Non-linear switching control method for air-ground dual-purpose robot

Abstract

The invention discloses a non-linear switching control method for an air-ground dual-purpose robot, and relates to the technical field of robot control. The invention aims to solve the problem that a traditional control method is difficult to directly apply due to the fact that the degree of freedom of a system state of an air-ground dual-purpose robot changes along with mode switching. The invention provides a non-linear switching control method for an air-ground dual-purpose robot. The non-linear switching control method comprises the following steps: constructing an air-ground dual-purpose robot control system model; carrying out stability analysis on the air-ground dual-purpose robot control system; and establishing a nonlinear switching controller of the air-ground dual-purpose robot according to a stability analysis result, and controlling the air-ground dual-purpose robot by using the nonlinear switching controller. According to the method, an existing generalized system theory method is expanded, and the method has high engineering application value.

Description

Technical Field

[0001] The present application belongs to the field of robot control technology. Background Art

[0002] Dual-purpose air-ground robots possess both aerial and terrestrial mobility, freely switching between these modes depending on the mission scenario. Compared to ground robots, they offer greater spatial accessibility and superior obstacle-crossing capabilities; compared to aerial robots of similar size, they consume less energy and have longer flight times. Due to their combined advantages of spatial accessibility and long flight times, dual-purpose air-ground robots have garnered increasing attention in recent years, with applications in underground space exploration, pipeline and bridge inspections, and other tasks.

[0003] As a typical multimodal system, the air-ground dual-purpose robot exhibits significantly different dynamic characteristics in aerial mode and ground mode. Its system state degrees of freedom change with mode switching, making it difficult to directly apply traditional control methods.

[0004] Application Contents

[0005] This application aims to solve the problem that the system state freedom degree of air-ground dual-purpose robots changes with mode switching, making it difficult to directly apply traditional control methods. Now, combined with the fuzzy generalized hybrid system theory, a nonlinear switching control method for air-ground dual-purpose robots is provided, which can complete nonlinear switching control based on the stability analysis method of multiple Lyapunov functions.

[0006] This application provides a nonlinear switching control method for an air-ground dual-purpose robot, including:

[0007] Construct a control system model for an air-ground dual-purpose robot;

[0008] Conducting stability analysis on the control system of the air-ground dual-purpose robot;

[0009] A nonlinear switching controller of the air-ground dual-purpose robot is established according to the stability analysis result, and the air-ground dual-purpose robot is controlled by using the nonlinear switching controller.

[0010] Furthermore, the above-mentioned construction of the air-ground dual-purpose robot control system model includes:

[0011] The dynamics analysis of the aerial flight mode and ground rolling mode of the air-ground dual-purpose robot was carried out respectively to obtain the dynamic models under the aerial flight mode and ground rolling mode; based on the fuzzy generalized hybrid system, the control system model of the air-ground dual-purpose robot was established.

[0012] Furthermore, the control system model of the above-mentioned air-ground dual-purpose robot is expressed as follows:

[0013]

[0014] Among them, σ(t)∈{1,2} is the modal variable of the air-ground dual-purpose robot, σ(t)=1 represents the air mode, σ(t)=2 represents the ground mode, h m (t) is the weight coefficient of the fuzzy subsystem and satisfies 0≤h m (t)≤1 and m represents the fuzzy rule, m∈{1,2,…,M}, M is the number of fuzzy rules,

[0015] x(t) and u(t) are the state variables and input variables of the air-ground dual-purpose robot control system, respectively, and: x = [φ θ ψ pqr] T ,u=[u φ u θ u ψ ] T , φ, θ, ψ are the roll angle, pitch angle and yaw angle of the air-ground dual-purpose robot respectively, p, q, r are the angular velocities of the air-ground dual-purpose robot along the three axes of the body coordinate system respectively, u φ 、u θ 、u ψ are the components of the input torque corresponding to φ, θ, and ψ, respectively.

[0016] E[σ(t)]、A m [σ(t)] and B m [σ(t)] are all control system matrices of the air-ground dual-purpose robot, and [φ m θ m ψ m p m q m r m ] T is the equilibrium state of the air-ground dual-purpose robot control system corresponding to the fuzzy rule m, then:

[0017]

[0018] I6 is the six-dimensional identity matrix, J x 、J y 、J z are the components of the body's moment of inertia corresponding to the three axes of the body's coordinate system, k p 、k q 、k r are the components of the air resistance coefficient corresponding to the three axes of the air-ground dual-purpose robot along the body coordinate system.

[0019] Furthermore, the stability analysis of the control system of the air-ground dual-purpose robot includes:

[0020] Based on matrix analysis theory, the equivalent form of the air-ground dual-purpose robot control system model is obtained; the state jump form of the air-ground dual-purpose robot at the air-ground switching moment is obtained according to the generalized system method analysis; combined with the equivalent form of the air-ground dual-purpose robot control system model and the state jump form of the air-ground dual-purpose robot at the air-ground switching moment, the stability condition of the air-ground dual-purpose robot control system is established, and the stability analysis of the air-ground dual-purpose robot control system is performed based on the stability condition.

[0021] Furthermore, based on the matrix analysis theory, the equivalent form of the air-ground dual-purpose robot control system model is obtained, including:

[0022] According to the matrix analysis theory, the fuzzy generalized hybrid system and There exists a non-singular matrix n x is the dimension of the state variable x, such that:

[0023] For r i The identity matrix of dimension r i is the rank of E(i),

[0024]

[0025] make

[0026] Then the air-ground dual-purpose robot control system model described in the formula has the following equivalent form:

[0027]

[0028] Furthermore, the state transition form of the air-ground dual-purpose robot at the air-ground switching moment obtained by the above analysis based on the generalized system method includes:

[0029] for By the consistent projection π m (i) State transition form for:

[0030]

[0031]

[0032] Furthermore, the above-mentioned stability conditions of the air-ground dual-purpose robot control system are established by combining the equivalent form of the air-ground dual-purpose robot control system model and the state jump form of the air-ground dual-purpose robot at the air-ground switching moment, including:

[0033] Consider an open-loop fuzzy generalized hybrid system, given constants α>0 and μ≥1, when there exists a matrix System submode And i≠j, fuzzy rule And m≠n, then there is a stability condition:

[0034]

[0035] in,

[0036]

[0037] The control system of the air-ground dual-purpose robot is globally uniformly asymptotically stable for switching signals that satisfy the dwell time condition, which is:

[0038]

[0039] Furthermore, the nonlinear switching controller of the air-ground dual-purpose robot is established based on the stability analysis results, including:

[0040] A state feedback switching fuzzy controller based on fuzzy rules is constructed; based on the stability analysis results, the existence conditions of the controller of the air-ground dual-purpose robot are established; and the existence conditions of the controller of the air-ground dual-purpose robot are solved to obtain a nonlinear switching controller.

[0041] Furthermore, the controller of the above-mentioned air-ground dual-purpose robot has the following conditions:

[0042] Consider an open-loop fuzzy generalized hybrid system, given constants α>0 and μ≥1, when there exists a matrix and W m (i), system submode And i≠j, fuzzy rule And m≠n, then the controller exists under the following conditions:

[0043]

[0044]

[0045] in,

[0046]

[0047] The control system of the air-ground dual-purpose robot is globally uniformly asymptotically stable for switching signals that satisfy the dwell time condition, which is:

[0048]

[0049] Furthermore, the expression of the above nonlinear switching controller is:

[0050]

[0051] Among them, K n [σ(t)] is the feedback gain, which is expressed as:

[0052]

[0053] Beneficial effects of this application:

[0054] This application addresses the issue of modal variations in state dimensions and nonlinear dynamics in the multimodal motion of an air-to-ground dual-purpose robot. By applying a fuzzy generalized hybrid system model and a multi-Lyapunov function approach, a switching controller is designed that can adapt to nonlinear dynamics of different dimensions in both air and ground. This controller effectively reduces state tracking errors in large-angle maneuver tracking tasks for the air-to-ground dual-purpose robot. The beneficial effects of this application are:

[0055] First, this application expands the generalized hybrid system model, fully considering the state dimensional changes of the robot's aerial flight and ground rolling modes, and realizes unified modeling of the nonlinear dynamics of air / ground modes. It can support the numerical analysis of indicators such as the stability, dynamic response, and motion accuracy of the robot's air-ground hybrid motion.

[0056] Second, this application adopts the TS fuzzy method to characterize the nonlinear characteristics of the air-ground dual-purpose robot. The designed nonlinear switching controller has a faster response speed and smaller tracking error than the existing linear controller.

[0057] In summary, this application addresses the practical engineering problem of motion control for air-to-ground dual-use robots by proposing a stability analysis and controller design method based on fuzzy generalized hybrid systems. This method expands existing generalized system theory and has high engineering application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 This is a flow chart of a generalized nonlinear switching control method for air-ground dual-purpose robots;

[0059] Figure 2 This is a schematic diagram of the structure of an air-ground dual-purpose robot;

[0060] Figure 3 is a system modal diagram in an embodiment;

[0061] Figure 4 A comparison diagram of the state response curves of the control method of the present application and the traditional method φ in the embodiment;

[0062] Figure 5: is a comparison diagram of the state response curves of the control method of the present application and the traditional method θ in the embodiment;

[0063] Figure 6 : A comparison diagram of the tracking error of the attitude angle φ of the control method of the present application and the traditional method in the embodiment;

[0064] Figure 7 3 is a comparison chart of the tracking error of the attitude angle θ between the control method of the present application and the traditional method in the embodiment. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application. It should be noted that, in the absence of conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0066] The proportional-integral-derivative (PID) control method commonly used in the UAV field fails to fully consider the kinematic characteristics and correlations of air-ground modes, and cannot guarantee system stability during air-ground switching, posing a significant safety hazard to the practical application of air-ground dual-use robots. Another approach, based on generalized hybrid systems, can provide modeling tools for air-ground cross-domain robots, but existing theoretical results are relatively preliminary and lack nonlinear control methods.

[0067] In view of this, the embodiment of the present application provides a nonlinear switching control method and system for an air-ground dual-purpose robot in order to solve the above problems. Figures 1 to 7 , the scheme of the implementation method of this application is described in detail.

[0068] Specific implementation method one: Figure 1 A nonlinear switching control method for an air-ground dual-use robot is provided, comprising steps 1 to 3. The numbering of each step does not necessarily limit the order in which they are executed. Each step is described in detail below:

[0069] Step 1: Build the air-ground dual-purpose robot system and controller model.

[0070] Dynamic analysis is performed on the air-ground robot's flight mode and ground rolling mode, respectively, taking into account the state dimension changes and nonlinear dynamic characteristics of the air-ground robot's motion process. Based on the fuzzy generalized hybrid system, a unified air-ground state space expression is established.

[0071] The air-ground dual-purpose robot studied in this embodiment has the following features: Figure 2The structure shown in the figure is composed of an embedded quadrotor and passive wheels on both sides. To describe the motion of the air-ground dual-purpose robot, the inertial coordinate system I, the body coordinate system B, and the rolling coordinate system R are defined. Figure 2 As shown, Perpendicular to the embedded quadrotor plane, and coincide, and parallel.

[0072] In the aerial flight mode, the four rotor motors can provide rotational torque to change the body's attitude and position. Its dynamic model is as follows:

[0073]

[0074] Among them, φ, θ, ψ are the roll angle, pitch angle and yaw angle of the air-ground dual-purpose robot respectively, p, q, r are the angular velocities of the air-ground dual-purpose robot along the three axes of the body coordinate system respectively, J x 、J y 、J z They are the components of the body's moment of inertia in the three axes in the body coordinate system, u φ 、u θ 、u ψ are the components of the input torque corresponding to the roll angle, pitch angle, and yaw angle, respectively, k p 、k q 、k r are the three-axis components of the air resistance coefficient in the body coordinate system.

[0075] In ground rolling mode, the passive wheels on both sides provide ground support force, and the four rotor motors provide rotational torque in the pitch and yaw directions. The dynamic model is as follows:

[0076]

[0077] Among them, d θ and d ψ are the components of the pitch angle and yaw angle corresponding to the disturbance torque. It is worth noting that the state freedom of the air-ground system is different. Due to the ground restrictions, the roll angle According to the coordinate system transformation relationship, It can be written as p+rtanθ=0.

[0078] In order to establish a unified air-ground dual-purpose robot control system model, the state variables of the control system are recorded as x = [φ θ ψ pqr] T , the input variable of the control system is recorded as u=[u φ u θ u ψ ] TBased on the fuzzy generalized hybrid system, the following air-ground dual-purpose robot control system model is established:

[0079]

[0080] in, is the modal variable of the air-ground dual-purpose robot, σ(t) = 1 corresponds to the air mode, and σ(t) = 2 corresponds to the ground mode. is the fuzzy rule of the air-ground dual-purpose robot control system, which characterizes the nonlinear characteristics of the system, and M is the number of fuzzy rules. m (t) is the weight coefficient of the fuzzy subsystem, satisfying 0≤h m (t)≤1 and is the first-order derivative of the state variable x(t) at time t.

[0081] E[σ(t)]、A m [σ(t)], B m [σ(t)] is the system matrix, and [φ m θ m ψ m p m q m r m ] T is the system equilibrium state corresponding to the fuzzy rule m (φ m θ m ψ m p m q m r m represent the roll angle, pitch angle, yaw angle and angular velocity of the robot along the three axes of the body coordinate system under the fuzzy rule m respectively. The system matrix can be expressed as:

[0082] E(1)=I6, I6 is the six-dimensional identity matrix,

[0083]

[0084] Step 2: Conduct stability analysis on the air-ground dual-purpose robot system.

[0085] Based on matrix analysis theory, an equivalent form of the air-ground dual-purpose robot system model is proposed. Then, combined with the generalized system method, the state transition form of the air-ground dual-purpose robot at the air-ground switching moment is analyzed. Finally, the multi-Lyapunov function is applied to judge the stability of the air-ground dual-purpose robot system.

[0086] According to the matrix analysis theory, for the fuzzy generalized hybrid system and arbitrary submode of formula (5) There exists a non-singular matrix (n x is the dimension of the state variable x) such that:

[0087] For r i The identity matrix of dimension r i is the rank of E(i),

[0088]

[0089] Because B m (i), M(i) and N(i) are known, then Able to pass M(i)B m (i)N(i) is obtained.

[0090] make Then formula (5) has the following equivalent form:

[0091]

[0092] It is known from the generalized hybrid system theory that the system state may jump at the moment of mode switching. By the consistent projection π m (i) State transition form as follows:

[0093] and are the time before and after the jump,

[0094]

[0095] Combining the system equivalent form of equations (6) and (7) and the state jump form of equations (8) and (9), the following stability condition of the air-ground dual-purpose robot system can be established:

[0096] Considering an open-loop fuzzy generalized hybrid system Given constants α>0 and μ≥1, if there exists a matrix For the system submode For fuzzy rules The following inequality holds:

[0097]

[0098] in,

[0099]

[0100] The system satisfies the residence time condition The switching signal is globally consistent and asymptotically stable.

[0101] Step 3: Design a nonlinear switching controller for the air-ground dual-purpose robot system.

[0102] The mathematical expression of the controller based on fuzzy rules is given; then, according to the stability analysis results of the air-ground dual-purpose robot system in step 2, the existence conditions of the controller of the air-ground dual-purpose robot system are established.

[0103] Based on the equivalent form of step 2, a state feedback switching fuzzy controller is given as follows:

[0104]

[0105] Among them, K n [σ(t)] is the feedback gain.

[0106] Solving the existence condition of the state feedback switching fuzzy controller of the form (15) can obtain the feedback gain K n [σ(t)], thereby ensuring the stability of the closed-loop system.

[0107] Based on the stability analysis results of the air-ground dual-purpose robot system given in step 2, the existence conditions of the state feedback switching fuzzy controller are further derived:

[0108] Consider an open-loop fuzzy generalized hybrid system, given constants α>0, μ≥1, if there exists a matrix and W m (i), for the system submode And i≠j, fuzzy rule And m≠n, the following inequality holds:

[0109]

[0110] in,

[0111]

[0112] The system satisfies the residence time condition The switching signal is globally consistent and asymptotically stable.

[0113] By using the Yalmip toolbox and the Sdpt3 solver to solve the linear matrix inequalities (16) to (21), a nonlinear switching controller with guaranteed stability can be obtained.

[0114] The nonlinear switching controller based on fuzzy rules is in the form of:

[0115]

[0116] The feedback gain is:

[0117]

[0118] Example

[0119] In this embodiment, for a structure such as Figure 2 Controller design for an air-ground dual-purpose robot.

[0120] Based on step 1, the system model is given, where:

[0121] Body moment of inertia: J x =0.319, J y =0.256, J z =0.352;

[0122] Air resistance coefficient: k p =0.06, k q =0.06, k r =0.02;

[0123] Mission required pitch angle Take fuzzy rule m=2;

[0124] Balance point: φ1=φ2=0, ψ1=ψ2=0, θ1=0, θ2=π / 3, p1=p2=0, q1=q2=0, r1=r2=0;

[0125] Fuzzy weight coefficient h1(t)=(θ-θ1) / (θ2-θ1), h2(t)=(θ2-θ) / (θ2-θ1).

[0126] According to the judgment conditions given in steps 2 and 3, stability analysis and controller design are performed on this system. The nonlinear switching controller is solved using the Yalmip toolbox and the Sdpt3 solver. The controller gain is:

[0127]

[0128] The system modal change curve is as follows: Figure 3 As shown, the state response curve and error comparison diagram of this embodiment and the traditional method are respectively Figures 4 to 7 It can be seen that the nonlinear switching control method proposed in this embodiment has better tracking effect than the traditional method and is suitable for large-angle tracking tasks. Specific embodiment 2: The nonlinear switching control system of the air-ground dual-purpose robot described in this embodiment includes:

[0129] Model building unit: used to build the control system model of the air-ground dual-purpose robot.

[0130] Stability analysis unit: used to perform stability analysis on the air-ground dual-purpose robot control system.

[0131] Control unit: used to establish a nonlinear switching controller of the air-ground dual-purpose robot according to the stability analysis result, and use the nonlinear switching controller to control the air-ground dual-purpose robot.

[0132] In one embodiment, the construction of the air-ground dual-purpose robot control system model includes:

[0133] The dynamics analysis of the aerial flight mode and ground rolling mode of the air-ground dual-purpose robot was carried out respectively to obtain the dynamic models under the aerial flight mode and ground rolling mode; based on the fuzzy generalized hybrid system, the control system model of the air-ground dual-purpose robot was established.

[0134] In one embodiment, the air-ground dual-purpose robot control system model expression is as follows:

[0135]

[0136] Among them, σ(t)∈{1,2} is the modal variable of the air-ground dual-purpose robot, σ(t)=1 represents the air mode, σ(t)=2 represents the ground mode, h m (t) is the weight coefficient of the fuzzy subsystem and satisfies 0≤h m (t)≤1 and m represents the fuzzy rule, m∈{1,2,…,M}, M is the number of fuzzy rules,

[0137] x(t) and u(t) are the state variables and input variables of the air-ground dual-purpose robot control system, respectively, and: x = [φ θ ψ pqr] T ,u=[u φ u θ u ψ ] T , φ, θ, ψ are the roll angle, pitch angle and yaw angle of the air-ground dual-purpose robot respectively, p, q, r are the angular velocities of the air-ground dual-purpose robot along the three axes of the body coordinate system respectively, u φ 、u θ 、u ψ are the components of the input torque corresponding to φ, θ, and ψ, respectively.

[0138] E[σ(t)]、A m [σ(t)] and B m [σ(t)] are all control system matrices of the air-ground dual-purpose robot, and [φ m θ m ψ m p m q m rm ] T is the equilibrium state of the air-ground dual-purpose robot control system corresponding to the fuzzy rule m, then:

[0139]

[0140] I6 is the six-dimensional identity matrix, J x 、J y 、J z are the components of the body's moment of inertia corresponding to the three axes of the body's coordinate system, k p 、k q 、k r are the components of the air resistance coefficient corresponding to the three axes of the air-ground dual-purpose robot along the body coordinate system.

[0141] In one embodiment, the stability analysis of the air-ground dual-purpose robot control system includes:

[0142] Based on matrix analysis theory, an equivalent form of the control system model of the air-ground dual-purpose robot is obtained;

[0143] The state transition form of the air-ground dual-purpose robot at the air-ground switching moment is obtained by analyzing the generalized system method;

[0144] Combining the equivalent form of the air-ground dual-purpose robot control system model and the state jump form of the air-ground dual-purpose robot at the air-ground switching moment, the stability condition of the air-ground dual-purpose robot control system is established, and the stability analysis of the air-ground dual-purpose robot control system is performed based on the stability condition.

[0145] In one embodiment, the equivalent form of the air-ground dual-purpose robot control system model is obtained based on matrix analysis theory, including:

[0146] According to the matrix analysis theory, the fuzzy generalized hybrid system and There exists a non-singular matrix n x is the dimension of the state variable x, such that:

[0147] For r i The identity matrix of dimension r i is the rank of E(i),

[0148]

[0149] make

[0150] Then the air-ground dual-purpose robot control system model described in the formula has the following equivalent form:

[0151]

[0152] In one embodiment, the state transition form of the air-ground dual-purpose robot at the air-ground switching moment is obtained by analyzing the generalized system method, including:

[0153] for By the consistent projection π m (i) State transition form for:

[0154]

[0155]

[0156] In one embodiment, the establishment of a stability condition of the air-ground dual-purpose robot control system by combining the equivalent form of the air-ground dual-purpose robot control system model and the state transition form of the air-ground dual-purpose robot at the air-ground switching moment includes:

[0157] Consider an open-loop fuzzy generalized hybrid system, given constants α>0 and μ≥1, when there exists a matrix System submode And i≠j, fuzzy rule And m≠n, then there is a stability condition:

[0158]

[0159] in,

[0160]

[0161] The control system of the air-ground dual-purpose robot is globally uniformly asymptotically stable for switching signals that satisfy the dwell time condition, which is:

[0162]

[0163] In one embodiment, establishing a nonlinear switching controller for the air-ground dual-purpose robot based on the stability analysis results includes:

[0164] Construct a state feedback switching fuzzy controller based on fuzzy rules;

[0165] According to the stability analysis results, the existence conditions of the controller of the air-ground dual-purpose robot are established;

[0166] The existence condition of the controller of the air-ground dual-purpose robot is solved to obtain a nonlinear switching controller.

[0167] In one embodiment, the controller of the air-ground dual-purpose robot exists under the following conditions:

[0168] Consider an open-loop fuzzy generalized hybrid system, given constants α>0 and μ≥1, when there exists a matrix and W m (i), system submode And i≠j, fuzzy rule And m≠n, then the controller exists under the following conditions:

[0169]

[0170]

[0171] in,

[0172]

[0173] The control system of the air-ground dual-purpose robot is globally uniformly asymptotically stable for switching signals that satisfy the dwell time condition, which is:

[0174]

[0175] In one embodiment, the expression of the nonlinear switching controller is:

[0176]

[0177] Among them, K n [σ(t)] is the feedback gain, which is expressed as:

[0178]

[0179] Specific embodiment three: The nonlinear switching control device of the air-ground dual-purpose robot described in this embodiment includes a processor and a memory, wherein the memory stores at least one instruction, and the at least one instruction is loaded and executed by the processor to implement the nonlinear switching control method of the air-ground dual-purpose robot as described in specific embodiment one.

[0180] Specific embodiment 4: This embodiment describes a computer storage medium, in which at least one instruction is stored. The at least one instruction is loaded and executed by a processor to implement the nonlinear switching control method of the air-ground dual-purpose robot as described in specific embodiment 1.

[0181] Although the present application is described herein with reference to specific embodiments, it should be understood that these embodiments are merely illustrative of the principles and applications of the present application. It should therefore be understood that many modifications may be made to the illustrative embodiments, and that other arrangements may be devised, without departing from the spirit and scope of the present application as defined by the appended claims. It should be understood that the various dependent claims and features described herein may be combined in ways other than those described in the original claims. It should also be understood that features described in conjunction with individual embodiments may be used in other described embodiments.

Claims

1. A nonlinear switching control method for an air-ground dual-purpose robot, characterized in that: include: Construct a control system model for an air-ground dual-purpose robot; Conducting stability analysis on the control system of the air-ground dual-purpose robot; A nonlinear switching controller of the air-ground dual-purpose robot is established according to the stability analysis result, and the air-ground dual-purpose robot is controlled by using the nonlinear switching controller.

2. The nonlinear switching control method for an air-ground dual-purpose robot according to claim 1, characterized in that: The construction of the air-ground dual-purpose robot control system model includes: The dynamics analysis of the air-to-ground dual-purpose robot in the air-to-flight mode and the ground-to-rolling mode was carried out respectively, and the dynamic models of the air-to-flight mode and the ground-to-rolling mode were obtained. Based on fuzzy generalized hybrid system, a control system model of air-ground dual-purpose robot is established.

3. The nonlinear switching control method for an air-ground dual-purpose robot according to claim 2, characterized in that: The control system model of the air-ground dual-purpose robot is expressed as follows: Among them, σ(t)∈{1,2} is the modal variable of the air-ground dual-purpose robot, σ(t)=1 represents the air mode, σ(t)=2 represents the ground mode, h m (t) is the weight coefficient of the fuzzy subsystem and satisfies 0≤h m (t)≤1 and m represents the fuzzy rule, m∈{1,2,…,M}, M is the number of fuzzy rules, x(t) and u(t) are the state variables and input variables of the air-ground dual-purpose robot control system, respectively, and: φ, θ, ψ are the roll angle, pitch angle and yaw angle of the air-ground dual-purpose robot respectively; p, q, r are the angular velocities of the air-ground dual-purpose robot along the three axes of the body coordinate system respectively; u φ 、u θ 、u ψ are the components of the input torque corresponding to φ, θ, and ψ, respectively. E[σ(t)]、A m [σ(t)] and B m [σ(t)] are all control system matrices of the air-ground dual-purpose robot. is the equilibrium state of the air-ground dual-purpose robot control system corresponding to the fuzzy rule m, then: E(1)=I6, E(2)=diag{0,1,1,0,1,1}, I6 is the six-dimensional identity matrix, J x 、J y 、J z are the components of the body's moment of inertia corresponding to the three axes of the body's coordinate system, k p 、k q 、k r are the components of the air resistance coefficient corresponding to the three axes of the air-ground dual-purpose robot along the body coordinate system.

4. The nonlinear switching control method for an air-ground dual-purpose robot according to claim 3, characterized in that: The stability analysis of the air-ground dual-purpose robot control system includes: Based on matrix analysis theory, an equivalent form of the control system model of the air-ground dual-purpose robot is obtained; The state transition form of the air-ground dual-purpose robot at the air-ground switching moment is obtained by analyzing the generalized system method; Combining the equivalent form of the air-ground dual-purpose robot control system model and the state jump form of the air-ground dual-purpose robot at the air-ground switching moment, the stability condition of the air-ground dual-purpose robot control system is established, and the stability analysis of the air-ground dual-purpose robot control system is performed based on the stability condition.

5. The nonlinear switching control method for an air-ground dual-purpose robot according to claim 4, characterized in that: The equivalent form of the air-ground dual-purpose robot control system model is obtained based on matrix analysis theory, including: According to the matrix analysis theory, the fuzzy generalized hybrid system and There exists a non-singular matrix n x is the dimension of the state variable x, such that: For r i The identity matrix of dimension r i is the rank of E(i), make Then the air-ground dual-purpose robot control system model described in the formula has the following equivalent form:

6. The nonlinear switching control method for an air-ground dual-purpose robot according to claim 5, characterized in that: The state transition form of the air-ground dual-purpose robot at the air-ground switching moment is obtained by analyzing the generalized system method, including: for By the consistent projection π m (i) State transition form for:

7. The nonlinear switching control method for an air-ground dual-purpose robot according to claim 5, characterized in that: The stability condition of the air-ground dual-purpose robot control system is established by combining the equivalent form of the air-ground dual-purpose robot control system model and the state jump form of the air-ground dual-purpose robot at the air-ground switching moment, including: Consider an open-loop fuzzy generalized hybrid system, given constants α>0 and μ≥1, when there exists a matrix System submode And i≠j, fuzzy rule And m≠n, then there is a stability condition: in, The control system of the air-ground dual-purpose robot is globally uniformly asymptotically stable for switching signals that satisfy the dwell time condition, which is:

8. The nonlinear switching control method for an air-ground dual-purpose robot according to claim 5, characterized in that: The nonlinear switching controller of the air-ground dual-purpose robot is established according to the stability analysis result, comprising: Construct a state feedback switching fuzzy controller based on fuzzy rules; According to the stability analysis results, the existence conditions of the controller of the air-ground dual-purpose robot are established; The existence condition of the controller of the air-ground dual-purpose robot is solved to obtain a nonlinear switching controller.

9. The nonlinear switching control method for an air-ground dual-purpose robot according to claim 8, characterized in that: The existence conditions of the controller of the air-ground dual-purpose robot include: Consider an open-loop fuzzy generalized hybrid system, given constants α>0 and μ≥1, when there exists a matrix and W m (i), system submode And i≠j, fuzzy rule And m≠n, then the controller exists under the following conditions: in, The control system of the air-ground dual-purpose robot is globally uniformly asymptotically stable for switching signals that satisfy the dwell time condition, which is:

10. The nonlinear switching control method for an air-ground dual-purpose robot according to claim 9, characterized in that: The expression of the nonlinear switching controller is: Among them, K n [σ(t)] is the feedback gain, which is expressed as:

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