CN-121979251-A - Unmanned aerial vehicle track tracking control method based on model prediction and preset performance constraint

CN121979251ACN 121979251 ACN121979251 ACN 121979251ACN-121979251-A

Abstract

The invention relates to an unmanned aerial vehicle track tracking control method based on model prediction and preset performance constraint, which is characterized in that Lyapunov stability constraint is introduced into a model prediction control frame and a preset performance control mechanism is integrated, so that uniformity of performance constraint and system stability analysis is realized, and the method comprises the following steps of establishing a nonlinear system model based on unmanned aerial vehicle dynamics; defining position errors and attitude errors, constructing a preset performance function, converting errors with performance constraints into unconstrained errors through error normalization and nonlinear transformation, establishing a model prediction optimization problem under the premise of considering input saturation and stability constraints, designing an auxiliary control law based on the transformation errors to construct stability constraints, and proving that the control strategy can ensure that the errors meet the preset performance constraints and the local asymptotic stability of the system. The invention can realize stable and reliable track tracking control of the unmanned aerial vehicle system, and has higher tracking precision and good dynamic performance.

Inventors

LIU WEI
TIAN CHENGJI

Assignees

华南理工大学

Dates

Publication Date: 20260505
Application Date: 20260409

Claims (10)

1. The unmanned aerial vehicle track tracking control method based on model prediction and preset performance constraint is characterized by comprising the following steps, According to the kinematics and dynamics relation of the unmanned aerial vehicle, a nonlinear system model is established, and a state variable of the unmanned aerial vehicle is obtained; Based on the obtained state variables of the unmanned aerial vehicle, defining a position error and an attitude error, and obtaining a tracking error based on the position error and the attitude error Constructing a preset performance function, and carrying out error normalization and nonlinear transformation to restrict tracking errors constrained by the preset performance function Conversion to equivalent unconstrained error variables ; To unconstrained error variable As a prediction error is introduced into a cost function, a model prediction control optimization problem is established under the premise of considering input saturation and stability constraint; based on unconstrained error variables Designing an auxiliary control law; and solving a model predictive control optimization problem based on an auxiliary control law to obtain an optimal control sequence, and acting a control instruction corresponding to a first sampling period in the optimal control sequence on the unmanned aerial vehicle as an actual control input so as to realize track tracking.
2. The unmanned aerial vehicle track tracking control method of claim 1, wherein the nonlinear system model of the unmanned aerial vehicle is: ; ; Wherein, the Representing the position and yaw angle of the unmanned aerial vehicle in an inertial coordinate system, Is the linear velocity and the angular velocity of the unmanned aerial vehicle under the machine body coordinate system, The control input is represented as such, And Is the gain matrix described by a diagonal matrix, 、、、 As the gain factor of the gain factor, 、、、 Is a time constant which is a function of the time constant, Representing a transformation matrix for transforming vectors from a body coordinate system to an inertial coordinate system, defining tracking errors as , Is the reference trajectory.
3. The unmanned aerial vehicle track following control method of claim 2, wherein to ensure a tracking error Meeting expected transient and steady-state performances, and introducing a preset performance function matrix , Is a diagonal matrix of smooth, bounded and strictly decreasing scalar functions, i.e Such that each component of the unconstrained error variable satisfies: , , ; Wherein, the Representing the corresponding components of position and yaw angle, selecting each boundary function The method comprises the following steps: ; Wherein, the , , Respectively representing the initial error boundary, the final steady-state boundary and the convergence rate of each component, and is required to satisfy 。
4. The unmanned aerial vehicle trajectory tracking control method of claim 3, wherein the unmanned aerial vehicle trajectory tracking control method uses a preset performance function matrix and tracking errors Defining a normalized error variable: ; Wherein, the , And is also provided with Transforming each normalized error component: ; Using functions of the above type Converting normalized error into unconstrained error as long as Remains bounded, and can ensure when In the time-course of which the first and second contact surfaces, Establishment, definition of 。
5. The unmanned aerial vehicle trajectory tracking control method of claim 4, wherein the model predicts the cost function of the control optimization problem At the sampling time The definition is as follows: Wherein, the Is the prediction error of the current signal, , In order to predict the time domain of the signal, Is divided into In the step of the method, the device comprises the steps of, Is the sampling period of time that is required for the sample, Is the state of the prediction and, Is a control sequence in the prediction domain, Is a positive diagonal weighting matrix of prediction errors, Is the positive-definite diagonal weighting matrix of the system input, Representation of , Representation of , Is at A cost function of the time of day, Meeting control input saturation constraints , Is the maximum input limit.
6. The unmanned aerial vehicle trajectory tracking control method of claim 5, wherein the model predictive control optimization problem introduces Lyapunov stability contraction constraints: Wherein, the method comprises the steps of, Is at The auxiliary control law of the moment of time, Is a lyapunov function that is, Representing a non-linear model of the unmanned aerial vehicle, Is shown in An initial state of time.
7. The unmanned aerial vehicle trajectory tracking control method of claim 6, wherein for the unconstrained error variable Subscript of Representing the corresponding components of position and yaw angle, the time derivatives of the components thereof Can be expressed as: ; To simplify expression, definitions , ; Defined herein And Thus, it is Can be rewritten as ; To design the auxiliary control law, the following error variables are defined Wherein For virtually controlling input vectors, designed as ; Wherein, the Is a positive fixed gain matrix and is used to determine the gain, Is a virtual control input vector.
8. The unmanned aerial vehicle track following control method of claim 7, wherein the auxiliary control law Adopts a back-step method design, and the concrete form is as follows: ; Wherein, the The gain matrix is determined for a positive direction, As a vector of the error it is, Representing the derivative of the transformation matrix, Representing the second derivative of the reference trajectory, Is that The derivative of the derivative is used to determine, 。
9. The method for controlling tracking of unmanned aerial vehicle according to claim 8, wherein the unmanned aerial vehicle tracking control method is satisfied when Not less than the auxiliary control law With recursive feasibility at an upper bound of infinity, the stability being only in a defined attraction domain The inner holds that the specific range of the attraction domain is constrained by the controller parameters.
10. An electronic device comprising a processor and a memory, wherein the memory stores a computer program, and wherein the processor implements the unmanned aerial vehicle trajectory tracking control method of any one of claims 1-9 when executing the computer program.

Description

Unmanned aerial vehicle track tracking control method based on model prediction and preset performance constraint Technical Field The invention relates to the technical field of automatic control, in particular to an unmanned aerial vehicle track tracking control method based on model prediction and preset performance constraint. Background The unmanned plane is used as high-tech equipment integrating advanced electronic technology and computer technology, and can complete various flight tasks through a preset program or an autonomous decision-making system under the condition that personnel do not need to control in real time. Along with continuous iteration of sensor technology and automatic control technology and continuous maturity of production manufacturing process, unmanned aerial vehicle is applied to fields such as intelligent agriculture, electric power inspection, road monitoring in the aspect of civilian use. Therefore, how to design an effective control strategy to ensure that the unmanned aerial vehicle realizes high-precision tracking control is an important and challenging research subject. Conventional control methods can meet the track tracking requirements of unmanned aerial vehicles to a certain extent, but often lack systematic means when dealing with hard constraints related to unmanned aerial vehicles, and it is difficult to guarantee the transient performance of a closed-loop system. The model predictive control method (CN 120215553A) of the four-rotor unmanned aerial vehicle based on DQN, the model predictive control method (CN 118092493A) of the four-rotor unmanned aerial vehicle based on multi-model and the model predictive control method (CN 115480487A) of the unmanned aerial vehicle driven by a hybrid strategy respectively improve the predictive capability and the control precision of the unmanned aerial vehicle from different angles, but the transient performance of a closed-loop system is difficult to directly guarantee by the methods. If the preset performance constraint is directly used as the constraint of the model prediction, the model prediction optimization problem may be caused to be insoluble. In addition, the multi-four-rotor unmanned aerial vehicle preset performance enclosing fault-tolerant control method (CN 120065731A) and the unmanned aerial vehicle preset performance control method and system (CN 119536343A) taking time-varying position constraint into consideration achieve good effects in the aspects of ensuring tracking performance, processing time-varying constraint and the like, but the preset performance framework is difficult to process complex constraints such as input saturation and state constraint. Disclosure of Invention Aiming at the problems existing in the prior art, the invention aims to provide the unmanned aerial vehicle track tracking control method based on model prediction and preset performance constraint, which can ensure that tracking errors meet the preset performance constraint and ensure recursion feasibility under the condition of bounded auxiliary control laws. In order to achieve the above purpose, the invention adopts the following technical scheme: the unmanned aerial vehicle track tracking control method based on model prediction and preset performance constraint comprises the following steps, According to the kinematics and dynamics relation of the unmanned aerial vehicle, a nonlinear system model is established, and a state variable of the unmanned aerial vehicle is obtained; Based on the obtained state variables of the unmanned aerial vehicle, defining a position error and an attitude error, and obtaining a tracking error based on the position error and the attitude error Constructing a preset performance function, and carrying out error normalization and nonlinear transformation to restrict tracking errors constrained by the preset performance functionConversion to equivalent unconstrained error variables; To unconstrained error variableAs a prediction error is introduced into a cost function, a model prediction control optimization problem is established under the premise of considering input saturation and stability constraint; based on unconstrained error variables Designing an auxiliary control law; and solving a model predictive control optimization problem based on an auxiliary control law to obtain an optimal control sequence, and acting a control instruction corresponding to a first sampling period in the optimal control sequence on the unmanned aerial vehicle as an actual control input so as to realize track tracking. Further, the nonlinear system model of the unmanned aerial vehicle is: ;; Wherein, the Representing the position and yaw angle of the unmanned aerial vehicle in an inertial coordinate system,Is the linear velocity and the angular velocity of the unmanned aerial vehicle under the machine body coordinate system,The control input is represented as such,AndIs the gain matrix described by a diagonal matrix,