A method for active tracking control of the hinge angle of a hinged vehicle based on a sinusoidal trajectory

Abstract

The present application relates to a kind of active hinged angle tracking control method based on sinusoidal trajectory of articulated vehicle, belong to vehicle intelligent control field.It aims to solve the problem of insufficient tracking accuracy caused by the step change of articulated angle when traditional articulated vehicle turns, the influence of nonlinear friction of hydraulic system and the risk of vehicle instability.The present application proposes: through path planning and cubic spline interpolation to generate smooth trajectory, the expected articulated angle is calculated through coordinate system conversion and kinematics model;Adopt Fourier series to decompose articulated angle into N order sine component, construct continuous and smooth bionic trajectory, eliminate step mutation;Based on articulated angle-hydraulic cylinder piston geometric constraint model, design adaptive tracking differentiator, robustly extract displacement high-order derivative through dynamic parameter adjustment mechanism, inhibit noise interference;Develop time-varying sliding mode controller, combine ATD output signal with asymmetric hydraulic cylinder model, use saturation function to suppress nonlinear friction buffeting, realize high-precision tracking of piston displacement.

Description

An Active Articulation Angle Tracking Control Method for Articulated Vehicles Based on Sine Trajectory Technical Field

[0001] This invention relates to an active articulation angle tracking control method for articulated vehicles based on a sinusoidal trajectory, belonging to the technical field of intelligent driving control. Background Technology

[0002] Articulated low-speed heavy-duty vehicles, with their unique articulated structure, exhibit significant advantages in turning in confined spaces and navigating complex terrains, and are widely used in mining transportation, agricultural operations, fire rescue, and other fields. The unique articulated structure design connects the front and rear vehicle bodies via a hydraulic mechanism, allowing for a large degree of horizontal relative deflection between them. This core characteristic gives articulated low-speed heavy-duty vehicles an extremely small turning radius and excellent terrain mobility. As a result, they can navigate environments with extremely limited space and exceptionally harsh road conditions with ease.

[0003] Traditional articulated low-speed heavy-duty vehicles rely on passive coupling control between the steering wheel and the articulation angle. The steering control logic of such vehicles is closely centered around the driver's operation of the steering wheel. The input generated by the driver turning the steering wheel is transmitted through the universal joint and drive shaft to the hydraulic steering control valve, which in turn drives the steering hydraulic cylinders connected to the front and rear frames, forming a mechanical closed loop.

[0004] However, when a vehicle is turning, the driver indirectly controls the dynamic process of the articulation angle through the steering wheel torque. The articulation angle changes abruptly, causing sudden changes in the instantaneous lateral acceleration / yaw rate of the articulated vehicle. This increases the risk of roll / instability, increases tire wear, reduces ride comfort, and the abrupt change makes the articulated vehicle less smooth in continuous small curvature steering or when fine trajectory tracking is required, making it difficult to adapt to complex and changing environments.

[0005] Therefore, a new solution is needed to address this problem. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide an active articulation angle tracking control method for articulated vehicles based on sinusoidal trajectory. This method solves the problem that articulated vehicles do not respond smoothly enough when turning with continuous small curvature or when fine trajectory tracking is required, and are difficult to adapt to complex and changing environments.

[0007] The technical problem to be solved by this invention is achieved by the following technical solution:

[0008] An active articulation angle tracking control method for articulated vehicles based on sinusoidal trajectories includes the following steps:

[0009] A global path is generated based on the environmental information of the articulated vehicle, wherein the environmental information includes at least obstacle information;

[0010] Obtain the trajectory points of the global path, transform the trajectory points of the global path into the articulated vehicle coordinate system, and obtain the desired attitude and position of the articulated vehicle in the local coordinate system based on the transformed trajectory points.

[0011] Based on the kinematic model of the articulated vehicle, the desired attitude and position are converted into changes in the hinge angle. The desired hinge angle change curve is obtained through kinematic calculation. The desired hinge angle change curve is decomposed into N sinusoidal components to generate a continuous and smooth hinge angle trajectory.

[0012] Based on the mechanical structural constraints of the articulated vehicle, a mapping relationship between the change of the articulation angle and the displacement of the hydraulic cylinder piston is established.

[0013] Based on the mapping relationship between the hinge angle change and the hydraulic cylinder piston displacement, the hinge angle trajectory is converted into the desired piston displacement signal;

[0014] Based on the desired piston displacement signal and combined with the valve control model, a time-varying sliding mode controller is designed to track and control the hydraulic cylinder piston.

[0015] The present invention is further configured to: acquire obstacle information through lidar, construct an environmental map, generate a feasible initial path based on the starting point and the target point using a hybrid A* algorithm, and perform smoothing processing using cubic spline interpolation to obtain the global path;

[0016] Based on the initial path, points obtained by sampling at unequal intervals are selected to guide the shape of the cubic spline interpolation curve;

[0017] Determine the boundary conditions for cubic spline interpolation based on the tangent direction and curvature at the starting point and the tangent direction and curvature at the ending point;

[0018] Based on the vehicle's kinematic model and actual driving constraints, set the constraints for cubic spline interpolation.

[0019] The present invention is further configured to: take the current position of the vehicle as the starting point, and generate multiple sub-nodes according to a preset expansion step size and different steering angles;

[0020] For each child node, check whether it collides with an obstacle. If it does not collide, add it to the open list and record its cost function value. Select the node with the smallest cost function value from the open list as the current node and continue to expand the nodes until the target point is found or the open list is empty.

[0021] After finding the target point, an initial path from the starting point to the target point is generated by backtracking the parent node of each node.

[0022] The present invention is further configured such that: the transformation of the trajectory points of the global path to the articulated vehicle coordinate system includes the following steps:

[0023] The vehicle's current position is taken as the origin of the coordinate system, and the vehicle's current heading angle is taken as the rotation reference.

[0024] Calculate the planar displacement vector of the global path point relative to the vehicle's current position;

[0025] Based on the vehicle's current heading angle, the planar displacement vector is rotated around the origin of the coordinate system;

[0026] After transformation, the longitudinal and lateral relative distances of the trajectory points of the global path in the vehicle coordinate system are obtained.

[0027] The present invention is further configured such that obtaining the hinge angle change based on the desired posture includes the following steps:

[0028] Based on the current steering wheel angle, vehicle wheelbase, and longitudinal distance from the rear vehicle's center of gravity to the hinge point, calculate the first intermediate parameter and the second intermediate parameter.

[0029] The first intermediate parameter is the product of the vehicle wheelbase and the steering wheel angle, and the second intermediate parameter is the sum of the vehicle wheelbase and the longitudinal distance.

[0030] Divide the first intermediate parameter by the second intermediate parameter to obtain the ratio result;

[0031] Calculate the arctangent of this ratio and output the hinge angle.

[0032] The present invention is further configured to decompose the obtained hinge angle variation curve using Fourier series.

[0033] The present invention is further configured such that: the articulated vehicle includes a front vehicle, a rear vehicle, and a first hydraulic arm and a second hydraulic arm arranged symmetrically;

[0034] Define the hinge center, the distance from the two ends of the first hydraulic arm to the hinge center, and the distance from the two ends of the second hydraulic arm to the hinge center;

[0035] When the hinge angle changes from the initial state to the target angle:

[0036] The change in length of the first hydraulic arm is the difference between its initial length and the cosine function of the hinge angle;

[0037] The change in length of the second hydraulic arm is the difference between its initial length and the cosine function of the hinge angle.

[0038] The change in piston displacement and hinge angle of the hydraulic cylinder is related through a geometric constraint function.

[0039] The present invention is further configured to: use an adaptive tracking differentiator to process the desired piston displacement signal, and robustly extract its smoothed signal and derivatives of various orders:

[0040] Let the hinge angle input signal, which is mapped through the hinge structure, be... Through a dynamic parameter adjustment mechanism, the input signal is estimated in real time, and its smoothed signal is output. and its derivatives;

[0041] By performing an exponentially weighted average of the absolute values ​​of the input signal, the current value is combined with historical values ​​to filter out high-frequency noise and obtain a smooth signal.

[0042] The present invention is further configured to: combine the valve control model to design a time-varying sliding mode controller, and use the smoothing signal and derivatives of each order as the input reference for the time-varying sliding mode controller to complete the tracking control of the hydraulic cylinder piston.

[0043] The beneficial effects of this invention are:

[0044] 1. This invention smooths the trajectory obtained by traditional path planning and then transforms the vehicle body posture under path planning into the hinge angle changes of n sinusoidal trajectories based on coordinate system transformation and kinematic relationships, thus constructing a continuous and smooth biomimetic trajectory. This effectively eliminates the step change of the hinge angle, ensures that the hinge angle of the articulated vehicle is reduced in impact, improves the tracking accuracy of the vehicle under complex trajectories, enhances the steering safety of the articulated vehicle, and reduces the risk of instability of the articulated vehicle.

[0045] 2. Based on an adaptive tracking differentiator and a time-varying sliding mode controller, this invention can robustly adapt to the nonlinear friction characteristics of the hydraulic system, suppress noise interference, and achieve high-precision tracking of piston displacement, thereby reducing the risk of vehicle instability during steering and improving vehicle stability.

[0046] 3. Compared with traditional control methods, the present invention has significant improvements in many aspects, including control accuracy, vehicle stability, system adaptability, operational performance, operating efficiency, and overall performance. The present invention not only improves the flexibility and adaptability of articulated vehicles, but also reduces the dependence on driver skills, improves the driving experience, and enhances work efficiency and safety. Attached Figure Description

[0047] Figure 1 is an overall flowchart of the active articulation angle tracking control method for sinusoidal trajectory of articulated vehicles according to the present invention.

[0048] Figure 2 is a schematic diagram of the trajectory of the articulated vehicle of the present invention.

[0049] Figure 3 is a schematic diagram of the articulated vehicle articulation structure of the present invention.

[0050] Figure 4 is a schematic diagram of the hydraulic cylinder of the articulated vehicle articulation structure of the present invention.

[0051] Figure 5 is the controller flowchart.

[0052] Figure 6 shows the effect of the adaptive tracking differentiator.

[0053] Figure 7 shows the tracking effect of sliding mode control. Detailed Implementation

[0054] To facilitate a clear understanding of the technical means, creative features, objectives, and effects of this invention, the invention will be further described below in conjunction with specific illustrations.

[0055] As shown in Figure 1, an active articulation angle tracking control method for articulated vehicles based on sinusoidal trajectories includes the following steps: generating a global path → coordinate system transformation and desired attitude calculation → articulation angle curve generation and decomposition → establishing an articulation angle-piston displacement mapping → generating the desired piston displacement signal → time-varying sliding mode controller (SMC) tracking.

[0056] Specifically, in the global coordinate system, when the articulated vehicle turns, it acquires information about the surrounding environment, including at least obstacle information. In order to obtain the trajectory points after path planning, it uses LiDAR to scan the surrounding environment to obtain point cloud data and obtain obstacle information on the road surface in order to construct an environmental map.

[0057] Based on the starting point and the target point, a feasible initial path is generated using a hybrid A* algorithm. In order to use the hybrid A* algorithm for planning, the straight-line distance between the vehicle and the target point is also considered, and the vehicle's kinematic model is combined. Starting from the vehicle's current position, multiple child nodes are generated according to the preset expansion step size and different steering angles.

[0058] For each child node, check if it collides with an obstacle. If it does not collide, add it to the open list and record its cost function value. Select the node with the smallest cost function value from the open list as the current node and continue to expand the nodes until the target point is found or the open list is empty.

[0059] After finding the target point, an initial path from the starting point to the target point is generated by backtracking the parent node of each node, using the cost function of the hybrid A* algorithm:

[0060]

[0061] in, It is the total cost of node n. It is the actual distance traveled from the starting point to node n. It is a heuristic estimate of the distance from node n to the target point.

[0062] To achieve the division of the sinusoidal trajectory, the constraint range is appropriately expanded when performing path planning.

[0063] Specifically, since the hybrid A* algorithm has large constraints, the initial path is smoothed and optimized to improve feasibility and quality, and to ensure the continuity of vehicle kinematics.

[0064] Preferably, smoothing is performed using cubic spline interpolation. Based on the initial path generated by the hybrid A* algorithm, points obtained by sampling at unequal intervals are selected to guide the shape of the cubic spline interpolation curve.

[0065] The boundary conditions for cubic spline interpolation are determined based on the tangent direction and curvature at the starting point and the tangent direction and curvature at the ending point.

[0066] Based on the vehicle's kinematic model and actual driving constraints, set the constraints for cubic spline interpolation.

[0067] Based on the above conditions, a reasonable smoothness trade-off parameter for cubic spline interpolation should be selected.

[0068]

[0069] For a given sequence of control points , , ..., cubic spline interpolation function It can be represented as follows: where i = 0, 1, ..., n-1.

[0070] The global path is obtained by smoothing the initial path using cubic spline interpolation.

[0071] To complete the coordinate transformation and obtain the trajectory points of the global path, the trajectory points of the global path in the global coordinate system are transformed to the vehicle coordinate system, with the vehicle's current position as the origin and the vehicle's current heading angle as the rotation reference, representing a point in the path planning. Points corresponding to the vehicle coordinate system The following formula is used:

[0072]

[0073]

[0074] Calculate the planar displacement vector of the global pathpoint relative to the vehicle's current position, and further perform the following steps:

[0075]

[0076]

[0077] Perform translation and rotation transformations;

[0078] in, Represents the vehicle's current heading angle. This represents the relative distance of a path point along the vehicle's longitudinal axis in the vehicle coordinate system. Represents the relative horizontal distance.

[0079] Based on the transformed trajectory points, the desired attitude and position of the articulated vehicle in the local coordinate system are obtained.

[0080] As shown in Figure 2, since the serpentine movement of a snake can essentially be decomposed into sine waves with different phases in each segment of the body, this movement is smooth, continuous, and energy efficient. This embodiment of the invention draws on this principle and uses multiple sine components to synthesize the change curve of the hinge angle, thereby fundamentally avoiding step jumps.

[0081] Based on the kinematic model of the articulated vehicle, the desired attitude and position are converted into changes in the articulation angle. Based on the current steering wheel angle, vehicle wheelbase, and longitudinal distance from the rear vehicle's center of gravity to the articulation point, a first intermediate parameter and a second intermediate parameter are calculated. The first intermediate parameter is the product of the vehicle wheelbase and the steering wheel angle, and the second intermediate parameter is the sum of the vehicle wheelbase and the longitudinal distance. The first intermediate parameter is divided by the second intermediate parameter to obtain a ratio. The arctangent value of this ratio is then calculated using the following formula:

[0082]

[0083] in, Represents the vehicle's hinge angle. Represents the vehicle's wheelbase. Represents the steering wheel angle. This represents the longitudinal distance from the rear center of gravity to the articulation point in an articulated vehicle.

[0084] This embodiment employs a hinge angle-based tracking control method, which can obtain a mapping curve by testing the corresponding hinge angle at different steering wheel angles. .

[0085] Furthermore, the obtained hinge angle variation curve is decomposed using Fourier series:

[0086]

[0087] in, It is a curve showing the change of the hinge angle over time. It is the DC component. and These are the Fourier series coefficients, and N is the harmonic order being intercepted.

[0088] After decomposing the desired hinge angle change curve into N sinusoidal components, a continuous and smooth hinge angle trajectory is generated, which fundamentally eliminates the step change of the hinge angle, so that the hinge angle and its first derivative (rate of change) remain continuous and smooth.

[0089] As shown in Figure 3, in this embodiment, the articulated vehicle includes a front vehicle, a rear vehicle, a first hydraulic arm, and a second hydraulic arm. , These are the hinge points of the first hydraulic arm with the front and rear vehicles, respectively. , These are the hinge points of the second hydraulic arm with the front and rear vehicles, respectively. The hinge center of the hinged structure. Hinged point To the hinge center distance, Hinged point To the hinge center distance, Hinged point To the hinge center distance, Hinged point To the hinge center The distance.

[0090] Referring to this articulated structure, if the articulated vehicle is moving forward and then rotates by a certain angle, from the perspective of the fixed leading vehicle, the trailing vehicle will rotate by a certain angle as the articulated vehicle turns, and the center of gravity of the trailing vehicle will change from position 1 to position 2. The position, the hinge angle changes from 0 to an angle The two ends of the first hydraulic arm are formed by Change to The two ends of the second hydraulic arm are formed by Change to .

[0091] Then we have:

[0092] ;

[0093] ;

[0094] When the hinge angle changes by a certain angle, the change in the length of the first hydraulic arm is obtained as the difference between its initial length and the cosine function of the hinge angle.

[0095]

[0096] Similarly, the change in length of the second hydraulic arm is obtained as the difference between its initial length and the cosine function of the hinge angle:

[0097]

[0098] The hinge angle is obtained from the above. With hydraulic cylinder piston The relationship between them (taking the first hydraulic arm as an example for analysis):

[0099] .

[0100] Based on the mapping relationship between the hinge angle change and the hydraulic cylinder piston displacement, an adaptive tracking differentiator (ATD) is designed to convert the hinge angle trajectory into the desired piston displacement signal.

[0101] In a noisy environment, directly differentiating the noisy signal will amplify the noise and cause control input jitter. In order to track and control the hinge angle, an adaptive tracking differentiator is used to process the desired piston displacement signal and robustly extract its smooth signal and derivatives of each order.

[0102] Let the hinge angle input signal, which is mapped through the hinge structure, be... Through a dynamic parameter adjustment mechanism, real-time estimation of the input signal can be achieved in noisy environments, and a smoothed signal can be output. and its derivatives , , It can also adapt to parameter adjustments to cope with changes in signal amplitude. The design goal is:

[0103]

[0104] in, To track error boundaries.

[0105] By performing an exponentially weighted average of the absolute values ​​of the input signal, the current value is combined with historical values ​​to filter out high-frequency noise and obtain a smooth signal.

[0106] Signal amplitude is estimated using low-pass filtering:

[0107]

[0108] Where 0 < α < 1 is the smoothing factor. The larger the smoothing factor, the higher the weight of the current value and the lower the smoothness of the signal; the smaller the smoothing factor, the higher the smoothness, but it may lead to a slower response to signal abrupt changes.

[0109] Define the lower limit of amplitude:

[0110]

[0111] in This is the preset maximum amplitude value. This is to prevent the input signal amplitude from being too small, which could cause subsequent parameter adjustments to fail.

[0112] Define the normalized amplitude scaling factor:

[0113]

[0114] The normalized amplitude scaling factor is used to reflect the proportional relationship between the input signal amplitude and the maximum amplitude, providing a basis for subsequent parameter adjustments.

[0115] Dynamically adjust tracking speed parameters and filter parameters :

[0116]

[0117] in, and These are the baseline values ​​for the tracking speed parameter and the filtering parameter, respectively.

[0118] Define state variables (Smoothed signal) and (First derivative), construct the following control law:

[0119] Error calculation and segmented control:

[0120]

[0121]

[0122]

[0123] State update equation:

[0124]

[0125] in, .

[0126] The second and third derivatives can then be estimated using numerical differentiation:

[0127]

[0128]

[0129] When the input signal amplitude is large, the normalized amplitude scaling factor When the amplitude of the input signal is large, the tracking speed parameter and the filtering parameter are also increased accordingly, enabling the differentiator to quickly track changes in the input signal; conversely, when the amplitude of the input signal is small, the tracking speed parameter and the filtering parameter are decreased to improve tracking accuracy and filtering effect.

[0130] The adaptive tracking differentiator dynamically adjusts the tracking speed parameters and filtering parameters by estimating the amplitude of the input signal in real time, constructing a normalized proportional factor, and designing a piecewise control law based on the error threshold to suppress high-frequency noise interference in the hydraulic system and robustly extract the higher-order derivative signal of the displacement.

[0131] Design a piecewise control law based on an error threshold to generate a smooth displacement estimate and its first and second derivatives.

[0132] By using a piecewise control law, the adaptive tracking differentiator can effectively filter out high-frequency noise and obtain a smooth estimated signal when the error is small; when the error is large, it can quickly track changes in the input signal and avoid lag in the estimated signal due to slow tracking speed.

[0133] This dynamic adjustment mechanism enables the adaptive tracking differentiator to robustly estimate the higher-order derivatives of the desired piston displacement in a noisy environment, providing an accurate reference input for the sliding mode controller, solving the problem of high noise in direct differentiation, and improving the stability and accuracy of the control system.

[0134] As shown in Figure 4, in this embodiment, the hinge structure is driven by a valve-controlled asymmetric hydraulic cylinder. Indicates the flow rate of the rodless cavity. Indicates the flow rate in the rod cavity.

[0135] To simplify the control model, internal and external leakage of the hydraulic cylinder is ignored. Furthermore, during the operation of the hydraulic cylinder, changes in oil temperature will cause changes in the effective bulk modulus of elasticity, which is assumed to be a constant. The state-space equation of the system is obtained by modeling the valve-controlled asymmetric hydraulic cylinder as a whole.

[0136] Continuity equations for flow rates in the rod-side and rodless-side chambers of a hydraulic cylinder:

[0137]

[0138]

[0139] The dynamic equilibrium equation of a hydraulic cylinder:

[0140]

[0141] Based on the flow-input signal characteristic curve, the flow equation for the electro-hydraulic servo valve is as follows:

[0142]

[0143]

[0144] In the formula: ;

[0145] Let the extension and retraction displacement of the hydraulic cylinder piston be x, and the movement speed of the hydraulic cylinder piston be... Rod chamber pressure and rodless chamber pressure For the system's state variables, that is:

[0146] .

[0147] After rearranging, the state-space equation of the system can be obtained:

[0148]

[0149] Based on the obtained smooth signal and its derivatives , , By combining it with the valve-controlled asymmetric hydraulic cylinder model, the actual displacement and desired displacement of the piston in the valve-controlled asymmetric hydraulic cylinder are used as inputs to the sliding mode controller. The opening amount of the servo valve in the hydraulic cylinder is adjusted by the sliding mode control to achieve position tracking of the piston in the valve-controlled asymmetric hydraulic cylinder.

[0150] To accelerate the system's dynamic response and reduce chattering, this invention employs a time-varying sliding surface for the sliding mode controller design. The tracking effect of the adaptive tracking differentiator is shown in Figure 6.

[0151] As shown in Figure 5, a smoothed signal will be obtained. and its derivatives , , In the input diaphragm control, the output of the diaphragm control is fed back to the diaphragm control through the valve-controlled asymmetric hydraulic cylinder model, forming a closed-loop control. The tracking effect of the hydraulic cylinder diaphragm control is shown in Figure 7.

[0152] The implementation principle of this invention is as follows:

[0153] By mimicking the movement characteristics of snakes, the trajectory obtained by traditional path planning is smoothed and then decomposed into multiple sinusoidal signals using Fourier series to construct a continuous and smooth biomimetic trajectory. This effectively eliminates the abrupt changes in the articulation angle and improves the tracking accuracy of vehicles on complex trajectories.

[0154] Meanwhile, based on an adaptive tracking differentiator and a time-varying sliding mode controller, this invention can robustly adapt to the nonlinear friction characteristics of the hydraulic system, suppress noise interference, and achieve high-precision tracking of piston displacement, thereby reducing the risk of vehicle instability during steering and improving vehicle stability.

[0155] This invention demonstrates significant advantages in many aspects, including control precision, vehicle stability, system adaptability, operational performance, operating efficiency, and overall performance. Compared with traditional control methods, this invention not only improves the flexibility and adaptability of articulated vehicles but also reduces reliance on driver skills, improves the driving experience, and enhances operational efficiency and safety.

[0156] Furthermore, this invention effectively solves the problems of insufficient tracking accuracy, nonlinear friction effects of hydraulic systems, and vehicle instability risks existing in the prior art, providing a more reliable and efficient control method for the application of articulated vehicles in complex environments such as mining transportation, agricultural operations, and fire rescue.

[0157] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments, and various changes and modifications can be made without departing from the spirit and scope of the invention, all of which fall within the scope of protection claimed by the present invention. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for active articulation angle tracking control of articulated vehicles based on sinusoidal trajectories, characterized in that, Includes the following steps: A global path is generated based on the environmental information of the articulated vehicle, wherein the environmental information includes at least obstacle information; The trajectory points of the global path are obtained and transformed into the articulated vehicle coordinate system. Based on the transformed trajectory points, the desired attitude and position of the articulated vehicle in the local coordinate system are obtained. According to the kinematic model of the articulated vehicle, the desired attitude and position are converted into changes in the hinge angle. The desired hinge angle change curve is obtained through kinematic calculation and decomposed into N sinusoidal components using a Fourier series, generating a continuous and smooth hinge angle trajectory synthesized from multiple sinusoidal components. Based on the mechanical structural constraints of the articulated vehicle, a mapping relationship between the hinge angle change and the hydraulic cylinder piston displacement is established. Based on this mapping relationship, the continuous and smooth hinge angle trajectory is converted into a desired piston displacement signal. An adaptive tracking differentiator is used to process the desired piston displacement signal, robustly extracting its smooth signal and derivatives of various orders. Based on the desired piston displacement signal and combined with a valve control model, a time-varying sliding mode controller is designed to track and control the hydraulic cylinder piston.

2. The active articulation angle tracking control method for articulated vehicles based on a sinusoidal trajectory according to claim 1, characterized in that: Obstacle information is acquired using LiDAR to construct an environmental map. Based on the starting and target points, a feasible initial path is generated using a hybrid A* algorithm, and then smoothed using cubic spline interpolation to obtain the global path. Based on this initial path, points obtained through unequal-interval sampling are selected to guide the shape of the cubic spline interpolation curve. Boundary conditions for the cubic spline interpolation are determined based on the tangent direction and curvature at the starting and ending points. Finally, constraints for the cubic spline interpolation are set based on the vehicle's kinematic model and actual driving constraints.

3. The active articulation angle tracking control method for articulated vehicles based on a sinusoidal trajectory according to claim 2, characterized in that: Starting from the vehicle's current position, multiple child nodes are generated based on the preset expansion step size and different steering angles; For each child node, check if it collides with an obstacle. If it does not collide, add it to the open list and record its cost function value. Select the node with the smallest cost function value from the open list as the current node and continue to expand the nodes until the target point is found or the open list is empty. After finding the target point, generate the initial path from the starting point to the target point by backtracking the parent node of each node.

4. The active articulation angle tracking control method for articulated vehicles based on a sinusoidal trajectory according to claim 1, characterized in that, The process of converting the trajectory points of the global path to the articulated vehicle coordinate system includes the following steps: The vehicle's current position is taken as the origin of the coordinate system, and the vehicle's current heading angle is taken as the rotation reference. Calculate the planar displacement vector of the global path point relative to the vehicle's current position; Based on the vehicle's current heading angle, the planar displacement vector is rotated around the origin of the coordinate system; after transformation, the longitudinal and lateral relative distances of the trajectory points of the global path in the vehicle coordinate system are obtained.

5. The active articulation angle tracking control method for articulated vehicles based on a sinusoidal trajectory according to claim 1, characterized in that, The process of converting the desired attitude and position into changes in the hinge angle based on the kinematic model of the articulated vehicle includes the following steps: Calculating a first intermediate parameter and a second intermediate parameter based on the current steering wheel angle, vehicle wheelbase, and longitudinal distance from the rear vehicle's center of gravity to the hinge point; the first intermediate parameter is the product of the vehicle wheelbase and the steering wheel angle, and the second intermediate parameter is the sum of the vehicle wheelbase and the longitudinal distance; dividing the first intermediate parameter by the second intermediate parameter to obtain a ratio; calculating the arctangent of this ratio and outputting it as the hinge angle.

6. The active articulation angle tracking control method for articulated vehicles based on a sinusoidal trajectory according to claim 1, characterized in that: The articulated vehicle includes a front vehicle, a rear vehicle, and symmetrically arranged first and second hydraulic arms; the articulation center, the distance from the two ends of the first hydraulic arm to the articulation center, and the distance from the two ends of the second hydraulic arm to the articulation center are defined; when the articulation angle changes from the initial state to the target angle: the change in length of the first hydraulic arm is the difference between its initial length and the cosine function relationship of the articulation angle; the change in length of the second hydraulic arm is the difference between its initial length and the cosine function relationship of the articulation angle; the displacement of the hydraulic cylinder piston is related to the change in the articulation angle through a geometric constraint function.

7. The active articulation angle tracking control method for articulated vehicles based on a sinusoidal trajectory according to claim 1, characterized in that, Let the hinge angle input signal, which is mapped through the hinge structure, be... Through a dynamic parameter adjustment mechanism, the input signal is estimated in real time, and its smoothed signal is output. And its derivatives; by performing an exponentially weighted average of the absolute value of the input signal, the current value is combined with historical values ​​to filter out high-frequency noise and obtain a smooth signal.

8. The active articulation angle tracking control method for articulated vehicles based on a sinusoidal trajectory according to claim 7, characterized in that: Based on the valve control model, a time-varying sliding mode controller is designed. The smoothing signal and derivatives of each order are used as the input reference for the time-varying sliding mode controller to complete the tracking control of the hydraulic cylinder piston.

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