A quasi-zero stiffness automatic adjustable seat vibration isolation device and control method

Abstract

This invention relates to a quasi-zero stiffness automatic adjustable seat vibration isolation device, comprising: a base; a support seat disposed at the top of the inner cavity of the base; a positive stiffness mechanism disposed inside the base; a negative stiffness mechanism disposed inside the base and connected in parallel with the positive stiffness mechanism; a sensor; and a controller. In this invention, by integrating a feedforward compensator and a linear quadratic feedback controller within the controller, the feedforward control force can be calculated based on vibration and attitude signals using a radial basis function neural network to primarily counteract the cubic nonlinear stiffness force in the nonlinear restoring force of the seat vibration isolation device. The feedback control force is then calculated using a linear quadratic optimal controller for global disturbance optimization. The feedforward and feedback control forces are synthesized and subjected to semi-active constraints to obtain the desired control force, which is then mapped to a current signal output based on the inverse model of a magnetorheological damper. This solves the problems of poor control accuracy, system instability, and significant degradation of vibration isolation performance in existing devices under strongly nonlinear conditions.

Description

Technical Field

[0001] This invention relates to the field of vibration isolation technology, specifically to a quasi-zero stiffness automatic adjustable seat vibration isolation device and control method. Background Technology

[0002] Traditional linear vibration isolation seats mostly use a structure of coil springs or air springs connected in parallel with dampers. Their vibration isolation effect is only effective when the excitation frequency is higher than the system's natural frequency. While effective only when the frequency is doubled, it is difficult to isolate low-frequency vibrations commonly found in vehicles and construction machinery. To address this issue, related technologies have proposed quasi-zero stiffness vibration isolators that connect positive stiffness springs and negative stiffness mechanisms in parallel. Theoretically, this can reduce the system's natural frequency to an extremely low level, achieving efficient low-frequency vibration isolation.

[0003] However, existing quasi-zero stiffness seat vibration isolation devices still have the following technical problems: First, while existing devices can achieve quasi-zero stiffness characteristics, their equivalent dynamic stiffness is difficult to truly approach zero in actual operation. The effective vibration isolation range cannot be extended to the ultra-low frequency band, and the problems of poor low-frequency vibration isolation and easy resonance still exist, failing to fundamentally solve the low-frequency vibration isolation pain points of traditional linear vibration isolation systems. Second, existing quasi-zero stiffness isolators typically only achieve optimal vibration isolation performance under the design rated load. Once changes in occupant weight or posture adjustments cause the static load to deviate from the rated equilibrium position, the positive and negative stiffness matching relationship of the system is disrupted, the quasi-zero stiffness characteristics are significantly attenuated, and there is a lack of adaptive adjustment capability to cope with variable load conditions. Third, CN122014798A discloses a nonlinear stiffness automatic adjustment vibration isolation device and control method. Its negative stiffness mechanism adopts a three-layer uniformly distributed "link-tension spring" transmission unit design, and the dynamic adjustment component can adjust the working height of the positive stiffness mechanism. Adaptive optimization of vibration isolation performance is achieved through multi-sensor information fusion and a feedforward-feedback composite control strategy. However, the prior application still has the following shortcomings: its feedforward compensator mainly relies on the system's nonlinear stiffness model for calculation, which is highly dependent on the model's accuracy. When system parameters change or there are unmodeled dynamics, the feedforward compensation effect will significantly decrease; its LQR feedback controller's weight matrix adjustment mainly relies on offline tuning or simple rule adjustment, lacking the ability to adaptively optimize control parameters in real time; in addition, the control strategy has not been specifically optimized to suppress the human motion sickness sensitive frequency band (0.1-0.5Hz), making it difficult to meet the core requirements of driving comfort. Fourth, the controller in the existing device has a single function, only able to perform simple proportional adjustment of the damper based on a single signal such as the rate of change of angle, which is difficult to cope with the strong nonlinear characteristics in the dynamic model of the quasi-zero stiffness system, and cannot effectively offset external inertial disturbances and nonlinear stiffness forces inside the system, resulting in poor control accuracy, easy system instability, and a significant decrease in vibration isolation performance under strong nonlinear conditions. Fifth, existing vibration isolation systems typically employ full-frequency control strategies, which cannot precisely target and suppress motion sickness in the sensitive frequency range (0.1-0.5 Hz), resulting in ineffective mitigation of motion sickness caused by low-frequency vibrations. Sixth, existing systems lack a complete closed-loop adaptive control system; an effective closed-loop iteration is not formed between state acquisition, control calculation, and execution output, and the matching problem between control force and the actual physical characteristics of the actuator is often ignored, making it difficult for the system to achieve continuous, stable, and high-performance operation under complex working conditions.

[0004] Therefore, there is an urgent need to provide a quasi-zero stiffness automatic adjustment seat vibration isolation device and control method that can solve the above problems. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art, adapt to practical needs, and provide a quasi-zero stiffness automatic adjustment seat vibration isolation device and control method to solve the above-mentioned technical problems.

[0006] To achieve the objectives of this invention, the technical solution adopted is as follows: A quasi-zero stiffness automatic adjustable seat vibration isolation device includes: a base; a support seat disposed at the top of the inner cavity of the base for supporting the seat; a positive stiffness mechanism disposed inside the base for providing main vertical support positive stiffness; the positive stiffness mechanism includes a compression spring and a magnetorheological damper arranged in parallel, the upper end of the compression spring abutting the support seat, the lower end abutting the cylinder end of the magnetorheological damper, the piston rod end of the magnetorheological damper connected to the support seat, and the cylinder end connected to the inner bottom of the base; and a negative stiffness mechanism disposed inside the base and arranged in parallel with the positive stiffness mechanism for generating a stiffness similar to that of the seat. The positive stiffness mechanism has the opposite negative stiffness; a sensor is used to collect vibration and attitude signals; a controller is electrically connected to the magnetorheological damper and the sensor respectively; the controller is configured to: calculate the feedforward control force based on the vibration and attitude signals using a radial basis function neural network to mainly counteract the cubic nonlinear stiffness force in the nonlinear restoring force of the seat vibration isolation device, and calculate the feedback control force through a linear quadratic optimal controller for global disturbance optimization, synthesize the feedforward and feedback control forces and obtain the desired control force through semi-active constraints, and then map it into a current signal output according to the inverse model of the magnetorheological damper.

[0007] Furthermore, it also includes a support disposed inside the base, the support being fixedly connected to the bottom of the support base, and one end of the negative stiffness mechanism being connected to the lower surface of the support base through the support.

[0008] Furthermore, the negative stiffness mechanism includes a horizontal guide rail that is fixedly connected to the inner wall of the base and extends laterally. Two horizontal sliders are slidably connected to the horizontal guide rail. The two horizontal sliders are symmetrically arranged and located on both sides of the positive stiffness mechanism. A transverse tension spring is connected between the two horizontal sliders.

[0009] Furthermore, each of the horizontal sliders is hinged to a connecting rod via a rotating shaft, the other end of which extends upward and is hinged to a support.

[0010] Furthermore, the sensor includes a base acceleration sensor, a support base acceleration sensor, and an angle sensor; wherein the base acceleration sensor is connected to the base, the support base acceleration sensor is mounted on the support base, and the angle sensor is mounted on the rotating shaft.

[0011] Furthermore, it also includes a load adjustment mechanism, which is fixed to the inner bottom of the base and its output end is fixedly connected to the cylinder end of the magnetorheological damper, for driving the positive stiffness mechanism to vertically lift and lower to adjust its working height.

[0012] Furthermore, the load adjustment mechanism includes a base fixedly connected to the inner bottom wall of the base, a guide sleeve fixedly connected to the base, a vertical slide rod slidably connected inside the guide sleeve, a bearing platform fixedly connected to the top end of the vertical slide rod, and the bearing platform fixedly connected to the bottom end of the positive stiffness mechanism.

[0013] Furthermore, it also includes a rotating seat fixedly connected to the upper surface of the base, a lead screw rotatably connected to the top of the rotating seat, a threaded sleeve threadedly connected to the surface of the lead screw, and the top of the threaded sleeve fixedly connected to the support platform.

[0014] Furthermore, it also includes a support frame fixedly connected to the rotating seat, a horizontal transmission shaft rotatably connected to the inner wall of the support frame, a driven sprocket fixedly connected to the surface of the horizontal transmission shaft, a first helical gear fixedly connected to the surface of the horizontal transmission shaft, and a second helical gear fixedly connected to the bottom of the lead screw, with the first helical gear meshing with the second helical gear; it also includes a stepper motor, the output end of which is connected to a planetary reducer, and the output end of the planetary reducer is equipped with a driving sprocket, which is connected to the driven sprocket via a chain.

[0015] The present invention also provides a control method for any of the above-mentioned quasi-zero stiffness automatic adjustment seat vibration isolation devices, comprising the following steps: Step S1: Acquire and process system status signals The raw signals from the base acceleration sensor, support acceleration sensor, and angle sensor are collected in real time. After filtering, noise reduction, and integration, the displacement, velocity, and acceleration status information of the seat vibration isolation device are obtained.

[0016] Step S2: Calculate the feedforward control force using a feedforward compensator based on a radial basis function neural network. Measurable basic acceleration signals and real-time system state data are collected and input into the feedforward compensator integrated within the controller. The nonlinear dynamic characteristics of the system are fitted online using a radial basis function neural network to calculate the feedforward control force. The feedforward control force is decomposed into two compensation components: the first component is used to cancel the external inertial disturbance caused by the basic acceleration, and the second component is used to cancel the cubic nonlinear stiffness force in the nonlinear restoring force of the system, so that the dynamic characteristics of the system near the equilibrium point are approximately linearized. The physical realizability of the calculated feedforward force is verified according to the semi-active constraint principle: the feedforward force is effective only when the direction of the feedforward force and the direction of system motion meet the energy dissipation condition; otherwise, it is set to zero.

[0017] Step S3: After processing by a band-stop filter, the input is fed into a linear quadratic optimal controller to calculate the feedback control force. The state of the seat vibration isolation device is processed by a band-stop filter to suppress vibrations in the 0.1–0.5 Hz frequency band that is sensitive to motion sickness. A state-space model suitable for the design of a linear quadratic optimal controller is established, and the system state vector includes the vertical displacement and vertical velocity of the seat. A hybrid band-stop filter is introduced, which is composed of a low-pass filter and a high-pass filter. Its cutoff frequency is matched to the boundary of the sensitive frequency band of 0.1 to 0.5 Hz. The vibration component of this sensitive frequency band is extracted from the acceleration response of the base in real time using the band-stop filter. The extracted frequency band signal energy is used as the basis for adjusting the state weight matrix in the cost function of the linear quadratic optimal controller. The weight elements corresponding to the absolute acceleration state are increased to minimize the energy of this sensitive frequency band first, and the control energy is constrained by the weight matrix. The continuous-time algebraic Riccati equation is solved to obtain the optimal state feedback gain matrix, and then the feedback control law of the linear quadratic optimal controller is calculated. The linear quadratic optimal controller works in conjunction with the feedforward compensator. The feedforward compensator is responsible for quickly canceling known and measurable main disturbances and nonlinear forces, while the linear quadratic optimal controller is responsible for optimizing the system state and suppressing residual disturbances, model errors, and unmodeled dynamics that the feedforward cannot completely cancel.

[0018] Step S4: Adaptively tune the controller weight parameters using a multi-objective optimization algorithm. A multi-objective optimization algorithm is adopted to adaptively tune the feedforward gain, filter parameters, and weight matrix of the linear quadratic optimal controller in real time to adapt to different loads and road conditions. Using the root mean square values ​​of human body vibration frequency, suspension workspace, and human body acceleration as objective functions, a multi-objective optimization model is constructed to minimize these values. The objective functions cover the vertical displacement between the suspension and the human body, the vertical acceleration of the human body, and the human body vibration frequency within the sensitive frequency band. Through optimization algorithms, a set of Pareto optimal solutions is found by weighing multiple conflicting objectives, and parameters that satisfy engineering constraints are selected from the Pareto optimal solution set.

[0019] Step S5: Synthesize the total control force and verify the physical constraints. The feedforward control force and the feedback control force of the linear quadratic optimal controller are algebraically superimposed to obtain the total desired control force. The total control force is dynamically limited to ensure that its absolute value does not exceed the maximum output of the magnetorheological damper. The relative velocity of the vibration isolation mass is monitored in real time. When the direction of the desired control force is opposite to the direction of the motion velocity, the control force is in the energy dissipation quadrant of the damper, and the command is considered physically realizable and output. If the direction of the desired control force is the same as the direction of the motion velocity or causes the damper to do positive work, the command is set to zero, thus obtaining the physically realizable desired control force.

[0020] Step S6: Map the desired control force into a current signal Based on the physical characteristics of the magnetorheological damper, the desired control force is mapped to the corresponding input current, and the mapping relationship is obtained based on calibration experiments. The mapping process strictly follows the semi-active constraint principle, and the corresponding current is output only when the magnetorheological damper is in the energy-consuming condition; otherwise, the current is zero. A model is established to establish the relationship between the damping force, the input current, and the motion speed. The relevant parameters of this model are determined through experimental calibration and supplemented with current limiting protection.

[0021] Step S7: Drive the magnetorheological damper to output damping force The calculated current signal is output to the damper coil through a power amplifier, so that it generates a corresponding damping force that acts on the seat vibration isolation device to achieve real-time suppression of vibration.

[0022] Step S8: Monitor load changes and adaptively adjust the working height of the positive stiffness mechanism. Continuously monitor load changes. When the angle sensor detects that the static load system deviates from the rated balance position, drive the load adjustment mechanism to adjust the working height of the positive stiffness mechanism: the controller drives the stepper motor to operate, which drives the bearing platform to rise and fall, changes the working height of the positive stiffness mechanism, and returns the connecting rod to the horizontal state. The system returns to the near-zero stiffness balance position, achieving precise cancellation of positive and negative stiffness.

[0023] Step S9: Closed-loop operation and continuous optimization After the magnetorheological damper acts on the seat vibration isolation device, the system state changes. The support seat acceleration sensor, angle sensor, and base acceleration sensor continuously collect a new round of data and repeat the above steps S1 to S8 to form a complete closed-loop control loop, realizing the continuous and adaptive optimized operation of the seat vibration isolation device.

[0024] Beneficial effects: 1. This invention achieves near-zero stiffness mechanical characteristics with high static stiffness and low dynamic stiffness, significantly widening the low-frequency vibration isolation bandwidth and fundamentally solving the industry pain points of poor low-frequency vibration isolation effect and easy resonance in traditional linear vibration isolation systems. This invention employs a core mechanical framework consisting of a positive stiffness mechanism and a negative stiffness mechanism connected in parallel. The positive stiffness mechanism provides the main vertical support stiffness through a compression spring, ensuring the system possesses excellent static load-bearing capacity and structural stability. The negative stiffness mechanism utilizes a "linkage rod-tension spring" transmission design, which can stably generate negative stiffness opposite to the positive stiffness effect. The two mechanisms precisely cancel each other out near the static equilibrium position, causing the equivalent dynamic stiffness of the seat vibration isolation device to approach zero, achieving quasi-zero stiffness characteristics. This characteristic significantly reduces the system's natural frequency and drastically lowers the vibration isolation initiation frequency, extending the effective vibration isolation range to low and even ultra-low frequency bands. This completely breaks through the limitations of traditional linear vibration isolation systems, which only isolate systems with excitation frequencies higher than the system's natural frequency. The limitation of effective vibration isolation capability only after a certain period of time is eliminated, thus fundamentally avoiding the low-frequency vibration resonance problem that is common in operating scenarios such as vehicles and construction machinery, and significantly reducing the harm of harmful vibration to ride comfort and human health.

[0025] 2. This invention possesses load-adaptive stiffness adjustment capability, solving the core problem of significant performance degradation under variable loads in traditional passive quasi-zero stiffness vibration isolation systems, and ensuring stable output of quasi-zero stiffness characteristics under full load conditions. This invention incorporates a load adjustment mechanism linked to the positive stiffness mechanism, coupled with real-time status monitoring by an angle sensor, constructing a closed-loop adaptive system of "load change - position deviation - stiffness adjustment - balance reset". When changes in occupant weight, posture adjustments, or other operating conditions cause the static load system to deviate from its rated equilibrium position, the angle sensor accurately captures the deviation signal. The load adjustment mechanism then adjusts the vertical working height of the positive stiffness mechanism to correct the system's geometric configuration and the matching relationship between positive and negative stiffness, driving the system to quickly return to the near-zero stiffness state of its rated equilibrium position. This design completely breaks through the limitation of traditional passive near-zero stiffness vibration isolators, which can only achieve optimal vibration isolation performance under the design rated load. Regardless of load changes, it can automatically maintain the system's optimal near-zero stiffness operating point, ensuring the consistency, stability, and reliability of vibration isolation performance under different application scenarios, significantly improving the product's adaptability and engineering practicality.

[0026] 3. This invention proposes a composite control strategy combining RBF neural network feedforward pre-compensation and filtered-LQR state feedback, which solves the control challenges caused by the strong nonlinearity of quasi-zero stiffness suspension and magnetorheological damper, significantly improving the control accuracy, response speed, and robustness of the control system. This invention addresses the industry-wide pain point of strong nonlinear dynamics in quasi-zero stiffness systems by constructing a feedforward-feedback collaborative composite control architecture. Compared to the prior application CN122014798A, this invention has the following significant improvements: First, the feedforward compensator in the prior application mainly relies on the system's nonlinear stiffness model for calculation, which is highly dependent on the model's accuracy; this invention uses a radial basis function neural network to fit the nonlinear dynamic characteristics of the system online, achieving accurate compensation for the cubic term and higher-order nonlinear components in the nonlinear restoring force without requiring an accurate system model, significantly reducing the control algorithm's dependence on model accuracy and enhancing the system's adaptability to parameter changes. Second, the weight matrix adjustment of the LQR controller in the prior application mainly relies on offline tuning or simple rule adjustments; this invention uses a multi-objective optimization algorithm to adaptively tune the feedforward gain, filter parameters, and LQR weight matrix in real time, automatically optimizing among multiple conflicting performance indicators such as human body vibration frequency, suspension working space, and human body acceleration, adapting to different loads and road conditions. Thirdly, this invention innovatively incorporates a band-stop filter design into the control strategy and deeply integrates it with LQR control, achieving precise targeted suppression of the 0.1-0.5Hz frequency band sensitive to motion sickness, whereas previous applications did not specifically optimize for this sensitive frequency band. In summary, the composite control strategy of this invention is superior to existing technologies in terms of control accuracy, adaptability to operating conditions, and human comfort.

[0027] 4. This invention achieves precise targeted vibration suppression in the frequency band sensitive to motion sickness, overcoming the technical limitations of traditional full-frequency control that cannot accurately suppress vibrations at frequencies sensitive to human motion sickness. This significantly improves driving comfort and effectively alleviates motion sickness caused by low-frequency vibrations. This invention targets the critical sensitive frequency band of 0.1-0.5Hz for motion sickness as defined in the ISO 2631-1:1997 standard. It innovatively incorporates a band-stop filter design into the control strategy and deeply integrates it with linear quadratic optimal control. This allows for precise and deep targeted suppression of vibrations in this core sensitive frequency band while maintaining full-bandwidth vibration isolation. By specifically attenuating the vertical vibration energy that causes motion sickness in the vehicle-seat-human vibration energy transmission chain, it significantly reduces the vibration load transmitted to the human body in the sensitive frequency band. This alleviates the neural integration discomfort caused by low-frequency vibrations in the vestibular system from the source of vibration transmission, filling the technical gap in traditional seat vibration isolation systems that cannot simultaneously achieve full-band vibration isolation and precise vibration suppression in the human body's sensitive frequency band. It deeply aligns with the core design requirements of low motion sickness and high comfort in the development of intelligent driving and automotive electrification.

[0028] 5. This invention constructs a full-process closed-loop adaptive control system, which takes into account both the physical feasibility of the control force and the continuous optimized operation of the system under all operating conditions, ensuring the safe, stable, and high-performance operation of the vibration isolation system under complex operating conditions. The control method of this invention constructs a complete closed-loop control circuit from state acquisition, disturbance compensation, control calculation, constraint verification to execution output and adaptive adjustment. During the control process, by limiting the amplitude and verifying the direction of the synthesized total control force, and combining it with the calibrated inverse model of the magnetorheological damper, the theoretically desired control force is accurately mapped to a physically realizable input current signal. This strictly adheres to the semi-active control constraint principle, avoiding control failure caused by the mismatch between the theoretical control output and the physical characteristics of the actuator. Simultaneously, the system load and operating status are continuously monitored, and adaptive load stiffness adjustment and dynamic vibration closed-loop control are executed synchronously. The control output is iteratively optimized through real-time system state data collected by multiple sensors, achieving continuous adaptive optimization of the vibration isolation system. This fully closed-loop system ensures system stability under extreme conditions such as transient impact and resonance ride-through, while also achieving ultra-low frequency high-efficiency vibration isolation under steady-state driving conditions, achieving a comprehensive improvement in system safety, stability, and vibration isolation performance. Attached Figure Description

[0029] Figure 1 This is a three-dimensional structural diagram of the present invention; Figure 2 This is a three-dimensional structural schematic diagram of the positive stiffness mechanism of the present invention; Figure 3 This is a three-dimensional structural schematic diagram of the negative stiffness mechanism of the present invention; Figure 4 This is a three-dimensional structural schematic diagram of the load adjustment mechanism of the present invention; Figure 5 This is a flowchart of the control method for the quasi-zero stiffness seat vibration isolation device of the present invention.

[0030] The attached figures are labeled as follows: 1. Base; 2. Support base; 201. Support base accelerometer; 3. Positive stiffness mechanism; 301. Compression spring; 302. Magnetorheological damper; 4. Negative stiffness mechanism; 401. Angle sensor; 402. Horizontal guide rail; 403. Transverse tension spring; 404. Connecting rod; 405. Horizontal slider; 406. Rotating shaft; 5. Load adjustment mechanism; 501. Base accelerometer; 502. Stepper motor; 503. Bearing platform; 504. Vertical slide bar; 505. Base; 506. Planetary reducer; 507. Lead screw; 508. First helical gear; 509. Second helical gear; 510. Guide sleeve; 511. Drive sprocket; 512. Rotating seat; 513. Threaded sleeve; 514. Support frame; 515. Horizontal drive shaft; 516. Driven sprocket; 517. Chain; 6. Support. Detailed Implementation

[0031] The following is in conjunction with the appendix Figure 1-5 The present invention is further illustrated by the embodiments: Example 1 like Figure 1-4 As shown, a quasi-zero stiffness automatic adjustable seat vibration isolation device includes a base 1, a support 2, a positive stiffness mechanism 3, a negative stiffness mechanism 4, and a load adjustment mechanism 5.

[0032] In this embodiment, the base 1 is a rigid shell structure, and its bottom is fixed to the vehicle / equipment mounting plane to provide an overall mounting base; the support 2 is located at the top of the inner cavity of the base 1, and its upper surface is used to install the seat cushion and backrest, and its lower surface is connected to the upper end of the positive stiffness mechanism 3 and the negative stiffness mechanism 4 respectively, for bearing the load of the seat and the occupant; the support 2 is equipped with a support accelerometer 201.

[0033] A positive stiffness mechanism 3 is located inside the base 1 and provides positive stiffness for the main vertical support. A negative stiffness mechanism 4 is located inside the base 1 and is connected in parallel with the positive stiffness mechanism 3 to generate negative stiffness opposite to that of the positive stiffness mechanism 3. A load adjustment mechanism 5 is fixedly connected to the inner bottom wall of the base 1, and its output end is fixedly connected to the lower end of the positive stiffness mechanism 3. It is used to drive the positive stiffness mechanism 3 to move vertically up and down to adjust its working height. By adjusting the working height of the positive stiffness mechanism 3, the positive stiffness value it provides cancels out the negative stiffness value of the negative stiffness mechanism 4 at the system equilibrium position, thereby making the system exhibit quasi-zero stiffness characteristics.

[0034] With the above configuration, the support base 2 serves as the load-bearing and transmission component, the positive stiffness mechanism 3 provides the main static support capacity, and the negative stiffness mechanism 4 generates the opposite mechanical effect to the positive stiffness mechanism 3. The positive stiffness mechanism 3 and the negative stiffness mechanism 4 are connected in parallel. With the load adjustment mechanism 5 adjusting the working height of the positive stiffness mechanism 3, the positive and negative stiffness are precisely canceled at the system equilibrium position, so that the system exhibits quasi-zero stiffness characteristics, thereby obtaining extremely low dynamic stiffness and excellent vibration isolation performance, achieving the dual advantages of "high load-bearing capacity and strong vibration reduction".

[0035] It also includes a controller and sensors for acquiring vibration and attitude signals. The controller is electrically connected to the magnetorheological damper 302 and the sensors.

[0036] The controller is configured to: calculate a feedforward control force based on a radial basis function neural network according to the aforementioned vibration and attitude signals, primarily to counteract the cubic nonlinear stiffness force in the nonlinear restoring force of the seat vibration isolation device; calculate a feedback control force through a linear quadratic optimal controller for global disturbance optimization; synthesize the feedforward and feedback control forces and obtain the desired control force through semi-active constraints; and then map the desired control force into a current signal output according to the inverse model of the magnetorheological damper 302. The positive stiffness mechanism 3 includes a compression spring 301 and a magnetorheological damper 302 arranged in parallel, and is vertically arranged between the support base 2 and the load adjustment mechanism 5.

[0037] Specifically, the compression spring 301 is a cylindrical helical compression spring, with its upper end abutting against the lower surface of the support base 2 and its lower end abutting against the cylinder of the magnetorheological damper 302, so as to provide the main support stiffness and load-bearing capacity in the vertical direction.

[0038] The magnetorheological damper 302 is arranged coaxially or parallel to the compression spring 301. The cylinder of the magnetorheological damper 302 is fixedly installed on the upper surface of the load adjustment mechanism 5, and its piston rod end is connected to the support seat 2. The damping force of the magnetorheological damper 302 is continuously adjustable and is used to dissipate vibration energy and suppress resonance and impact. The magnetorheological damper 302 is electrically connected to the controller through a wire, receives the current signal output by the controller, and outputs the corresponding damping force.

[0039] It also includes a support 6 disposed inside the base 1, which is fixedly connected to the bottom of the support base 2. One end of the negative stiffness mechanism 4 is connected to the lower surface of the support base 2 through the support 6. The support 6 serves as a connecting transition component between the negative stiffness mechanism 4 and the support base 2, ensuring effective force transmission and precise motion guidance.

[0040] The negative stiffness mechanism 4 adopts a linkage-tension spring transmission structure, including a horizontal guide rail 402, two horizontal sliders 405, a transverse tension spring 403, two rotating shafts 406, and two connecting rods 404.

[0041] A horizontal guide rail 402 is fixed to the inner wall of the base 1 and extends laterally. Two horizontal sliders 405 are slidably connected to the horizontal guide rail 402 and are located on the left and right sides of the positive stiffness mechanism 3, forming a symmetrical arrangement. A transverse tension spring 403 is connected between the two horizontal sliders 405. The transverse tension spring 403 is arranged laterally to provide horizontal restoring force.

[0042] Each horizontal slider 405 is hinged to a connecting rod 404 via a rotating shaft 406. The other end of the connecting rod 404 extends upward and is hinged to the support 6. An angle sensor 401 is installed at the rotating shaft 406 to detect the rotation angle of the connecting rod 404.

[0043] Thus, the negative stiffness mechanism 4 and the positive stiffness mechanism 3 are connected in parallel to form a stiffness system. When the support 2 undergoes vertical displacement, the connecting rod 404 converts the vertical motion into the lateral movement of the horizontal slider 405 along the horizontal guide rail 402, stretching or releasing the lateral tension spring 403, producing a negative stiffness effect opposite to that of the positive stiffness mechanism 3.

[0044] The load adjustment mechanism 5 is installed at the inner bottom of the base 1 and is used to drive the positive stiffness mechanism 3 to vertically lift and lower to adjust its working height. The load adjustment mechanism 5 includes a stepper motor 502, a support platform 503, a vertical slide bar 504, a base 505, a planetary reducer 506, a chain 517, a lead screw 507, a first helical gear 508, a second helical gear 509, and a guide sleeve 510.

[0045] The base 505 is fixedly connected to the inner bottom wall of the base 1, the guide sleeve 510 is fixedly connected to the upper surface of the base 505, the vertical slide rod 504 can slide along the guide sleeve 510, the support platform 503 is fixedly connected to the top of the vertical slide rod 504, and the support platform 503 is fixedly connected to the bottom end of the positive stiffness mechanism 3.

[0046] It also includes a rotating seat 512, which is fixedly connected to the upper surface of the base 505. A lead screw 507 is rotatably connected to the top of the rotating seat 512. A threaded sleeve 513 is threadedly connected to the surface of the lead screw 507. The top of the threaded sleeve 513 is fixedly connected to the support platform 503.

[0047] It also includes a support frame 514, which is fixedly connected to the rotating seat 512. A horizontal drive shaft 515 is rotatably connected to the inner wall of the support frame 514. A driven sprocket 516 is fixedly connected to the surface of the horizontal drive shaft 515. The output end of the stepper motor 502 is connected to the input end of the planetary reducer 506. A drive sprocket 511 is installed at the output end of the planetary reducer 506. The drive sprocket 511 is connected to the driven sprocket 516 through a chain 517.

[0048] The first helical gear 508 is fixedly connected to the surface of the horizontal transmission shaft 515, and the second helical gear 509 is fixedly connected to the lead screw 507, with the first helical gear 508 and the second helical gear 509 meshing.

[0049] In this embodiment, the load adjustment mechanism 5 is installed at the bottom of the base 1, and its output end is connected to the lower end of the positive stiffness mechanism 3. It is used to adjust the working height of the positive stiffness mechanism 3 so that the seat vibration isolation device returns to the rated equilibrium position under variable load and maintains the quasi-zero stiffness characteristics. The controller detects the equilibrium position of the seat vibration isolation device in real time through the angle sensor 401. When the load change causes the seat vibration isolation device to deviate from the rated quasi-zero stiffness equilibrium position, the controller outputs a control command to drive the stepper motor 502 to run. After the torque is amplified by the planetary reducer 506, it drives the horizontal transmission shaft 515 to rotate synchronously through the chain drive. After the first helical gear 508 and the second helical gear 509 reverse the transmission, they drive each lead screw 507 to rotate synchronously, driving the support platform 503 to rise and fall vertically, adjusting the vertical working height of the positive stiffness mechanism 3 until the seat vibration isolation device returns to the rated quasi-zero stiffness equilibrium position. Then, the stepper motor 502 is de-energized and locked, completing the adaptive stiffness adjustment under variable load.

[0050] The sensors used to collect vibration and attitude signals include at least the following three types: a base acceleration sensor 501 is mounted on the upper surface of the base 505 and connected to the base 1, used to collect the basic vibration acceleration signal (i.e., basic excitation) from the vehicle or equipment mounting plane; a support acceleration sensor 201 is fixedly connected to the support 2, used to collect the vertical vibration acceleration signal of the support 2 in real time and transmit the signal to the controller as the basis for system status feedback; an angle sensor 401 is mounted on the rotating shaft 406, which detects the tilt angle of the connecting rod 404 / the attitude of the support 2 in real time to determine whether the system deviates from the rated balance position; all sensor signals are filtered and amplified by the signal conditioning circuit before being input to the controller.

[0051] Example 2 like Figure 5 As shown, the present invention also provides a control method for a quasi-zero stiffness automatic adjustment vibration isolation seat vibration isolation device for any of the above claims, comprising the following steps: Step S1: Acquire and process system status signals The raw signals from the base acceleration sensor 501, the support acceleration sensor 201, and the angle sensor 401 are collected in real time. After filtering, noise reduction, and integration, the displacement, velocity, acceleration, and other status information of the seat vibration isolation device are obtained.

[0052] Step S2: Calculate the feedforward control force based on the feedforward compensator to counteract disturbances and nonlinear stiffness forces. Measurable basic acceleration signals and real-time system state data are acquired and input into the feedforward compensator integrated within the controller. The nonlinear dynamic characteristics of the system are then fitted online using a radial basis function (RBF) neural network. The specific implementation process is as follows: A three-layer RBF neural network structure is pre-configured in the controller: the input layer is set, corresponding to the system state quantity, the relative displacement u of the support; the number of hidden layer nodes is set (adjusted according to the nonlinear fitting accuracy requirements), and a Gaussian function is used as the radial basis function; the center vector of each node in the hidden layer is pre-initialized. Width parameters and output layer weight vector The output layer weights are initialized to 0; the relative displacement u of the support is acquired in real time, filtered, and normalized before being input to the input layer of the RBF neural network. For each hidden layer node... Calculate the input vector With the center vector of this node Euclidean distance Substituting the distance into the Gaussian radial basis function, the output value of the hidden layer node is calculated. :

[0053] Calculate the outputs of all hidden layer nodes sequentially to form the hidden layer output vector. (n is the number of hidden layer nodes); the hidden layer output vector With the output layer weight vector By performing linear weighted summation, the nonlinear restoring force value of the system fitted by the RBF neural network is obtained. :

[0054] This value represents the system's nonlinear restoring force. Online fitting results for cubic terms and higher-order nonlinear components; acquisition of actual system output acceleration signals, and calculation of the error between the RBF-fitted output and the actual nonlinear force of the system. The Least Mean Square (LMS) algorithm is used to adjust the output layer weights in real time based on the error. To minimize the sum of squared fitting errors, the weight update formula is:

[0055] in Let k be the learning rate and k be the current sampling time; by continuously updating the weights online, the RBF neural network adaptively tracks the changes in the nonlinear characteristics of the system; calculate the basic inertial disturbance compensation components. ( The equivalent mass of the seat and occupants. Based on the fundamental acceleration, the nonlinear force compensation component obtained by fitting with RBF is... Superimposed, the total feedforward control force is obtained. This makes the dynamic characteristics of the system near the equilibrium point approximately linear; the physical realizability of the calculated feedforward force is verified according to the semi-active constraint principle: the feedforward force is only effective when the direction of the feedforward force and the direction of system motion satisfy the energy dissipation condition, otherwise it is set to zero.

[0056] Step S3: After processing by a band-stop filter, the input is fed into the LQR controller to calculate the feedback control force. The state of the seat vibration isolation device is processed by a band-stop filter to suppress vibrations in the 0.1–0.5Hz frequency band, which is sensitive to motion sickness. A state-space model suitable for LQR design is established, with the system state vector set as follows: ,in This represents the vertical displacement of the seat. For the vertical velocity, the linearized state equation of the system can be expressed as: .

[0057] Where A is the system matrix and B is the input matrix. This is the output force of the LQR feedback controller.

[0058] A hybrid band-stop filter is introduced, which is composed of a low-pass filter (LPF) and a high-pass filter (HPF), with the following transfer functions:

[0059] In the formula, , These are the angular frequencies of the low-pass and high-pass filters, respectively. , For the corresponding low-frequency and high-frequency cutoff frequencies, the values ​​are the same as... Sensitive frequency band boundary matching.

[0060] The vibration components in the 0.1-0.5Hz frequency band were extracted in real time from the acceleration response of the base using a band-stop filter. The extracted frequency band signal energy is used as the state weight matrix in the LQR cost function for adjustment. Based on this, increase the matrix The weights corresponding to the absolute acceleration states are given by the following cost function:

[0061] By designing a cost function J, the energy of the sensitive frequency band is minimized first, and a weight matrix R is used to constrain and control the energy. The continuous-time algebraic Riccati equation is solved to obtain a symmetric positive definite matrix P, and the optimal state feedback gain matrix is ​​calculated. The LQR feedback control law is The LQR feedback controller works in conjunction with the feedforward compensator. The feedforward compensator is responsible for quickly canceling known and measurable major disturbances and nonlinear forces, while the LQR feedback is responsible for optimizing the system state and suppressing residual disturbances, model errors, and unmodeled dynamics that the feedforward could not completely cancel.

[0062] Step S4: Adaptively tune the controller weight parameters using a multi-objective optimization algorithm. Multi-objective optimization algorithms (such as NSGA-II and particle swarm optimization) are used to adaptively tune the feedforward gain, filter parameters, and LQR weight matrix in real time to adapt to different loads and road conditions.

[0063] Using the root mean square values ​​of human body vibration frequency (HBVF), suspension workspace (SWS), and human body acceleration (HA) as objective functions, a multi-objective optimization model is constructed to minimize these values. The objective function is expressed as follows:

[0064] in, , These represent the vertical displacement of the suspension and the human body, respectively. The vertical acceleration of the human body The human body vibration frequencies within the sensitive frequency band (0.1–0.5 Hz) The number of sampling points; through optimization algorithms, a set of Pareto optimal solutions can be found among the above multiple conflicting objectives, rather than a single optimal solution, and a set of parameters that satisfy all engineering constraints can be selected from the set of Pareto optimal solutions.

[0065] Step S5: Synthesize the total control force and verify the physical constraints. The feedforward control force and the LQR feedback control force are algebraically superimposed to obtain the total desired control force. for:

[0066] The total control force is dynamically limited to ensure that its absolute value does not exceed the maximum output force of the magnetorheological damper 302; the relative velocity of the vibration isolation mass is monitored in real time. When the direction of the desired control force is opposite to the direction of the motion velocity (i.e.) When the control force is in the damper's "energy dissipation quadrant," the command is considered physically realizable and is output; if If the command is set to zero, the desired physical control force is obtained.

[0067] Step S6: Map the desired control force into a current signal Based on the physical characteristics of the magnetorheological damper 302, the desired control force is mapped to the corresponding input current, and the mapping relationship is obtained based on calibration experiments. The mapping process strictly follows the semi-active constraint principle, outputting the corresponding current only when the magnetorheological damper 302 is in an energy-consuming condition; otherwise, the current is zero. A model is established to show the relationship between the damping force, the input current, and the motion velocity.

[0068] in It is the output force of the magnetorheological damper 302; It is the input current; It is the displacement of magnetorheological damper 302; , , and These are model parameters determined through experimental calibration; It is the ratio of the hysteresis critical velocity to the critical displacement, supplemented by current limiting protection.

[0069] Step S7: Drive the magnetorheological damper to output damping force The calculated current signal is output to the damper coil through a power amplifier, so that it generates a corresponding damping force that acts on the seat vibration isolation device to achieve real-time suppression of vibration.

[0070] Step S8: Monitor load changes and adaptively adjust the working height of the positive stiffness mechanism. Continuously monitor load changes; when angle sensor 401 detects that the static load system deviates from the rated balance position (i.e., angle) The controller drives the stepper motor 502 to operate, which in turn raises and lowers the support platform 503, changing the working height of the rigidity mechanism 3 and causing the connecting rod 404 to return to a horizontal state (angle). The system returns to the near-zero stiffness equilibrium position, with the positive and negative stiffness precisely canceled out.

[0071] Step S9: Closed-loop operation and continuous optimization After the magnetorheological damper 302 acts on the seat vibration isolation device, the system state changes. The support seat acceleration sensor 201, angle sensor 401, and base acceleration sensor 501 continuously collect a new round of data and repeat the above steps S1 to S8 to form a complete closed-loop control circuit, so as to realize the continuous and adaptive optimization operation of the seat vibration isolation device.

[0072] It should be noted that the aforementioned actuator refers to the magnetorheological damper 302.

[0073] The embodiments disclosed herein are preferred embodiments, but are not limited thereto. Those skilled in the art can readily grasp the spirit of the present invention based on the above embodiments and make different extensions and variations, but as long as they do not depart from the spirit of the present invention, they are all within the protection scope of the present invention.

Claims

1. A quasi-zero stiffness automatic adjustable seat vibration isolation device, characterized in that, include: Base (1); Support base (2), located at the top of the inner cavity of base (1), is used to support the seat; A positive stiffness mechanism (3) is disposed inside the base (1) to provide positive stiffness of the main support in the vertical direction; The positive stiffness mechanism (3) includes a compression spring (301) and a magnetorheological damper (302) arranged in parallel. The upper end of the compression spring (301) abuts against the support base (2), and the lower end abuts against the cylinder end of the magnetorheological damper (302). The piston rod end of the magnetorheological damper (302) is connected to the support base (2), and the cylinder end is connected to the inner bottom of the base (1). A negative stiffness mechanism (4) is disposed inside the base (1) and connected in parallel with the positive stiffness mechanism (3) to generate a negative stiffness opposite to that of the positive stiffness mechanism (3); Sensors are used to collect vibration and attitude signals; The controller is electrically connected to the magnetorheological damper (302) and the sensor, respectively; The controller is configured to: calculate a feedforward control force based on a radial basis function neural network according to the vibration and attitude signals to counteract the cubic nonlinear stiffness force in the nonlinear restoring force of the seat vibration isolation device, and calculate a feedback control force through a linear quadratic optimal controller (LQR) to suppress residual disturbances. The feedforward and feedback control forces are combined and then subjected to semi-active constraints to obtain the desired control force, which is then mapped to a current signal output according to the inverse model of the magnetorheological damper (302).

2. The quasi-zero stiffness automatic adjustable seat vibration isolation device as described in claim 1, characterized in that: It also includes a support (6) disposed inside the base (1), the support (6) being fixedly connected to the bottom of the support base (2), and one end of the negative stiffness mechanism (4) being connected to the lower surface of the support base (2) through the support (6).

3. The quasi-zero stiffness automatic adjustable seat vibration isolation device as described in claim 2, characterized in that: The negative stiffness mechanism (4) includes a horizontal guide rail (402) that is fixedly connected to the inner wall of the base (1) and extends laterally. Two horizontal sliders (405) are slidably connected on the horizontal guide rail (402). The two horizontal sliders (405) are symmetrically arranged and located on both sides of the positive stiffness mechanism (3). A transverse tension spring (403) is connected between the two horizontal sliders (405).

4. The quasi-zero stiffness automatic adjustable seat vibration isolation device as described in claim 3, characterized in that: Each of the horizontal sliders (405) is hinged to a connecting rod (404) via a rotating shaft (406), the other end of which extends upward and is hinged to a support (6).

5. The quasi-zero stiffness automatic adjustable seat vibration isolation device as described in claim 4, characterized in that: The sensors include a base acceleration sensor (501), a support base acceleration sensor (201), and an angle sensor (401); wherein, The base acceleration sensor (501) is connected to the base (1), the support base acceleration sensor (201) is installed on the support base (2), and the angle sensor (401) is installed on the rotating shaft (406).

6. The quasi-zero stiffness automatic adjustable seat vibration isolation device as described in claim 1, characterized in that: It also includes a load adjustment mechanism (5), which is fixed to the inner bottom of the base (1), and its output end is fixedly connected to the cylinder end of the magnetorheological damper (302) to drive the positive stiffness mechanism (3) to rise and fall vertically to adjust its working height.

7. The quasi-zero stiffness automatic adjustable seat vibration isolation device as described in claim 6, characterized in that: The load adjustment mechanism (5) includes a base (505) fixedly connected to the inner bottom wall of the base (1), a guide sleeve (510) fixedly connected to the base (505), a vertical slide rod (504) slidably connected inside the guide sleeve (510), a bearing platform (503) fixedly connected to the top of the vertical slide rod (504), and the bearing platform (503) fixedly connected to the bottom end of the positive stiffness mechanism (3).

8. The quasi-zero stiffness automatic adjustable seat vibration isolation device as described in claim 7, characterized in that: It also includes a rotating seat (512) fixedly connected to the upper surface of the base (505), the top of the rotating seat (512) is rotatably connected to a lead screw (507), the surface of the lead screw (507) is threadedly connected to a threaded sleeve (513), and the top of the threaded sleeve (513) is fixedly connected to the support platform (503).

9. The quasi-zero stiffness automatic adjustable seat vibration isolation device as described in claim 8, characterized in that: It also includes a support frame (514) fixedly connected to the rotating seat (512), a horizontal drive shaft (515) rotatably connected to the inner wall of the support frame (514), a driven sprocket (516) fixedly connected to the surface of the horizontal drive shaft (515), a first helical gear (508) fixedly connected to the surface of the horizontal drive shaft (515), and a second helical gear (509) fixedly connected to the bottom of the lead screw (507), and the first helical gear (508) meshes with the second helical gear (509); It also includes a stepper motor (502), the output end of which is connected to a planetary reducer (506), the output end of which is equipped with a drive sprocket (511), and the drive sprocket (511) is connected to the driven sprocket (516) via a chain (517).

10. A control method for a quasi-zero stiffness automatic adjustment seat vibration isolation device as described in any one of claims 1-9, characterized in that, Includes the following steps: Step S1: The controller collects the raw signals from the base acceleration sensor (501), support acceleration sensor (201), and angle sensor (401) in real time. After filtering, noise reduction, and integration, the displacement, velocity, acceleration, and other status information of the seat vibration isolation device are obtained. Step S2: Based on the measurable basic acceleration and the nonlinear dynamics model of the system, the feedforward control force is calculated through the "radial basis function neural network" to counteract the cubic nonlinear stiffness force in the main disturbance and nonlinear restoring force, and the physical realizability is verified according to the semi-active constraint principle. Step S3: The state of the seat vibration isolation device is processed by a band-stop filter to suppress vibrations in the 0.1–0.5Hz frequency band that is sensitive to motion sickness; then it is input into a linear quadratic optimal controller to calculate the global optimal state feedback control force, so as to achieve synergistic optimization of system stability and vibration isolation performance. Step S4: Employ a multi-objective optimization algorithm to adaptively tune the feedforward gain, filter parameters, and weight matrix of the linear quadratic optimal controller in real time to adapt to different loads and road conditions. Step S5: Integrate the total control force and perform amplitude limiting and direction verification to obtain the physically achievable desired control force; Step S6: Based on the physical characteristics of the magnetorheological damper (302), the desired control force is mapped to the corresponding input current. When the magnetorheological damper (302) is in an energy-consuming condition, the corresponding current is output; otherwise, the current is zero. The mapping relationship is obtained based on the calibration experiment and is supplemented by current limiting protection. Step S7: The calculated current signal is output to the damper coil through the power amplifier, so that it generates a corresponding damping force to act on the seat vibration isolation device, thereby achieving real-time suppression of vibration. Step S8: Continuously monitor load changes. When the angle sensor (401) detects that the static load system deviates from the rated balance position, adjust the working height of the positive stiffness mechanism (3) through the load adjustment mechanism (5) to restore the system to the horizontal quasi-zero stiffness state. Step S9: After the magnetorheological damper (302) acts on the seat vibration isolation device, its state changes. The sensor continuously collects a new round of data and repeats the above steps S1 to S8 to form a complete closed-loop control circuit, so as to realize the continuous and adaptive optimization operation of the seat vibration isolation device.

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