A photoelectric pod control method and device based on crowd self-interference resistance

Abstract

The present invention provides a method and device for controlling an optoelectronic pod based on crowd self-disturbance rejection, including: establishing an optoelectronic pod dynamics model based on a tethered balloon system; theoretically modeling each actuator of the control system of the tethered balloon system to establish a speed stability loop control model; establishing an anti-disturbance rejection controller model based on the optoelectronic pod dynamics model and the speed stability loop control model; optimizing the parameters of the anti-disturbance rejection controller model using a crowd search algorithm to determine the optimal anti-disturbance rejection controller model. The present invention aims at the problem that the tethered balloon system, as a weakly controlled aircraft, is greatly disturbed by the wind field and has poor state stability, which affects the stable imaging of the optoelectronic pod. The crowd search algorithm is used to optimize the anti-disturbance rejection controller, which can effectively isolate the internal and external disturbances of the optoelectronic pod and improve the imaging stability of the optoelectronic pod. It has important significance in the application of tethered balloons and other aerostats in the fields of long-term airborne, ground observation, surveillance and monitoring.

Description

Technical Field

[0001] The present invention relates to the field of aircraft control technology, and in particular to a photoelectric pod control method and device based on crowd self-anti-disturbance. Background Art

[0002] Tethered balloons have the advantages of being able to stay in the air for a long time and having a large payload. After being equipped with an optoelectronic mission payload system, they can carry out different applications such as surveillance, ground reconnaissance, and remote sensing observation. Faced with the increasingly urgent application needs of border defense, coastal defense, and scientific exploration, the use of tethered balloon optoelectronic pod systems to carry out regional fine monitoring has received more and more attention, and will play a huge role in the future in the fields of national economy, scientific research, and national defense.

[0003] At present, a variety of control methods have been proposed for the stability control of optoelectronic pods, such as PID control, variable structure control, anti-disturbance control, intelligent control, robust control and other algorithms. Existing optoelectronic pod control methods are mostly applied to airborne, vehicle-mounted, ground-based and other platform forms, and the research and development of optoelectronic pods specifically for tethered balloons and other aerostat platforms is basically blank.

[0004] At present, the electro-optical pod stability control based on the tethered balloon platform faces many limitations, which are mainly reflected in the following aspects:

[0005] 1) Due to the structure of the tethered balloon itself, the balloon is easily affected by changes in wind direction and wind force when it is in the air, and will sway randomly in the three directions of roll, pitch and yaw. It is difficult to control the attitude of the tethered balloon, and the visual axis direction of the sensor in the optoelectronic pod often changes randomly.

[0006] 2) Limited by the influence of wind, when the wind direction changes too quickly, the tethered balloon platform is disturbed and rotates. In order to ensure effective tracking, the motor needs to be started and stopped frequently to control the direction of the photoelectric sensor. The friction torque and wind resistance torque change greatly. It is difficult to ensure high stability while ensuring rapidity.

[0007] 3) Due to the limitation of the rotation speed of the optoelectronic pod’s own rotation axis, when the wind direction changes quickly, the tethered balloon platform may rotate at a speed that exceeds the rotation speed of the optoelectronic pod’s own rotation axis, making it easy to “lose” the tracking target and difficult to achieve stable tracking. Summary of the invention

[0008] The present invention provides a photoelectric pod control method and system based on crowd self-anti-disturbance, which are used to fill the gap in the prior art in the photoelectric pod stability control based on a tethered balloon platform.

[0009] In a first aspect, the present invention provides a photoelectric pod control method based on crowd self-interference rejection, comprising:

[0010] Establish the dynamic model of optoelectronic pod based on tethered balloon system;

[0011] Conduct theoretical modeling on each actuator of the control system of the tethered balloon system and establish a speed stabilization loop control model;

[0012] Based on the electro-optical pod dynamics model and the speed stabilization loop control model, an active disturbance rejection controller model is established;

[0013] A crowd search algorithm is used to optimize the parameters of the active disturbance rejection controller model to determine the optimal active disturbance rejection controller model, so as to implement stable control of the optoelectronic pod using the optimal active disturbance rejection controller model.

[0014] According to a method for controlling an optoelectronic pod based on crowd self-anti-disturbance, the optoelectronic pod dynamics model is composed of a transient motion equation of a tethered balloon, boundary conditions of an anchor point, boundary conditions of a main node, a steady-state motion equation of a tethered balloon, and a differentially coupled dynamics equation of a tether.

[0015] According to a photoelectric pod control method based on crowd self-interference rejection provided by the present invention, the expression of the transient motion equation of the tethered balloon is:

[0016]

[0017] The boundary condition of the anchor point is expressed as:

[0018] [V x0 V y0 V z0 ] T =(L ce ) T [V t0 V n0 V b0 ] T ;

[0019] The expression of the master node boundary condition is:

[0020] L ce [V tN V nN V bN ] T =V B +ω×R B ;

[0021] The expression of the steady-state motion equation of the tethered balloon is:

[0022]

[0023] Assume that the dynamic equation of the mooring cable is expressed as:

[0024]

[0025] Then the differential coupled dynamic equation of the mooring cable is expressed as:

[0026]

[0027]

[0028] Among them, M1 is the mass matrix, M and N are intermediate result matrices, q is the force matrix, and Y is the mooring state matrix: [TV t V n V b βγ] T , β is the inclination angle of the mooring cable, γ is the azimuth angle of the mooring cable, V n 、V b 、V t are the components of the mooring cable velocity in CFS; τ RB is the projection of the sum of the inertial force and aerodynamic force of the tether in the body axis system BFS of the tethered balloon; V is the velocity of the tethered balloon in the BFS; is the derivative of V; C RB is the rotational torque; [V t0 V n0 V b0 ] T is the velocity of the mooring cable in the mooring cable local coordinate system CFS; L ce is the coordinate transformation matrix between the ground coordinate system EFS where the anchor point is located and the CFS; [V x0 V y0 V z0 ] T is the speed of the anchor point in the EFS; [V tN V nN V bN ] T is the speed of the Nth node in the CFS; R B V is the vector of the master node B in the BFS; B is the speed of the master node B in the BFS; ω is the motor angular velocity of the optoelectronic pod rotation axis; [p, q, r] are the rotation angular velocities of the tethered balloon in the BFS; ψ, θ, φ are the yaw angle, pitch angle and roll angle of the tethered balloon respectively; are the corresponding values ​​at time i and position j respectively; ΔS is the mooring micro-segment; Δt is the time micro-segment.

[0029] According to a method for controlling an optoelectronic pod based on crowd self-disturbance rejection provided by the present invention, the speed stabilization loop control model includes a motor transfer function of the optoelectronic pod rotating shaft, a transfer function of a speed gyroscope, and a transfer function of a power amplifier.

[0030] According to a photoelectric pod control method based on crowd self-disturbance rejection provided by the present invention, the expression of the motor transfer function is:

[0031]

[0032] The transfer function of the velocity gyro is expressed as:

[0033] G”(s)=G g (s);

[0034] The transfer function of the power amplifier is expressed as:

[0035] G”'(s)=K pwm ;

[0036] Wherein, G'(s), G"(s) and G"'(s) are the transfer function of the motor, the transfer function of the speed gyro and the transfer function of the power amplifier respectively; L a is the armature winding inductance; J is the total moment of inertia on the motor shaft; C m is the motor torque coefficient, C e is the electromotive force coefficient of the motor; R a is the armature winding resistance; w(s) is the Laplace transform of the output angular velocity, U a (s) is the Laplace transform of the input; G g (s) is the proportional link of the speed gyro; K pwm It is the proportional amplification link of the power amplifier.

[0037] According to a method for controlling an optoelectronic pod based on crowd self-disturbance rejection provided by the present invention, the expression of the self-disturbance rejection controller model is:

[0038]

[0039]

[0040]

[0041]

[0042] u(k)=u0(k)-z3(k) / b0;

[0043]

[0044]

[0045] in, is the differential equation of the optoelectronic pod control system; TD is the tracking differentiator; ESO is the extended state observer; NLSEF is the nonlinear state error feedback; is the total disturbance; v(k) is the system input signal; y is the output signal; w(k) is the external total disturbance; the differential signal v1(k) and the differential signal v2(k) are transformed by TD from v(k); z1(k), z2(k) and z3(k) represent v1(k), v2(k) and the total disturbance respectively. The estimator of; r, h, h0 are parameters in TD; r value is the fast factor; h is the system sampling step; h0 is a dimensionless parameter, which is an integer multiple of h; h, β 01 ,β 02 ,β 03 ,δ,b are the parameters in ESO; β 01 ,β 02 ,β 03 is a coefficient parameter related to h; δ is a meaningless coefficient, which is an integer multiple of h; the control quantity coefficient b is a time-varying function, which is approximately a constant b0; c, r1, h1 are parameters in NLSEF; c is the damping factor, h1 is the fast factor, and r1 is the control quantity factor; fhan and fal are expressions of nonlinear functions respectively; u is the controlled object; u is the controlled object; u0(t) is the error feedback control quantity; a, a0, a1 and a2 are dimensionless intermediate parameters.

[0046] According to a method for controlling an optoelectronic pod based on crowd self-disturbance rejection provided by the present invention, the parameters to be optimized of the self-disturbance rejection controller model include parameters β 01 ,β 02 ,β 03 ,c,h1;

[0047] The method of optimizing the parameters of the active disturbance rejection controller model by using a crowd search algorithm includes:

[0048] Step 1: t = 0, initialize the crowd search algorithm, set the spatial dimension, system sampling step, crowd size, maximum number of iterations N, minimum fitness value and the range of the crowd search space, and randomly generate multiple initial individuals in the feasible solution domain; each of the initial individuals is a combination of the parameters to be optimized;

[0049] Step 2: Calculate the fitness value of each individual;

[0050] Step 3: Calculate the search direction and step length of each individual in each dimension;

[0051] Step 4: Based on the search direction and step length, the position of each individual is updated to re-determine the fitness value of each individual;

[0052] Step 5: Let t=t+1 and determine whether the stopping condition is met; if so, output the optimal parameter combination; if not, return to step 2.

[0053] In a second aspect, the present invention further provides an optoelectronic pod control device based on crowd self-interference resistance, comprising:

[0054] A first processing unit is used to establish a dynamic model of an optoelectronic pod based on a tethered balloon system;

[0055] A second processing unit is used to perform theoretical modeling on each actuator of the control system of the tethered balloon system and establish a speed stabilization loop control model;

[0056] A third processing unit is used to establish an active disturbance rejection controller model based on the optoelectronic pod dynamics model and the speed stabilization loop control model;

[0057] The fourth processing unit is used to optimize the parameters of the active disturbance rejection controller model by using a crowd search algorithm to determine the optimal active disturbance rejection controller model, so as to implement stable control of the optoelectronic pod by using the optimal active disturbance rejection controller model.

[0058] In a third aspect, the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the optoelectronic pod control method based on crowd self-anti-interference are implemented as described in any one of the above-mentioned methods.

[0059] In a fourth aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the above-described methods for controlling an optoelectronic pod based on crowd self-anti-disturbance.

[0060] The optoelectronic pod control method and device based on crowd anti-disturbance provided by the present invention aims at the problem that the tethered balloon system, as a weakly controlled aircraft, is greatly disturbed by the wind field and has poor state stability, which affects the stable imaging of the optoelectronic pod. The crowd search algorithm is used to optimize the anti-disturbance controller, which can effectively isolate the internal and external disturbances of the optoelectronic pod and improve the imaging stability of the optoelectronic pod. It is of great significance in the application of tethered balloons and other airborne vehicles in the fields of long-term airborne stay, ground observation, surveillance and monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0062] Figure 1 It is a flow chart of the photoelectric pod control method based on crowd self-anti-disturbance provided by the present invention;

[0063] Figure 2 It is a schematic diagram of the tethered balloon coordinate system provided by the present invention;

[0064] Figure 3 It is a schematic diagram of the control principle of a single-axis motor provided by the present invention;

[0065] Figure 4 It is a control structure schematic diagram of the speed stabilization loop provided by the present invention;

[0066] Figure 5 It is a schematic diagram of a control model of a speed stabilization loop provided by the present invention;

[0067] Figure 6 Schematic diagram of the second-order active disturbance rejection controller provided by the present invention;

[0068] Figure 7 It is a schematic diagram of the principle of optimizing the parameters of the automatic disturbance rejection controller by the crowd search algorithm provided by the present invention;

[0069] Figure 8 It is a flow chart of the crowd search algorithm provided by the present invention.

[0070] Fig. 9 It is a structural schematic diagram of the photoelectric pod control device based on crowd self-interference resistance provided by the present invention;

[0071] Fig.10 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0072] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0073] For the difficult problems existing in the stable control of the above-mentioned ball-borne optoelectronic pod, it is necessary to overcome the random influence of wind on the tethered balloon platform, and to improve the anti-interference ability of the optoelectronic pod while ensuring the rapid response of the optoelectronic pod, that is, to improve the stability of the optoelectronic pod. This is the key technical problem that needs to be solved at present.

[0074] The core idea of ​​Active Disturbance Rejection Control (ADRC) is "active disturbance rejection". Through the extended state observer, the external disturbance of the system and the uncertainty of the system model can be estimated as a comprehensive disturbance term, so that direct feedforward compensation control of the disturbance can be achieved to eliminate its influence. This method does not require accurate modeling of the controlled object and physical measurement of the disturbance term. It has the characteristics of fast response speed, high accuracy, strong disturbance suppression ability and simple algorithm.

[0075] In the ADRC model, there are 12 parameters to be determined. Through the understanding of the model and empirical value selection, there are still 5 parameters that need to be determined. However, it is difficult to make these 5 parameters cooperate with each other to achieve the optimal control effect by relying solely on empirical values. Therefore, a new optimization algorithm is needed to find a corresponding set of parameter values.

[0076] The crowd search algorithm (SOA) is a new type of swarm intelligence algorithm. By analyzing people's random search behavior, with the help of research results in brain science, cognitive science, multi-agent systems and swarm intelligence, it uses people's selfish behavior, altruistic behavior and pre-action behavior to determine the individual's search direction, so as to find the optimal solution. It is widely used in PID controller parameter optimization. The present invention creatively uses it for automatic disturbance rejection controller parameter optimization, solves the defect that the ADRC model cannot adjust parameters adaptively in real time, effectively isolates the internal and external disturbances of the optoelectronic pod, improves the imaging stability of the optoelectronic pod, and greatly improves the system's anti-disturbance and robustness.

[0077] Combine the following Figure 1-Figure 10 The present invention describes an optoelectronic pod control method and device based on crowd self-interference rejection provided by an embodiment of the present invention.

[0078] Figure 1 is a flow chart of the photoelectric pod control method based on crowd self-interference resistance provided by the present invention, such as Figure 1 As shown, including but not limited to the following steps:

[0079] Step 101: Establish a dynamic model of an optoelectronic pod based on a tethered balloon system.

[0080] Specifically, the present invention mainly establishes a photoelectric pod dynamics model based on a tethered balloon system according to the photoelectric detection mission requirements of the tethered balloon system. Since the tethered balloon system connects the sphere of the tethered balloon and the photoelectric pod approximately as a rigid body, the motion of the photoelectric pod is basically consistent with the motion of the sphere of the tethered balloon, and the motion of the tethered balloon system is the coupling of the motion of the cable and the motion of the sphere of the tethered balloon, the photoelectric pod dynamics model is composed of the tether cable dynamics equation and the tethered balloon sphere motion equation as well as initial conditions and boundary conditions.

[0081] As an optional embodiment, the optoelectronic pod dynamic model is composed of the transient motion equation of the tethered balloon, the boundary conditions of the anchor point, the main node boundary conditions, the steady-state motion equation of the tethered balloon and the dynamic equation of the tether.

[0082] Figure 2 Schematic diagram of the tethered balloon coordinate system provided by the present invention. Figure 2 As shown in the figure, the ground coordinate system EFS where the anchor point is located, the body axis system BFS of the tethered balloon and the local coordinate system CFS of the tether are pre-built. The coordinate transformation matrix between EFS and BFS is denoted as L be , the coordinate transformation matrix between EFS and CFS is recorded as L ce , the azimuth and inclination angles of the tether are γ and β respectively, and the yaw, pitch and roll angles of the tethered balloon are ψ, θ and φ respectively.

[0083] After determining the coordinate system, the transient motion equation of the mooring cable can be obtained, which is expressed as:

[0084]

[0085] Among them, the expressions of the intermediate result matrices M, N and the force matrix q are:

[0086]

[0087]

[0088]

[0089] In the above formula, M is the intermediate result matrix, N is the intermediate result matrix, q is the force matrix; Y is the mooring state matrix: [TV t V n V b β γ] T , β is the inclination angle of the mooring cable, γ is the azimuth angle of the mooring cable, V n 、V b 、V t are the components of the mooring cable velocity in CFS; F t ,Fn ,F b are the components of the sum of the inertial force and aerodynamic force of the mooring cable in CFS; m is the mass of the mooring cable, ρ is the air density, u is the airspeed of the mooring cable; J t ,J n ,J b are the components of wind speed J in CFS; e = 1 / EA, E is the elastic modulus of the mooring cable, A is the area of ​​the mooring cable before deformation; T is the tension on the mooring cable; W is gravity; V n 、V b 、V t are the components of the mooring cable velocity in CFS; Y is [TV t V n V b β γ] T .

[0090] Based on the above, the expression of the transient motion equation of the tethered balloon is:

[0091]

[0092]

[0093] Among them, M1 is the mass matrix, where m is the mass of the sphere and the moment of inertia I xx ,I yy ,I zz and product of inertia I zx is the value corresponding to the center of gravity of the sphere in the body axis system BFS of the tethered balloon; τ RB is the projection of the sum of the inertial force and aerodynamic force of the tether in the body axis system BFS of the tethered balloon; V is the velocity of the tethered balloon in BFS; is the derivative of V, which represents the acceleration of the tethered balloon; C RB is the rotational torque.

[0094] The initial conditions of the transient motion equation of the tethered balloon mentioned above can be the mooring cable tension in the steady state, the inclination angle and azimuth angle of the cable, and the yaw angle, pitch angle and roll angle of the sphere.

[0095] Furthermore, the boundary condition of the anchor point can be expressed as:

[0096] [V x0 V y0 V z0 ] T =(L ce ) T [V t0 V n0 V b0 ] T (2)

[0097] Among them, [V t0 V n0 V b0 ] T is the velocity of the mooring cable in the local coordinate system CFS; [V x0 V y0 V z0 ] T is the velocity of the anchor point in the ground coordinate system EFS; L ce It is the coordinate transformation matrix between EFS and CFS.

[0098] Furthermore, the main node refers to the main connection point between the tether and the sphere of the tethered balloon. The boundary condition of the main node satisfies the velocity continuity condition and can be determined as:

[0099] L ce [V tN V nN V bN ] T =V B +ω×R B (3)

[0100] Among them, the mooring line is divided into N sections from the anchor point to the main node, then n represents the nth node, [V tN V nN V bN ] T is the speed of the Nth node in CFS; R B V is the vector of the main point B in BFS; B is the speed of node B in BFS; ω is the motor angular velocity of the optoelectronic pod's rotation axis.

[0101] Furthermore, the expression of the steady-state motion equation of the sphere can be:

[0102]

[0103] Wherein, [p, q, r] are the rotational angular velocities of the tethered balloon in the BFS; ψ, θ, φ are the yaw angle, pitch angle and roll angle of the tethered balloon respectively.

[0104] Finally, by establishing the coupling equation based on the difference method, the dynamic equation of the mooring cable can be obtained, which can be expressed as:

[0105]

[0106]

[0107] in, are the values ​​corresponding to position j at time i; ΔS is the mooring micro-segment; Δt is the time micro-segment.

[0108] By combining the above formulas (1) to (5), the optoelectronic pod dynamics model can be established. By solving the optoelectronic pod dynamics model, relevant parameters such as the tether speed, the tethered balloon speed, and the inclination angle can be determined, and the working status of the optoelectronic pod can be further analyzed.

[0109] Step 102: Conduct theoretical modeling on each actuator of the control system of the tethered balloon system to establish a speed stabilization loop control model.

[0110] Specifically, the speed stabilization loop control model constructed by the present invention mainly includes but is not limited to: the motor transfer function of the optoelectronic pod rotating shaft, the transfer function of the speed gyroscope and the transfer function of the power amplifier.

[0111] Since each axis of the photoelectric pod is controlled by a motor, the control principle and control method are the same, and the motor generally uses a DC torque motor. To control the direction of the photoelectric sensor, the motor of each axis needs to rotate a certain angle.

[0112] The stability of the photoelectric pod's stability control system is essentially to ensure that the photoelectric pod controls the rotation of each axis motor to compensate in real time in the case of internal and external disturbances, so as to reduce or eliminate interference, so that the pointing direction of the photoelectric sensor can remain stable without jitter and deviation.

[0113] Figure 3 Schematic diagram of the control principle of a single-axis motor provided by the present invention. Figure 3 As shown, the control of each axis motor is usually composed of three closed-loop control loops: position loop, speed loop and current loop, which correspond to the position controller, speed controller and current controller.

[0114] Among them, the current loop is the innermost loop, which controls the motor to output a stable torque so that the current is not easy to fluctuate and produce mutations; the speed loop is the middle loop, which can suppress the interference of the load and the friction torque inside the optoelectronic pod, and achieve stable sensor pointing, rapid response, and fast reaction; and the position loop is the outermost loop, which mainly measures and feeds back the position signal, so that the sensor pointing changes with the movement of the target, but the position loop can only isolate lower-frequency disturbances.

[0115] Figure 4 Schematic diagram of the control structure of the speed stabilization loop provided by the present invention. Figure 4 As shown, the key to achieving stable control of the optoelectronic pod is to design and control the speed loop, which is less affected by the current loop and position loop.

[0116] In view of this, the optoelectronic pod control method based on crowd self-interference rejection provided by the present invention, according to the control principle of a single-axis motor, comprehensively considers the internal and external interference factors that affect the speed, theoretically models each actuator of the control system of the tethered balloon system, determines the motor transfer function of the optoelectronic pod rotating shaft, the transfer function of the speed gyroscope and the transfer function of the power amplifier, and determines the speed stabilization loop control model.

[0117] The various actuators of the control system of the tethered balloon system mainly include: DC torque motor and load (mainly including the rotating shaft of the optoelectronic pod and other components connected to the rotating shaft), PWM power amplifier, speed gyroscope, etc.

[0118] Alternatively, the expression for the motor transfer function is:

[0119]

[0120] Among them, L a is the armature winding inductance; J is the total moment of inertia on the motor shaft; C m is the motor torque coefficient, C e is the electromotive force coefficient of the motor; R a is the armature winding resistance; w(s) is the Laplace transform of the output angular velocity, U a (s) is the Laplace transform of the input quantity.

[0121] Furthermore, when the bandwidth of the speed gyro is wide, the mathematical model of the speed gyro can be regarded as a proportional link:

[0122] G”(s)=G g (s) = k g (7)

[0123] Furthermore, the mathematical model of the power amplifier can be simplified to the proportional amplification link:

[0124] G”'(s)=K pwm (8)

[0125] Figure 5 Schematic diagram of the control model of the speed stabilization loop provided by the present invention, such as Figure 5 As shown, by combining the above formulas (6) to (8), a speed stabilization loop control model can be constructed.

[0126] Step 103: Establish an active disturbance rejection controller model based on the optoelectronic pod dynamics model and the speed stabilization loop control model.

[0127] The active disturbance rejection controller is mainly composed of three parts: tracking differentiator TD, nonlinear state error feedback control law NLSEF and extended state observer ESO. The differential equation of the control system of the optoelectronic pod can be expressed by a conventional second-order differential equation, which is:

[0128]

[0129] Where w(t) is the total external disturbance; It includes internal disturbances (such as friction torque, gyro noise), and external disturbances (such as the movement of the tethered balloon); u is the controlled object (the controlled object is Figure 3 The entire content shown mainly includes the input of motor load); b is the control quantity coefficient, which can be taken as a constant b0.

[0130] Figure 6 is a schematic diagram of a second-order active disturbance rejection controller provided by the present invention, such as Figure 6 As shown, v(t) is the system input signal, which is equivalent to the angular velocity signal required to be output by the motor.

[0131] The differential tracker converts the system input signal v(t) into the equivalent differential signal v1(t) and differential signal v2(t) (see the differential tracker expression). e1(t) and e2(t) are combined nonlinearly to obtain u0(t). z1(t), z2(t) and z3(t) represent v1(t), v2(t) and the total disturbance, respectively. The estimated amount.

[0132] When designing ADRC and optimizing parameters, the algorithm needs to be discretized, which can be expressed as:

[0133]

[0134]

[0135]

[0136] u(k)=u0(k)-z3(k) / b0 (13)

[0137] The expressions of the two nonlinear functions fhan and fal (which are expressions of nonlinear functions, similar to the linear combination in PID control, are both feedback control rates) are:

[0138]

[0139]

[0140] In addition, the ADRC also has a disturbance compensation process, which can be expressed as:

[0141] Combining the above formulas (9) to (15), the ADRC model is established. The entire model has 12 parameters, r, h, h0 in TD, h, β in ESO. 01 ,β 02 ,β 03 ,δ,b; there are c,r1,h1 in NLSEF.

[0142] Among them, r value is the fast factor, the larger the value, the faster the response; h is the system sampling step; h0 is a parameter, which has no physical meaning and can generally be an integer multiple of h; δ is a meaningless coefficient, which can also be an integer multiple of h; the control quantity coefficient b is a time-varying function and can be approximated as a constant b0; β 01 ,β 02 ,β 03 It is related to the system sampling step h, has no physical meaning, and is only a coefficient parameter; parameter c is the damping factor; h1 is the fast factor; r1 is the control amount factor. Therefore, it can be determined that the following five parameters need to be optimized: β 01 ,β 02 ,β 03 ,c,h1.

[0143] Step 104: A crowd search algorithm is used to optimize the parameters of the active disturbance rejection controller model to determine an optimal active disturbance rejection controller model, so as to implement stable control of the optoelectronic pod using the optimal active disturbance rejection controller model.

[0144] Figure 7 Schematic diagram of the principle of optimizing the parameters of the ADRC by the crowd search algorithm provided by the present invention. Figure 7 As shown, the present invention adopts a crowd search algorithm to face the above five parameters: β 01 ,β 02 ,β 03 ,c,h1 are optimized to obtain the optimal ADRC model.

[0145] Figure 8 is a flow chart of the crowd search algorithm provided by the present invention, such as Figure 8 As shown, in this embodiment, how to establish the ADRC model is not described in detail. It only introduces how to use the crowd search algorithm to optimize parameters after obtaining the ADRC model. The specific steps include but are not limited to:

[0146] Step 1: t = 0, initialize the crowd search algorithm, set the spatial dimension, system sampling step, crowd size, maximum number of iterations N, minimum fitness value and the range of the crowd search space, and randomly generate multiple initial individuals in the feasible solution domain; each of the initial individuals is a combination of the parameters to be optimized;

[0147] Step 2: Calculate the fitness value of each individual;

[0148] Step 3: Calculate the search direction and step length of each individual in each dimension;

[0149] Step 4: Based on the search direction and step length, the position of each individual is updated to re-determine the fitness value of each individual;

[0150] Step 5: Let t=t+1 and determine whether the stopping condition is met; if so, output the optimal parameter combination; if not, return to step 2.

[0151] The specific implementation of step one may include:

[0152] At the beginning of parameter optimization, i.e., at t=0, the crowd search algorithm is initialized and s initial positions are randomly generated in the feasible solution domain.

[0153] The crowd search algorithm uses Gaussian membership function to represent the fuzzy variable of the search step length based on the understanding of people's random search behavior. Its expression is:

[0154] u A (x) = exp[-(xu) 2 / 2d 2 ] (16)

[0155] Among them, u A is the Gaussian membership; x is the input variable; u and δ are the membership function parameters. The minimum membership value can be set to u min =0.0111, the maximum membership value is u max =0.95.

[0156] In addition, it is necessary to set the spatial dimension D to 5 dimensions, the system sampling step h, the crowd size s, the maximum number of iterations N, the minimum fitness value and the range of the crowd search space, etc.

[0157] Then, s initial positions are randomly generated within the space range to generate individual extreme values ​​p i,best and the global extremum g i,best .

[0158] Among them, the individual extreme value is the value of the objective function obtained by the population in the best position; the global extreme value is the smallest value among the individual extreme values ​​of all populations, and the corresponding value is the position of the global optimal population.

[0159] The specific implementation of evaluating the positions of each group of parameters proposed in step 2 and calculating the fitness value of each position may include:

[0160] At the end of each iterative cycle of crowd search, the fitness value fit[t] is calculated and compared.

[0161] The fitness function determines the direction of each individual solution, so that each group of parameters evolves towards the optimal solution. The present invention comprehensively considers the rapidity of response, overshoot and control energy, and adopts the following fitness function:

[0162]

[0163] Among them, e(t) is the deviation between the given value and the output; Δe(t) is the difference between two adjacent step outputs; c1 is the weight of the deviation in the fitness function, c2 is the weight of the square term of the control amount in the fitness function, which can be c1 = 0.02, c2 = 0.98. u(t) is the control amount; Q refers to the objective function value (that is, the fitness value).

[0164] Furthermore, the specific implementation method of calculating the search direction and step length of each position in each dimension proposed in step 3 may include:

[0165] Sort the objective function values ​​in descending order, use a linear membership function to make the membership proportional to the function value, and increase the randomness of the search:

[0166]

[0167] u ij =rand(u i ,1),j=1,2,…,D (18)

[0168] Among them, I i is the population function value after it is arranged in descending order x i (t) sequence number; u i is the membership of the objective function value i, and the maximum membership is set to u max 0.9500, minimum u min is 0.0111; u ij for dimensional search space; D is the dimension of the search space.

[0169] According to the behavior part of uncertain reasoning, the step length can be obtained, which is expressed as:

[0170]

[0171] Among them, α ij is the search step length of the j-dimensional search space; δ ij is the Gaussian membership function parameter, and its value can be determined by the following formula:

[0172]

[0173] Among them, x min and xmax are the positions with the minimum and maximum function values ​​in the same subgroup, respectively; t and T are the current iteration number and the maximum iteration number, respectively.

[0174] Then, the selfish direction of the i-th search individual is calculated separately Altruistic Direction And the pre-movement direction The search direction is determined by randomly weighted geometric averaging of three directions:

[0175]

[0176] where t1,t2∈{t,t-1,t-2}, and They are The best position in g i,best is the collective best historical position of the neighborhood of the i-th search individual, p i, b est is the best position that the i-th search individual has experienced so far; and is a real number selected uniformly at random in the known interval [0,1]; ω is the inertia weight, which decreases linearly from 0.9 to 0.1 as the number of iterations increases.

[0177] Furthermore, the above step 4 proposes to update the position of each individual based on the search direction and step length, specifically including:

[0178] After determining the search direction and step size α ij After that, the position is updated according to the following formula:

[0179] Δx ij (t+1)=α ij (t)d ij (t);

[0180] x ij (t+1)=x ij (t)+Δx ij (t+1) (22)

[0181] After the position is updated, if it exceeds the maximum range space or the minimum range space, the individual position must be changed to the maximum or minimum value of the range space.

[0182] Finally, for the individual extreme value p i,best and the global extremum g i,best Update: use its fitness value fit[t] and individual extreme value p i,best Compare:

[0183] If fit[t]<p i,best, then replace p with fit[t] i,best For each individual, use its fitness value fit[t] and the global extreme value g i,best Compare. If fit[t]<g i,best , then replace g with fit[t] i,best .

[0184] Furthermore, in step five, it is determined whether the stopping condition is met. If so, the algorithm is terminated and the optimization result is output; otherwise, it returns to step two.

[0185] The stopping condition may be that the maximum number of cycles is reached or the fitness value is less than the minimum fitness value.

[0186] The optoelectronic pod control method based on crowd anti-disturbance provided by the present invention aims at the problem that the tethered balloon system, as a weakly controlled aircraft, is greatly disturbed by the wind field and has poor state stability, which affects the stable imaging of the optoelectronic pod. The crowd search algorithm is used to optimize the anti-disturbance controller, which can effectively isolate the internal and external disturbances of the optoelectronic pod and improve the imaging stability of the optoelectronic pod. It is of great significance in the application of tethered balloons and other aerostats in the fields of long-term airborne stay, ground observation, surveillance and monitoring.

[0187] Fig. 9 Schematic diagram of the structure of the photoelectric pod control device based on crowd self-interference resistance provided by the present invention, such as Fig. 9 As shown, it mainly includes a first processing unit 901, a second processing unit 902, a third processing unit 903 and a fourth processing unit 904, wherein:

[0188] The first processing unit 901 is mainly used to establish a dynamic model of an optoelectronic pod based on a tethered balloon system; the second processing unit 902 is mainly used to perform theoretical modeling on various actuators of the control system of the tethered balloon system, and to establish a speed stabilization loop control model; the third processing unit 903 is mainly used to establish an auto-disturbance rejection controller model based on the optoelectronic pod dynamic model and the speed stabilization loop control model; the fourth processing unit 904 is mainly used to optimize the parameters of the auto-disturbance rejection controller model by using a crowd search algorithm, and to determine the optimal auto-disturbance rejection controller model, so as to implement stable control of the optoelectronic pod using the optimal auto-disturbance rejection controller model.

[0189] It should be noted that the optoelectronic pod control device based on crowd self-interference rejection provided in the embodiment of the present invention can execute the optoelectronic pod control method based on crowd self-interference rejection described in any of the above embodiments during specific operation, which will not be elaborated in this embodiment.

[0190] The optoelectronic pod control device based on crowd anti-disturbance is provided by the present invention. Aiming at the problem that the tethered balloon system, as a weakly controlled aircraft, is greatly disturbed by the wind field and has poor state stability, which affects the stable imaging of the optoelectronic pod, the optoelectronic pod can be effectively isolated from the internal and external disturbances of the optoelectronic pod and the imaging stability of the optoelectronic pod. The device has important application in the fields of long-term airborne stay of tethered balloons and other airships, ground observation, surveillance and monitoring.

[0191] Fig.10 is a schematic diagram of the structure of the electronic device provided by the present invention, such as Fig.10 As shown, the electronic device may include: a processor 110, a communication interface 120, a memory 130 and a communication bus 140, wherein the processor 110, the communication interface 120 and the memory 130 communicate with each other through the communication bus 140. The processor 110 may call the logic instructions in the memory 130 to execute the photoelectric pod control method based on crowd self-disturbance rejection, the method comprising: establishing a photoelectric pod dynamics model based on a tethered balloon system; theoretically modeling each actuator of the control system of the tethered balloon system to establish a speed stabilization loop control model; establishing a self-disturbance rejection controller model based on the photoelectric pod dynamics model and the speed stabilization loop control model; using a crowd search algorithm to optimize the parameters of the self-disturbance rejection controller model to determine the optimal self-disturbance rejection controller model, so as to implement the stable control of the photoelectric pod using the optimal self-disturbance rejection controller model.

[0192] In addition, the logic instructions in the above-mentioned memory 130 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program code.

[0193] On the other hand, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by the computer, the computer can execute the optoelectronic pod control method based on crowd self-disturbance rejection provided by the above methods, and the method includes: establishing an optoelectronic pod dynamic model based on a tethered balloon system; theoretically modeling each actuator of the control system of the tethered balloon system to establish a speed stabilization loop control model; establishing an anti-disturbance rejection controller model based on the optoelectronic pod dynamic model and the speed stabilization loop control model; using a crowd search algorithm to optimize the parameters of the anti-disturbance rejection controller model to determine the optimal anti-disturbance rejection controller model, so as to use the optimal anti-disturbance rejection controller model to implement stable control of the optoelectronic pod.

[0194] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the optoelectronic pod control method based on crowd anti-disturbance provided in the above-mentioned embodiments, the method comprising: establishing an optoelectronic pod dynamics model based on a tethered balloon system; theoretically modeling each actuator of the control system of the tethered balloon system to establish a speed stabilization loop control model; establishing an anti-disturbance controller model based on the optoelectronic pod dynamics model and the speed stabilization loop control model; and optimizing the parameters of the anti-disturbance controller model using a crowd search algorithm to determine the optimal anti-disturbance controller model, so as to implement stable control of the optoelectronic pod using the optimal anti-disturbance controller model.

[0195] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0196] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0197] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A photoelectric pod control method based on crowd self-interference rejection, characterized in that: include: Establish the dynamic model of optoelectronic pod based on tethered balloon system; Conduct theoretical modeling on each actuator of the control system of the tethered balloon system and establish a speed stabilization loop control model; Based on the electro-optical pod dynamics model and the speed stabilization loop control model, an active disturbance rejection controller model is established; A crowd search algorithm is used to optimize the parameters of the active disturbance rejection controller model to determine the optimal active disturbance rejection controller model, so as to implement stable control of the optoelectronic pod using the optimal active disturbance rejection controller model; The expression of the active disturbance rejection controller model is: ； ； ； ； ； ； ； in, is the differential equation of the optoelectronic pod control system; TD is the tracking differentiator; ESO is the extended state observer; NLSEF is the nonlinear state error feedback; is the total disturbance; is the system input signal; y is the output signal; is the total external disturbance; the differential signal and the differential signal TD will transformed into; , and , respectively , and total disturbance An estimate of is the parameter in TD; Value is the fast factor; is the system sampling step; is a dimensionless parameter, An integer multiple of ; is the parameter in ESO; is with Related coefficient parameters; is a meaningless coefficient, Integer multiple of; control quantity coefficient is a time-varying function, approximately a constant ; It is the parameter in NLSEF; is the damping factor, is the fast factor, is the control quantity factor; fhan and fal are the expressions of nonlinear functions respectively; For the accused; is the error feedback control quantity; , , and is a dimensionless intermediate parameter; The parameters to be optimized in the ADRC model include the parameters ; The method of optimizing the parameters of the active disturbance rejection controller model by using a crowd search algorithm includes: Step 1: , initialize the crowd search algorithm, set the spatial dimension, system sampling step, crowd size, and maximum number of iterations N , the minimum fitness value and the range of the space searched by the population, and randomly generate multiple initial individuals in the feasible solution domain; each of the initial individuals is a combination of the parameters to be optimized; Step 2: Calculate the fitness value of each individual; Step 3: Calculate the search direction and step length of each individual in each dimension; Step 4: Based on the search direction and step length, the position of each individual is updated to re-determine the fitness value of each individual; Step 5: Order , and determine whether the stop condition is met; if so, output the optimal parameter combination; if not, return to step 2; The calculation formula of the fitness value is: ； in, is the deviation between the given value and the output; is the difference between two adjacent step outputs; is the weight of the deviation in the fitness function, is the weight of the square term of the control quantity in the fitness function; To control the amount; Q refers to the objective function value; In the optimization process, the weight factor Make dynamic adjustments, including: ； in, represents the maximum number of iterations, and are the maximum inertia weight and the minimum inertia weight, Indicates the current iteration number.

2. The photoelectric pod control method based on crowd self-interference rejection according to claim 1 is characterized in that: The photoelectric pod dynamics model is composed of the transient motion equation of the tethered balloon, the boundary conditions of the anchor point, the boundary conditions of the main node, the steady-state motion equation of the tethered balloon and the differential coupling dynamics equation of the tether.

3. The photoelectric pod control method based on crowd self-interference rejection according to claim 2 is characterized in that: The expression of the transient motion equation of the tethered balloon is: ； The boundary condition of the anchor point is expressed as: ； The expression of the master node boundary condition is: ； Assume that the dynamic equation of the mooring cable is expressed as: ； Then the expression of the steady-state motion equation of the tethered balloon is: ； The differential coupled dynamic equation of the mooring cable is expressed as: ； in, is the mass matrix, and is the intermediate result matrix, is the force matrix; Y is the mooring state matrix: , is the inclination angle of the mooring cable, is the azimuth of the mooring cable, are the components of the mooring cable’s velocity in CFS respectively; is the projection of the sum of the inertial force and aerodynamic force of the tether in the body axis system BFS of the tethered balloon; is the velocity of the tethered balloon in the BFS; for The derivation of is the rotational torque; is the velocity of the mooring cable in the mooring cable local coordinate system CFS; is the coordinate transformation matrix between the ground coordinate system EFS where the anchor point is located and the CFS; is the speed of the anchor point in the EFS; For the N The speed of a node in the CFS; Master Node B vector in the BFS; Master Node B The speed in the BFS; is the motor angular velocity of the optoelectronic pod’s rotation axis; [ p , q , r ] are respectively the rotation angular velocities of the tethered balloon in the BFS; They are the yaw angle, pitch angle and roll angle of the tethered balloon respectively; They are i time, j The value corresponding to the position; It is the mooring cable micro segment; A micro-segment of time.

4. The photoelectric pod control method based on crowd self-interference rejection according to claim 1 is characterized in that: The speed stabilization loop control model includes a motor transfer function of the optoelectronic pod rotation axis, a transfer function of the speed gyro, and a transfer function of the power amplifier.

5. The photoelectric pod control method based on crowd self-interference rejection according to claim 4 is characterized in that: The expression of the motor transfer function is: ； The transfer function of the velocity gyro is expressed as: ； The transfer function of the power amplifier is expressed as: ； in, , and They are the transfer function of the motor, the transfer function of the speed gyro and the transfer function of the power amplifier; is the armature winding inductance; J is the total moment of inertia on the motor shaft; is the motor torque coefficient, is the electromotive force coefficient of the motor; is the armature winding resistance; is the Laplace transform of the output angular velocity, is the Laplace transform of the input quantity; It is the proportional link of the speed gyroscope; It is the proportional amplification link of the power amplifier.

6. An optoelectronic pod control device based on crowd self-interference resistance, characterized in that: include: A first processing unit is used to establish a dynamic model of an optoelectronic pod based on a tethered balloon system; A second processing unit is used to perform theoretical modeling on each actuator of the control system of the tethered balloon system and establish a speed stabilization loop control model; A third processing unit is used to establish an active disturbance rejection controller model based on the optoelectronic pod dynamics model and the speed stabilization loop control model; A fourth processing unit is used to optimize the parameters of the active disturbance rejection controller model by using a crowd search algorithm to determine an optimal active disturbance rejection controller model, so as to implement stable control of the optoelectronic pod by using the optimal active disturbance rejection controller model; The expression of the active disturbance rejection controller model is: ； ； ； ； ； ； ； in, is the differential equation of the optoelectronic pod control system; TD is the tracking differentiator; ESO is the extended state observer; NLSEF is the nonlinear state error feedback; is the total disturbance; is the system input signal; y is the output signal; is the total external disturbance; the differential signal and the differential signal TD will transformed into; , and , respectively , and total disturbance An estimate of is the parameter in TD; Value is the fast factor; is the system sampling step; is a dimensionless parameter, An integer multiple of ; is the parameter in ESO; is with Related coefficient parameters; is a meaningless coefficient, Integer multiple of; control quantity coefficient is a time-varying function, approximately a constant ; It is the parameter in NLSEF; is the damping factor, is the fast factor, is the control quantity factor; fhan and fal are the expressions of nonlinear functions respectively; For the accused; is the error feedback control quantity; , , and is a dimensionless intermediate parameter; The parameters to be optimized in the ADRC model include the parameters ; The method of optimizing the parameters of the active disturbance rejection controller model by using a crowd search algorithm includes: Step 1: , initialize the crowd search algorithm, set the spatial dimension, system sampling step, crowd size, and maximum number of iterations N , the minimum fitness value and the range of the space searched by the population, and randomly generate multiple initial individuals in the feasible solution domain; each of the initial individuals is a combination of the parameters to be optimized; Step 2: Calculate the fitness value of each individual; Step 3: Calculate the search direction and step length of each individual in each dimension; Step 4: Based on the search direction and step length, the position of each individual is updated to re-determine the fitness value of each individual; Step 5: Order , and determine whether the stop condition is met; if so, output the optimal parameter combination; if not, return to step 2; The calculation formula of the fitness value is: ； in, is the deviation between the given value and the output; is the difference between two adjacent step outputs; is the weight of the deviation in the fitness function, is the weight of the square term of the control quantity in the fitness function; To control the amount; Q refers to the objective function value; In the optimization process, the weight factor Make dynamic adjustments, including: ； in, represents the maximum number of iterations, and are the maximum inertia weight and the minimum inertia weight, Indicates the current iteration number.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the optoelectronic pod control method based on crowd self-anti-disturbance as described in any one of claims 1 to 5 are implemented.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the optoelectronic pod control method based on crowd self-anti-disturbance as described in any one of claims 1 to 5 are implemented.

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