Force sense control method for virtual orthopedic surgery system

Abstract

The invention belongs to the technical field of man-machine interaction and force sense feedback, and particularly relates to a force sense control method for a virtual orthopedic surgery system, which comprises the following steps of: acquiring a displacement signal generated when an operator operates a force feedback master hand; tool stress in the virtual environment is calculated through a virtual model based on the displacement signal; acquiring an actual stress signal fed back by the force feedback master manipulator; calculating a force control error between the tool stress and the actual stress; based on the error, a sliding mode controller is adopted to generate a main control quantity; meanwhile, a disturbance observer is adopted to observe the lumped disturbance in the force feedback master hand system in real time, and a disturbance estimation value is obtained; performing low-pass filtering processing on the estimated value to generate an interference compensation amount; and finally, adding the main control quantity and the interference compensation quantity, synthesizing a final control quantity, and outputting the final control quantity to the force feedback master manipulator. Through combination of sliding mode control and observer-based feed-forward compensation, the authenticity and stability of haptic interaction of the virtual operation are remarkably improved.

Description

Technical Field

[0001] This invention belongs to the field of human-computer interaction and force feedback technology, specifically a force control method for a virtual orthopedic surgery system. Background Technology

[0002] Virtual orthopedic surgery uses computers and interactive devices to reproduce the visual and force information of real surgery, allowing doctors to experience the procedures of a real operation. Virtual orthopedic surgery systems need to consider the doctor's cognitive process in understanding visual and force information, and combine this with the doctor's previous knowledge and experience to establish near-realistic visual and force information, serving as the basis for providing visual and force feedback to the operator during virtual surgery.

[0003] However, existing systems face the following problems in achieving high-fidelity force perception reproduction:

[0004] 1. Inherent physical interference in force feedback devices: To achieve force feedback with multiple degrees of freedom and a large workspace, many systems employ wire drive (such as wire rope) mechanisms. This type of transmission inevitably introduces significant frictional nonlinearity, backlash, and deformation and hysteresis effects due to the flexibility of the wire rope during long-stroke motion. These factors constitute time-varying lumped interference within the system, directly affecting the accuracy and real-time performance of torque transmission, leading to a deviation between the output force and the desired force, i.e., "force perception distortion."

[0005] 2. Chattering Issues Arising from Highly Robust Control Strategies: To improve the system's anti-interference capability, nonlinear robust control methods such as sliding mode control have been introduced. Although sliding mode control is theoretically completely robust to matched disturbances, its discontinuous switching characteristics can excite unmodeled high-frequency dynamics in practical applications, leading to high-frequency chattering in the output force. This chattering not only severely weakens the realism and smoothness of the force perception, making it feel "stiff" or "vibrating," but may also accelerate the wear of mechanical components and even cause discomfort to the operator. Simply increasing the switching gain of sliding mode control to suppress disturbances will further exacerbate chattering, creating a contradiction.

[0006] Therefore, there is an urgent need in this field for a comprehensive control solution that can be deeply integrated into the architecture of a virtual surgical system, effectively observe and compensate for lumped interference caused by transmission mechanism and model errors, and significantly suppress output chattering that may be caused by the robust control algorithm itself, so as to provide force feedback with high realism, high smoothness and strong anti-interference capability under complex working conditions. Summary of the Invention

[0007] The purpose of this invention is to provide a force control method for a virtual orthopedic surgery system. To improve the realism of force feedback control, a sliding mode controller is used to enhance its robustness. An interference observer is designed to estimate and compensate for lumped disturbances in the system, alleviating the pressure on sliding mode control and suppressing system chattering. This method eliminates the influence of various interference factors in force feedback control, thereby improving the realism of force feedback control.

[0008] The technical solution adopted by the present invention to achieve the above objectives is: a force control method for a virtual orthopedic surgical system, comprising the following steps:

[0009] Step S1: Obtain the operation displacement signal generated by the operator's operation, output by the force feedback master hand; and input the operation displacement signal into the virtual model processing module to calculate the tool force in the virtual environment based on the pre-built virtual model. ;

[0010] Step S2: Obtain the actual force signal fed back by the force feedback main hand sensor ; Calculation tool under force Compared with actual force signals Force control error between ,Right now: ;

[0011] Step S3: Based on the force control error, a sliding mode controller is used to generate the main control quantity;

[0012] Step S4: Use an interference observer to detect lumped interference in the force feedback master system. Real-time observations were conducted to obtain estimated disturbance values. The interference estimate is filtered to generate the interference compensation value.

[0013] Step S5: Add the main control quantity and the disturbance compensation quantity to generate the final control quantity, and output it to the force feedback master hand to drive its movement and provide force feedback to the operator.

[0014] In step S3, the calculation and generation of the main control quantity using a sliding mode controller includes the following steps:

[0015] Step S3-1: Design the nonlinear sliding mode surface function Its expression is:

[0016]

[0017] in, It is a sliding surface function, representing the sliding state of the system; It is a systematic error; These are the parameters for the sliding surface design; is the derivative of e(t); n is the power, a design value related to the sliding surface;

[0018] Step S3-2: Based on the sliding surface function The power-approach law is designed as follows:

[0019]

[0020] in, For sliding surface functions The derivative; and , where is the reaching law gain coefficient, all of which are positive; m is the power, the design value related to the reaching law, used to adjust the convergence characteristics when moving away from or near the sliding surface. It is a symbolic function;

[0021] The power-approach law is obtained by combining linear terms. and power nonlinear terms This achieves smooth adjustment of the approach velocity: when the system state is far from the sliding surface, the nonlinear term dominates, accelerating convergence; when the system state is close to the sliding surface, the linear term dominates, smoothly decelerating, thus ensuring rapid convergence while reducing the chattering tendency caused by sudden changes in control quantity.

[0022] Step S3-3: Combining the dynamic model, virtual model, nonlinear sliding surface, and power-law approach of the force feedback master, solve for the master control quantity so that the system state converges to the equilibrium point along the sliding surface.

[0023] In step S4, the interference observer is used to monitor the lumped interference. Real-time observation includes the following steps:

[0024] Step S4-1: Based on the dynamic characteristics of the force feedback master, establish its state-space equation as the basic model for the design of the disturbance observer, expressed as:

[0025]

[0026] in, Let be the state vector of the system. The output vector of the system. To control the input, For the lumped interference to be observed, , , These are the state matrix, input matrix, and output matrix, respectively.

[0027] Step S4-2: Construct the disturbance observer, whose dynamic equation is:

[0028]

[0029] in, It is the gain matrix of the observer. It is a state vector The observed values, It is the system output. Observed values;

[0030] Step S4-3: The interference observer obtains the lumped interference by estimating the error in the observed state or the output error. The estimated value .

[0031] Step S4-3 specifically includes:

[0032] By handling state estimation error Or output estimation error To reconstruct the lumped interference Real-time estimates It is determined by the dynamic equation of the observation error and the inverse relationship;

[0033] a) Observation error The derivative is:

[0034]

[0035] b) Selecting an appropriate observer system matrix It is required that the real part of its eigenvalues ​​is negative, that is:

[0036]

[0037]

[0038] Where Re{} denotes taking the real part of the eigenvalue; It is the derivative of the observed values ​​of the lumped disturbance D. An adjustable parameter is provided to control the observer bandwidth, which is used to adjust the convergence speed of the observer, thereby ensuring the stability of the interference observer.

[0039] c) Based on state-space model With observer equations , for centralized interference Real-time estimates It is obtained by analyzing the dynamics of the observation error and calculating the system parameters in reverse;

[0040] d) The real-time estimate of the lumped disturbance obtained from real-time calculation. The output is sent to the filtering and compensation unit for subsequent filtering and compensation.

[0041] The force feedback master hand adopts a line drive method, and its transmission component includes a steel wire rope. The lumped interference includes at least the interference component caused by the friction and flexible deformation of the steel wire rope transmission, as well as load disturbance, power supply disturbance, and system disturbance with uncertain parameters.

[0042] In step S4, the filtering of the interference estimate to generate the interference compensation amount specifically involves:

[0043] a. Design and apply a low-pass filter to estimate the interference value. Process it;

[0044] b. The transfer function of the low-pass filter is:

[0045]

[0046] in The time constant determines the filter's response speed. It is the Laplace operator; the cutoff frequency is When frequency When, the observations pass through with almost no decay; when At that time, the observed value is decayed before passing through;

[0047] c. Converting the continuous filter into a difference equation yields the discretized formula:

[0048]

[0049] in, For the current filter input, For the corresponding filter output, These are the filter coefficients. Determine the weight of historical values ​​and current values. The sampling period.

[0050] A control system for a force feedback control method in a virtual orthopedic surgical system includes: a force feedback master hand, a virtual model processing module, a display module, and a controller module; wherein,

[0051] The force feedback master hand is used to collect the operation displacement signal and output force feedback based on the received final control quantity;

[0052] The virtual model processing module is used to receive the operation displacement signal and calculate and output the force on the tool based on the virtual model. ;

[0053] The controller module is used to receive the operation displacement signal and force feedback from the force feedback master hand, as well as the tool force sent from the virtual model processing module. The data is processed and synthesized into a final control output to the force feedback master.

[0054] The display module is used to provide visual images to the operator based on the output of the virtual model processing module.

[0055] The controller module includes:

[0056] An error calculation unit is used to receive the force signal of the tool. and the actual force signal from the force feedback master hand And calculate the force control error ;

[0057] The sliding mode control unit, connected to the error calculation unit, is used to generate the main control quantity based on the force control error, through a nonlinear sliding mode surface function and a power-law approaching law.

[0058] Interference observation unit, used for lumped interference of the force feedback master system. Perform real-time observation and output disturbance estimates. ;

[0059] The filtering compensation unit, connected to the interference observation unit, is used to process the interference estimate. Perform low-pass filtering and output interference compensation. ;

[0060] The control quantity synthesis unit is connected to both the sliding mode control unit and the filtering compensation unit, and is used to synthesize the main control quantity and the interference compensation quantity. The sums are combined, and the final control quantity is output to the force feedback master.

[0061] The present invention has the following beneficial effects and advantages:

[0062] 1. This invention introduces an interference observer to observe and estimate the lumped interference of the force feedback master hand system in real time, and uses the estimated value as a feedforward compensation amount, which can directly and actively counteract the influence of these interferences on the output force. Combined with the strong robustness of the sliding mode controller to residual interference and model uncertainty, the force signal output by the system can track the expected force calculated by the virtual environment with high precision, greatly reducing force distortion and allowing the operator to feel mechanical feedback that is closer to real surgical operation.

[0063] 2. This invention combines a sliding mode controller with a disturbance observer, with the disturbance observer undertaking the main disturbance compensation task, significantly reducing the dependence on the switching gain of the sliding mode controller. This allows the sliding mode control law to maintain strong robustness while employing a relatively smooth approaching law (such as a power-law approaching law), thereby fundamentally weakening the high-frequency switching characteristics of the control signal and greatly reducing the chattering of the final output torque. Combined with a low-pass filter to filter out observation noise, this further ensures the smoothness and continuity of the output force, eliminating the unpleasant tremor.

[0064] 3. The nonlinear sliding surface design and power-law approach employed in this invention enable the system to converge quickly even with large initial errors, improving the initial response speed of the force feedback. The feedforward compensation of the disturbance observer allows the system to cancel known disturbances in near real-time, reducing the lag in feedback control. These two factors combined significantly improve the dynamic performance of the force feedback system, making operation feel more responsive and rapid, enhancing the naturalness and immersion of the interaction.

[0065] 4. The control method provided by this invention exhibits strong robustness to system parameter variations and external disturbances. The introduction of a disturbance observer enhances the adaptability to time-varying disturbances, while sliding mode control ensures stable convergence under parameter perturbations. This composite control strategy enables the virtual surgical system to maintain stable force output performance when faced with different operating forces, speeds, and minor equipment wear, thereby improving the system's reliability and service life. Attached Figure Description

[0066] Figure 1 System configuration principle diagram of the virtual orthopedic surgical system of the present invention;

[0067] Figure 2 The control principle diagram inside the controller module of this invention. Detailed Implementation

[0068] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0069] like Figure 1 The diagram shown is a schematic diagram of the system structure of the virtual orthopedic surgery system of the present invention. The control system of the force control method for the virtual orthopedic surgery system of the present invention includes: a force feedback master hand, a virtual model processing module, a display module, and a controller module; wherein,

[0070] The force feedback master is used to acquire the operation displacement signal and output force feedback based on the received final control quantity;

[0071] The virtual model processing module is used to receive the operation displacement signal and calculate and output the force on the tool based on the virtual model. ;

[0072] The controller module receives the displacement signal and force feedback from the force feedback master hand, as well as the tool force sent from the virtual model processing module. The data is processed and synthesized into a final control output to the force feedback master.

[0073] like Figure 2 As shown, the controller module includes:

[0074] An error calculation unit is used to receive the force signal of the tool. and the actual force signal from the force feedback master hand And calculate the force control error ;

[0075] The sliding mode control unit, connected to the error calculation unit, is used to generate the main control quantity based on the force control error, through a nonlinear sliding mode surface function and a power-law approaching law.

[0076] Interference observation unit, used for lumped interference of the force feedback master system. Perform real-time observation and output disturbance estimates. ;

[0077] The filtering compensation unit, connected to the interference observation unit, is used to process the interference estimate. Perform low-pass filtering and output interference compensation. ;

[0078] Controller module such as Figure 2 As shown in the block diagram, in this embodiment, the sliding mode control unit calculates the control error sent by the error calculation unit. Real-time adjustment of control quantities, interference observation unit's lumped interference on the system Observations were conducted to obtain the observed values. After filtering by the filtering compensation unit, the result is... Perform feedforward compensation. It is a virtual model. The virtual model needs to provide the force to the human hand. It is the control quantity provided by the controller. It is the force perceived by the human hand. For manual force feedback, the displacement of the master hand is provided. It is a dynamic model of the force feedback master hand. It measures noise.

[0079] The control quantity synthesis unit is connected to both the sliding mode control unit and the filtering compensation unit, and is used to synthesize the main control quantity and the interference compensation quantity. The sums are combined, and the final control quantity is output to the force feedback master.

[0080] The display module is used to provide visual images to the operator based on the output of the virtual model processing module.

[0081] Among them, such as Figure 1 As shown, the area within the dashed box represents the force feedback interaction system. When the operator uses the force feedback main hand, the main hand provides feedback on the displacement of each degree of freedom. The controller calculates the force acting on the tool in the virtual environment based on the displacement and compares it with the real-time force feedback from the operator. The controller then provides a control amount based on the force control error to complete force tracking. The display provides a visual image of the surgical site model to the operator.

[0082] like Figure 1 As shown, a force control method for a virtual orthopedic surgery system includes the following steps:

[0083] Step S1: Obtain the operation displacement signal generated by the operator's operation, output by the force feedback master hand; and input the operation displacement signal into the virtual model processing module to calculate the tool force in the virtual environment based on the pre-built virtual model. ;

[0084] Step S2: Obtain the actual force signal fed back by the force feedback main hand sensor ; Calculation tool under force Compared with actual force signals Force control error between ,Right now: ;

[0085] Step S3: Based on the force control error, a sliding mode controller is used to generate the main control quantity;

[0086] Since the force feedback master uses linear transmission to transmit torque, the transmission wire rope has flexible characteristics, making it difficult to calculate the stiffness coefficient accurately. The system needs to eliminate the effects of inaccurate modeling and parameter variations. Sliding mode control is chosen as the control strategy, as it features strong robustness and fast convergence. Sliding mode control forces the system state variables to slide along a predefined phase trajectory to the desired point. This given phase trajectory is independent of changes in the controlled object parameters and external disturbances, resulting in strong anti-interference capabilities.

[0087] In step S3, the main control quantity is calculated and generated using a sliding mode controller, including the following steps:

[0088] Step S3-1: Design the nonlinear sliding mode surface function Its expression is:

[0089]

[0090] in, is the sliding mode surface function, representing the sliding mode state of the system; is the control error of the system; is the parameter for the design of the sliding mode surface; is the derivative of e(t); n is the power, a design value related to the sliding mode surface;

[0091]

[0092]

[0093]

[0094] The design goal of the sliding mode surface is to make the system state tend to the equilibrium state along the sliding mode surface within a finite time by selecting appropriate parameters, so as to achieve the stable control of the system. Designing a non - linear sliding mode surface can quickly make the system error converge. In the non - linear sliding mode surface, the high - order power of the error term can accelerate the speed of the system converging to the sliding mode surface. Especially in the initial stage, the change of the system state will be more rapid, thus improving the dynamic response.

[0095] Step S3 - 2: Based on the sliding mode surface function , design the power reaching law as:

[0096]

[0097] where, is the derivative of the sliding mode surface function ; and are reaching law gain coefficients, both being positive numbers; m is the power, a design value related to the reaching law, used to adjust the convergence characteristics when far from or close to the sliding mode surface, is the sign function;

[0098] is the sign function about s, and the expression is:

[0099]

[0100] The power reaching law combines a linear term and a power term, and can balance the convergence speed and smoothness. When m > 1, it accelerates convergence when far from the sliding mode surface; when 0 < m < 1, it smoothly decelerates when approaching.

[0101] The power reaching law realizes the smooth adjustment of the reaching speed by combining the linear term and the power non - linear term : when the system state is far from the sliding mode surface, the non - linear term dominates and accelerates convergence; when the system state is close to the sliding mode surface, the linear term dominates and smoothly decelerates, thus while ensuring fast convergence, reducing the chattering trend caused by the sudden change of the control quantity;

[0102] Step S3-3: Combining the dynamic model, virtual model, nonlinear sliding surface, and power-law approach of the force feedback master, solve for the master control quantity so that the system state converges to the equilibrium point along the sliding surface.

[0103] Although the nonlinearity of the sliding mode controller can effectively suppress the influence of disturbances on the system, allowing the system state to move along the sliding surface to the equilibrium point, due to the influence of discontinuous control, when the sliding mode controller forces the system to move on the sliding surface, the sign function... The system switches between positive and negative values, which can easily lead to chattering. Furthermore, as the controlled object becomes increasingly complex, system disturbances such as load disturbances, power supply disturbances, and parameter uncertainties are inevitable. Lumped system disturbances are a significant factor contributing to chattering. To effectively suppress these disturbances, traditional sliding mode control methods typically choose high switching gain, but in practical applications, this high gain is often limited. To address this issue and improve anti-interference capability without compromising system stability, while reducing unnecessary chattering, a disturbance observer is used to estimate common time-varying disturbances. Through this method, the disturbance is accurately estimated and used as a feedforward signal added to the controller output, thereby achieving precise compensation for time-varying disturbances and improving anti-disturbance capability.

[0104] Step S4: Use an interference observer to detect lumped interference in the force feedback master system. Real-time observations were conducted to obtain estimated disturbance values. The interference estimate is filtered to generate the interference compensation value.

[0105] Using an interference observer to monitor lumped interference Real-time observation includes the following steps:

[0106] Step S4-1: Based on the dynamic characteristics of the force feedback master, establish its state-space equation as the basic model for the disturbance observer design, and set the lumped disturbance of the system observed by the disturbance observer as... Because the system's sampling period is very small, it can... Treat it as a constant within a sampling period, i.e. The state-space equations of the system can be described as follows:

[0107]

[0108] in, Let be the state vector of the system. The output vector of the system. To control the input, For the lumped interference to be observed, , , These are the state matrix, input matrix, and output matrix, respectively.

[0109] Step S4-2: Construct the disturbance observer, whose dynamic equation is:

[0110]

[0111] in, It is the gain matrix of the observer. It is a state vector The observed values, It is the system output. Observed values;

[0112] Step S4-3: The interference observer obtains the lumped interference by estimating the error in the observed state or the output error. The estimated value Specifically, it includes the following steps:

[0113] By handling state estimation error Or output estimation error To reconstruct the lumped interference Real-time estimates It is determined by the dynamic equation of the observation error and the inverse relationship;

[0114] a) Observation error The derivative is:

[0115]

[0116] b) Selecting an appropriate observer system matrix It is required that the real part of its eigenvalues ​​is negative, that is:

[0117]

[0118]

[0119] Where Re{} denotes taking the real part of the eigenvalue; It is the derivative of the observed values ​​of the lumped disturbance D. An adjustable parameter is provided to control the observer bandwidth, which is used to adjust the convergence speed of the observer, thereby ensuring the stability of the interference observer.

[0120] The observations obtained directly from the interference observer include lumped interference as well as measurement noise from the sensors. The interference spectrum is located in the low-frequency band, while the measurement noise is in the high-frequency band. If such observations are directly used as feedforward compensation, it will increase the jitter of the controller output. This problem can be solved by adding a low-pass filter.

[0121] c) Based on state-space model With observer equations , for centralized interference Real-time estimates It is obtained by analyzing the dynamics of the observation error and calculating the system parameters in reverse;

[0122] d) The real-time estimate of the lumped disturbance obtained from real-time calculation. The output is sent to the filtering and compensation unit for subsequent filtering and compensation.

[0123] The force feedback master uses a wire drive method, and its transmission components include a steel wire rope. The lumped interference includes at least the interference component caused by friction and flexible deformation of the steel wire rope, as well as load disturbance, power supply disturbance, and system disturbance with uncertain parameters.

[0124] In step S4, the interference estimate is filtered to generate the interference compensation amount, specifically as follows:

[0125] a. Low-pass filters can filter out high-frequency interference. The performance of data directly observed by the observer is optimized after low-pass filtering, which can directly reflect the changing trend of generalized interference and improve the observation and compensation effect of interference observer.

[0126] b. The transfer function of the low-pass filter is:

[0127]

[0128] in The time constant determines the filter's response speed. It is the Laplace operator; the cutoff frequency is When frequency When, the observations pass through with almost no decay; when At that time, the observed value is decayed before passing through;

[0129] c. Converting the continuous filter into a difference equation yields the discretized formula:

[0130]

[0131] in, For the current filter input, For the corresponding filter output, These are the filter coefficients. Determine the weight of historical values ​​and current values. The sampling period.

[0132] Step S5: Add the main control quantity and the disturbance compensation quantity to generate the final control quantity, and output it to the force feedback master hand to drive its movement and provide force feedback to the operator.

[0133] In summary, this invention addresses the key technical challenge of force feedback distortion and high-frequency chattering caused by the physical transmission characteristics of the force feedback master hand (such as the friction and flexibility of the steel wire rope) and the uncertainty of the system model in virtual surgery, especially orthopedic surgical simulation systems. It proposes an innovative composite force feedback control method and corresponding system. The core of this method lies in the deep integration of robust sliding mode control with a disturbance observer technique capable of real-time estimation and feedforward compensation of lumped disturbances, supplemented by a low-pass filter to remove observation noise. This method achieves high-fidelity control commands to drive the force feedback device through precise force error calculation, robust control law generation based on nonlinear sliding surfaces and power-law approximation, and real-time observation and compensation of lumped disturbances such as transmission interference. This invention not only effectively counteracts the main sources of interference in principle, significantly improving the realism and accuracy of force feedback, but also fundamentally suppresses output chattering by reducing dependence on the sliding mode switching gain, ensuring the smoothness and comfort of force feedback interaction. The constructed system clearly defines the controller module architecture, which includes units for error calculation, sliding mode control, disturbance observation, filtering compensation, and control synthesis, providing a reliable hardware and software platform for the implementation of the aforementioned methods. This invention significantly enhances the immersion, realism, and reliability of virtual surgical training systems, possessing significant practical value for improving the quality and efficiency of surgical skills training. It also provides an advanced and effective solution for the application of human-computer interaction force feedback technology in the field of high-end medical simulation.

[0134] Those skilled in the art will understand that the above description is merely a preferred embodiment of the present invention, and the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways, even if such combinations or combinations are not explicitly described in this disclosure. This is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0135] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention. Clearly, those skilled in the art can make various alterations and modifications to the invention without departing from its spirit and scope. Thus, if these modifications and modifications of the invention fall within the scope of the claims and their equivalents, the invention is also intended to include these modifications and modifications.

Claims

1. A force control method for a virtual orthopedic surgical system, characterized in that, Includes the following steps: Step S1: Obtain the operation displacement signal generated by the operator's operation, output by the force feedback master hand; and input the operation displacement signal into the virtual model processing module to calculate the tool force in the virtual environment based on the pre-built virtual model. ; Step S2: Obtain the actual force signal fed back by the force feedback main hand sensor ; Calculation tool under force Compared with actual force signals Force control error between ,Right now: ; Step S3: Based on the force control error, a sliding mode controller is used to generate the main control quantity; Step S4: Use an interference observer to detect lumped interference in the force feedback master system. Real-time observations were conducted to obtain disturbance estimates. ; The interference estimate is filtered to generate the interference compensation value; Step S5: Add the main control quantity and the disturbance compensation quantity to generate the final control quantity, and output it to the force feedback master hand to drive its movement and provide force feedback to the operator.

2. The force control method for a virtual orthopedic surgical system according to claim 1, characterized in that, In step S3, the calculation and generation of the main control quantity using a sliding mode controller includes the following steps: Step S3-1: Design the nonlinear sliding surface function Its expression is: ； in, It is a sliding surface function, representing the sliding state of the system; It is a systematic error; These are the parameters for the sliding surface design; is the derivative of e(t); n is the power, a design value related to the sliding surface; Step S3-2: Based on the sliding surface function The power-approach law is designed as follows: ； in, For sliding surface functions The derivative; and , where is the reaching law gain coefficient, all of which are positive; m is the power, the design value related to the reaching law, used to adjust the convergence characteristics when moving away from or near the sliding surface. It is a symbolic function; The power-approach law is obtained by combining linear terms. and power nonlinear terms This enables smooth adjustment of the approach velocity: when the system state is far from the sliding surface, the nonlinear term dominates, accelerating convergence; when the system state is close to the sliding surface, the linear term dominates, smoothly decelerating, thus ensuring rapid convergence while reducing chattering tendencies caused by sudden changes in control quantities. Step S3-3: Combining the dynamic model, virtual model, nonlinear sliding surface, and power-law approach of the force feedback master, solve for the master control quantity so that the system state converges to the equilibrium point along the sliding surface.

3. The force control method for a virtual orthopedic surgical system according to claim 1, characterized in that, In step S4, the interference observer is used to monitor the lumped interference. Real-time observation includes the following steps: Step S4-1: Based on the dynamic characteristics of the force feedback master, establish its state-space equation as the basic model for the design of the disturbance observer, expressed as: ； in, Let be the state vector of the system. The output vector of the system. To control the input, For the lumped interference to be observed, , , These are the state matrix, input matrix, and output matrix, respectively. Step S4-2: Construct the disturbance observer, whose dynamic equation is: ； in, It is the gain matrix of the observer. It is a state vector The observed values, It is the system output. Observed values; Step S4-3: The interference observer obtains the lumped interference by estimating the error in the observed state or the output error. The estimated value .

4. The force control method for a virtual orthopedic surgical system according to claim 3, characterized in that, Step S4-3 specifically includes: By handling state estimation error Or output estimation error To reconstruct the lumped interference Real-time estimates It is determined by the dynamic equation of the observation error and the inverse relationship; a) Observation error The derivative is: ； b) Selecting an appropriate observer system matrix It is required that the real part of its eigenvalues ​​is negative, that is: ； ； Where Re{} denotes taking the real part of the eigenvalue; It is the derivative of the observed values ​​of the lumped disturbance D. An adjustable parameter is provided to control the observer bandwidth, which is used to adjust the convergence speed of the observer, thereby ensuring the stability of the interference observer. c) Based on state-space model With observer equations , for centralized interference Real-time estimates It is obtained by analyzing the dynamics of the observation error and calculating the system parameters in reverse; d) The real-time estimate of the lumped disturbance obtained from real-time calculation. The output is sent to the filtering and compensation unit for subsequent filtering and compensation.

5. The force control method for a virtual orthopedic surgical system according to claim 1, characterized in that, The force feedback master hand adopts a line drive method, and its transmission component includes a steel wire rope. The lumped interference includes at least the interference component caused by the friction and flexible deformation of the steel wire rope transmission, as well as load disturbance, power supply disturbance, and system disturbance with uncertain parameters.

6. The force control method for a virtual orthopedic surgical system according to claim 1, characterized in that, In step S4, the filtering of the interference estimate to generate the interference compensation amount specifically involves: a. Design and apply a low-pass filter to estimate the interference value. Process it; b. The transfer function of the low-pass filter is: ； in The time constant determines the filter's response speed. It is the Laplace operator; the cutoff frequency is When frequency When, the observations pass through with almost no decay; when At that time, the observed value is decayed before passing through; c. Converting the continuous filter into a difference equation yields the discretized formula: ； in, For the current filter input, For the corresponding filter output, These are the filter coefficients. Determine the weight of historical values ​​and current values. The sampling period.

7. The control system of the force control method for a virtual orthopedic surgical system according to claim 1, characterized in that, include: The system includes a force feedback main handpiece, a virtual model processing module, a display module, and a controller module; among which, The force feedback master hand is used to collect the operation displacement signal and output force feedback based on the received final control quantity; The virtual model processing module is used to receive the operation displacement signal and calculate and output the force on the tool based on the virtual model. ; The controller module is used to receive the operation displacement signal and force feedback from the force feedback master hand, as well as the tool force sent from the virtual model processing module. The data is processed and synthesized into a final control output to the force feedback master. The display module is used to provide visual images to the operator based on the output of the virtual model processing module.

8. The control system of the force control method for a virtual orthopedic surgical system according to claim 7, characterized in that, The controller module includes: An error calculation unit is used to receive the force signal of the tool. and the actual force signal from the force feedback master hand And calculate the force control error ; The sliding mode control unit, connected to the error calculation unit, is used to generate the main control quantity based on the force control error, through a nonlinear sliding mode surface function and a power-law approaching law. Interference observation unit, used for lumped interference of the force feedback master system. Perform real-time observation and output disturbance estimates. ; The filtering compensation unit, connected to the interference observation unit, is used to process the interference estimate. Perform low-pass filtering and output interference compensation. ; The control quantity synthesis unit is connected to both the sliding mode control unit and the filtering compensation unit, and is used to synthesize the main control quantity and the interference compensation quantity. The sums are combined, and the final control quantity is output to the force feedback master.

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