, so that the stability of the controller is ensured, and an ideal control effect is achieved.
In conclusion, under the condition that the parameters of the model equation do not need to be accurately identified, the designed controller can effectively limit the energy input by the system, inhibit the rotation speed disturbance according to the change of the wind speed and meet the power control requirement in a high wind section.
Although the present invention has been described with reference to the preferred embodiments, it should be understood that various changes and modifications can be made therein by those skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (2)
1. An adaptive control method for a variable pitch sliding mode of a wind turbine, which takes account of uncertainty of an actuating mechanism, is characterized by comprising the following steps:
step 1: in a permanent magnet direct-drive wind power system, a fan mechanical power original model is usedBased on the model of the fan transmission systemObtaining a fan model with uncertain parameters of the fan model and uncertain input of a variable pitch actuating mechanism; wherein, PωCapturing power for a fan, wherein rho is air density; r is the radius of the wind turbine blade; v is the wind speed; cp(β lambda) is the wind energy utilization coefficient, β is the pitch angle of the wind turbine blades, lambda is the tip speed ratio, J is the rotational inertia of the wind power system, and T iseFor generator electromagnetic torque, TωIs the mechanical torque of the fan; omega is the rotating speed of the fan rotor;
step 2: aiming at the fan model with uncertain parameters and uncertain input of a variable pitch actuating mechanism obtained in the step1, obtaining a fan sliding mode self-adaptive controller with online adjustment of controller parameters on the basis of a nonsingular terminal sliding mode surface model;
the step1 of obtaining the uncertain parameter of the fan model and the uncertain input fan model of the variable pitch actuating mechanism comprises the following steps:
the first step is as follows: original model of mechanical power of fanObtaining a mechanical torque model of the fan:
the second step is that: constant power operating point (ω) of the mechanical torque model for the first stepo，vo，βo) Linearizing the mechanical torque model of the constant-power working point to obtain a linearized constant-power working point mechanical torque model: t isω-To＝αΔω+ξΔv+γΔβ；
Wherein Δ ω ═ ω - ωo)，Δv＝(v-vo)，Δβ＝(β-βo)，To＝f(ωo，vo，βo)，α, gamma, ξ is constant parameter, gamma is the coefficient of pitch actuator, delta omega is the increment of rotation speed, delta v is wind speedIncrement, Δ β, represents the pitch angle increment, To,ωo,voRespectively representing the fan torque, the fan rotating speed and the wind speed at a constant-power working point, wherein β is the real-time pitch angle of the fan;
the third step: and (3) enabling the linearized constant power working point mechanical torque model obtained in the second step to be as follows: t isω-ToSubstituting α Δ ω + ξ Δ v + γ Δ β into the fan drive system model described in step1In the method, a linear model of the fan at a constant-power working point is obtainedJ is the rotational inertia of the wind power system;
the fourth step: the method comprises the following steps of (1) enabling a fan variable pitch actuating mechanism to be equivalent to an inertial system, wherein a model of the inertial system is as follows:τβfor the time constant of the pitch actuator, βcInputting a pitch angle;
and fifthly, obtaining a parameter combination with a constant parameter estimated value and an uncertain part by using the constant parameters α, gamma, wherein the parameter combination comprises the following steps:wherein,is an estimated value of the constant parameter, Δ α, Δ ξ, Δ γ is an uncertain value of the constant parameter;
and a sixth step: bringing the model of the inertial system of the fourth step and the parameter combination of the fifth step into the model of the third stepIn the step of obtaining step1, obtaining parameters including a fan modelInputting an uncertain fan model into the uncertain and variable pitch actuating mechanism; the fan model specifically comprises:
wherein,and the constant parameter uncertain part and the actuator uncertain part represent the fan model.
2. The sliding-mode adaptive control method according to claim 1, wherein the obtaining step of the sliding-mode adaptive controller of the wind turbine in step2 is as follows:
step 1: taking the rotating speed error and the derivative of the error of the fan, and designing a nonsingular terminal sliding mode surface:wherein p is more than q and more than 0, and p and q are sliding mode surface design parameters and are odd numbers; e ═ Δ ω ═ ω - ωoIs the deviation of the fan rotating speed and the fan rated rotating speed, s is a nonsingular terminal sliding mode surface, c represents a coefficient, βcInputting a pitch angle;
step 2: designing an upper bound of an uncertain part of a required model by the fan sliding mode adaptive controller; the upper bound being denoted by a, i.e.
Step 3: in the design process of the fan sliding mode adaptive controller, the parameters of the fan sliding mode adaptive controllerRepresenting the estimated value of a to further obtain an adaptive parameter model; the adaptive parameter model is as follows:
βc＝βceq+βcn
wherein the controller parameterEstimate of a, βceqFor equivalent control, βcnFor switching control, η and k are both constants greater than zero.
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| CN107975457B (en) * | 2017-11-17 | 2019-12-31 | 重庆邮电大学 | Wind turbine generator variable pitch control method for inhibiting wind speed fluctuation interference |
| CN108678902B (en) * | 2018-05-02 | 2019-08-27 | 曾喆昭 | The straight disturbance sensing control method for driving PMSM wind generator system MPPT |
| CN109149617A (en) * | 2018-08-29 | 2019-01-04 | 河海大学 | A kind of D.C. high voltage transmission design method based on global quickly Terminal sliding formwork control |
| CN110032238B (en) * | 2019-04-28 | 2020-06-12 | 闽江学院 | Maximum power tracking method for wind turbine power generation yaw control system |
| CN110566406B (en) * | 2019-10-16 | 2020-08-04 | 上海海事大学 | Wind turbine generator set real-time variable pitch robust control system and method based on reinforcement learning |
| CN114355762B (en) * | 2021-12-30 | 2023-09-26 | 上海电机学院 | Pitch control method based on nonsingular rapid terminal sliding mode |
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