600 results about "State observer" patented technology

The invention belongs to the technical field of temperature control, and discloses a temperature control method and device of a hot runner system for an inverted mold. The method comprises the following steps: defining a critical melt area in a physical sprue which directly influences the product quality in a sprue of a hot runner system as a virtual sprue; dynamically generating a melt viscosity target track of the virtual gate region according to the type of an injection molding material and an injection molding process stage; based on measurable injection molding process parameters and sprue area temperature, estimating a current melt viscosity value of a virtual sprue area in real time through a state observer; calculating to obtain an optimal power control sequence by adopting a multivariable model prediction controller; and driving a sprue area heater according to the optimal power control sequence, so that the actual change of the melt viscosity of the virtual sprue area tracks a melt viscosity target track. According to the invention, the defects such as salivation and wire drawing can be effectively eliminated, so that the sprue quality stability and the production efficiency are improved.

The invention discloses a predetermined time expansion state observer generation method and an observation error convergence method, which are applied to the technical field of aerospace, and comprise the following steps: constructing a controller for a second-order nonlinear system according to an all-drive system theory; converting the second-order nonlinear system according to the controller to obtain an all-drive system based on the main controller; wherein the main controller is a controller for controlling the all-wheel-drive system; designing a predetermined time expansion state observer based on the total disturbance and observation error of the all-wheel-drive system; wherein the predetermined time expansion state observer is an observer which limits the upper bound of convergence time of the observer based on a predetermined time parameter. Compared with most existing extended state observers which can only ensure asymptotic convergence and finite time or fixed time convergence, the observer generated based on the predetermined time extended state observer generation method can ensure that the observation error converges within the predetermined time, so that the converged predetermined time is more stable; and the user experience is improved.

The invention provides a field emission thruster extraction electrode indium deposition cleaning temperature control method and system, and relates to the technical field of space electric propulsion, and the method comprises the steps: obtaining multi-source temperature data and electric field intensity data of a target region, and carrying out the time-space fusion processing of the two data, and generating target feature information reflecting the deposition state of an indium material; based on the feature information, a fuzzy PID control algorithm is adopted to generate a power control signal, and then the embedded heating unit is adjusted; monitoring electrothermal characteristics to obtain thermal impedance parameters, and further generating heat flow distribution data; analyzing heat flow data by using a state observer to predict an indium deposition growth trend to obtain deposition rate information, finally determining a cleaning control strategy according to the growth rate, and controlling temperature change in a non-uniform heating mode to enable the indium material to reach a phase change state. According to the invention, the reliability and maintenance efficiency of on-orbit long-term operation of the field emission propeller are improved.

The invention relates to the technical field of power system operation and control, and discloses an improved model-free adaptive flexible low-frequency power transmission oscillation suppression method, which performs zero-phase lag filtering on noisy signals through a nonlinear tracking differentiator, effectively solves the problem of control divergence caused by signal noise, and improves the suppression efficiency. A tight-format dynamic linearization and linear expansion state observer technology is adopted, accurate capture of dynamic characteristics of a strong nonlinear system and real-time observation and compensation of internal and external full-dimensional disturbance are achieved without dependence of a physical model, and particularly, an adaptive estimation algorithm of an output variable quantity penalty factor is introduced. The problem that model parameter identification jumps severely under the broadband oscillation working condition is solved, the robustness of a control system is enhanced, and the self-adaptive optimality of a control strategy is guaranteed and interference of long-term online operation on steady-state performance is avoided by combining parameter optimization of a cuckoo search algorithm and an event triggering mechanism of time-frequency double criteria.

The invention discloses a permanent magnet synchronous motor rotating speed control method based on composite sliding mode control. The method comprises the steps that a mathematical model of a permanent magnet synchronous motor in a d-q axis synchronous rotating coordinate system is built; designing a layered sliding mode surface according to the mathematical model of the permanent magnet synchronous motor; designing a mixed reaching law containing a barrier function in combination with a sliding mode surface; and estimating periodic and non-periodic disturbances existing in the rotating speed of the permanent magnet synchronous motor and carrying out feed-forward compensation on sliding mode control by adopting a cascaded extended state observer combined with quasi-resonance control. According to the method, the rotating speed precision of the permanent magnet synchronous motor can be effectively improved, the dynamic response is improved, and a better inhibition effect on periodic and non-periodic disturbance is achieved.

The invention discloses a PMSM (permanent magnet synchronous motor) control method for a mining electric locomotive. The method comprises a cooperative control framework of a fractional order sliding mode controller and a nonlinear extended state observer. Wherein the fractional order sliding mode controller constructs a novel sliding mode surface by introducing a terminal factor and a fractional order calculus theory, and introduces a state variable to design an adaptive fractional order reaching law, so that buffeting is effectively inhibited and controlled while system error convergence is accelerated; and the nonlinear extended state observer is used for estimating the uncertainty of a system model and the disturbance of an external load in real time, and introducing the uncertainty and the disturbance as feedforward compensation quantity into a control loop, so that the anti-interference capability of the system is remarkably enhanced. Through deep fusion of the fractional calculus theory, the sliding mode control and the nonlinear extended state observer, the problems of large buffeting, slow response, poor anti-interference capability and the like of a traditional control method of the mining electric locomotive under complex working conditions are solved, and the dynamic and steady state performance and the control precision of the system are remarkably improved.

The invention relates to the technical field of unmanned aerial vehicle control, and discloses a fire-fighting unmanned aerial vehicle flight attitude instability control device and a control method thereof. The device at least comprises a control module which is configured to estimate an equivalent disturbance torque vector generated by throwing a fire extinguishing bomb in real time by utilizing an expansion state observer according to an attitude state quantity, a load state parameter and a current motor control instruction, a self-adaptive sliding mode controller fuses the equivalent disturbance torque vector and a feedback control quantity obtained through sliding mode control based on the current attitude error, a total compensation torque instruction needed by the fire-fighting unmanned aerial vehicle to recover stability is generated, and the total compensation torque instruction is decomposed into a target displacement instruction and a differential speed adjusting instruction; and the execution module is configured to execute the target displacement instruction by using the movable counterweight mechanism to drive the counterweight block to move, and execute the differential speed adjustment instruction through the power fine adjustment mechanism to adjust the rotating speed of the motor. The problem of attitude instability after bomb dropping of the fire-fighting unmanned aerial vehicle is effectively solved.

The invention relates to the technical field of drainage control, in particular to a liquid level sensing drainage control method and system based on electronic and floating ball cooperative detection, and the method comprises the steps: fusing the angular displacement, capacitance value and acceleration disturbance data of a floating ball, and constructing a liquid level state observer; a dynamic compensation factor is introduced to strip liquid shaking interference, and an accurate liquid level reference value is obtained; a composite control vector is constructed based on the liquid level deviation and the change rate, and a drainage instruction is generated through analysis to control a valve to act; meanwhile, a self-adaptive feedback adjustment mechanism is established, observer parameters are dynamically calibrated through liquid level response residual errors, and the drifting error of an actuator is offset; according to the technical scheme, the robustness of drainage control can be remarkably improved.

The invention discloses an input-limited and coupled-output-limited quadrotor unmanned aerial vehicle motion control method and system based on an extended state observer, and the method comprises the steps: building a quadrotor unmanned aerial vehicle kinetic model, and carrying out the modeling and decoupling of lumped disturbance. And designing an extended state observer to estimate the position, speed and lumped disturbance of the unmanned aerial vehicle. Coupling output constraint is converted into time-varying non-coupling constraint through the rotation matrix, and tracking errors are defined accordingly. And designing a position controller and an attitude controller based on the error and an estimated value of the observer, and generating expected thrust and expected angular velocity. An input limited function and an auxiliary variable are introduced, and the saturation problem of the controller is solved. The system comprises a dynamic modeling and disturbance decoupling module, a state estimation module, an output constraint processing module, a position control and attitude control module and an input saturation compensation module. According to the invention, the trajectory tracking precision, robustness and constraint processing capability of the unmanned aerial vehicle are significantly improved.

The invention provides an anti-disturbance unmanned aerial vehicle trajectory tracking control method, system and device and a medium. The method comprises the following steps: establishing a six-degree-of-freedom rigid body dynamic model of a four-rotor unmanned aerial vehicle; selecting an unmanned aerial vehicle feasible trajectory of the kinetic model as an expected trajectory, and introducing a coupling attitude; designing a position loop control law, generating a virtual control force based on a smooth terminal sliding mode control surface, and calculating an actual thrust; designing an attitude loop control law, representing an attitude error based on Lie group SO (3), constructing an attitude tracking controller with a stable global index, and outputting a control torque; constructing a four-order state observer to estimate the angular velocity and the angular acceleration of the coupling attitude, and replacing a true value with an estimated value to participate in control law calculation; thrust and control torque are converted into thrust input of the unmanned aerial vehicle, the unmanned aerial vehicle is driven to track an expected trajectory, and the problems that in trajectory tracking control of the four-rotor unmanned aerial vehicle, dependence on position acceleration measurement is high, noise is amplified through differential derivation, disturbance rejection is weak, and real-time calculation burden is large are solved.

The invention discloses a high-robustness deadbeat predictive current control method which is suitable for current control of a dual three-phase permanent magnet motor driving system, and belongs to the technical field of permanent magnet motor control. The method mainly comprises the following steps: reconstructing a motor mathematical model by adopting a space vector decoupling matrix and Park transformation to obtain a motor voltage equation under a dqxy axis; designing a linear expansion state observer; a reference value of an output voltage vector is obtained in combination with deadbeat predictive current control; time delay in the digital control system is calculated, and angle delay is compensated; and designing a closed-loop Smith predictor for compensating a time delay link to complete high-robustness dead-beat predictive current control of the dual three-phase permanent magnet motor. The current loop design in the method does not depend on motor parameters, and the method has high parameter change robustness. By introducing the closed-loop Smith predictor, large delay of the system can be effectively compensated, and high-precision current tracking is realized under low switching frequency.

The invention relates to the technical field of temperature control, in particular to a multi-dimensional compensation ablation system temperature control system, method and device and a medium. The system calculates a medium texture index representing the structural change of the load medium by synchronously acquiring electrical parameters and ultrasonic image data; constructing an anti-interference control model comprising an extended state observer, and defining energy transmission loss caused by contact thermal resistance as an extended state variable; calculating an adaptive correction factor based on the texture index, dynamically correcting the state updating process of the observer to obtain an energy loss correction estimated value, and constructing a compensation control model to adjust the output power according to the energy loss correction estimated value; according to the invention, the technical problem of incomplete heating caused by false high temperature of the sensor and system misjudgment due to state deterioration of the contact interface is effectively solved; accurate reconstruction and closed-loop compensation of effective heat flow in a non-ideal contact environment are realized, sufficient energy penetration can still be maintained even if contact thermal resistance is sharply increased, and the integrity of an ablation area is guaranteed.

The invention discloses an unmanned aerial vehicle anti-wind disturbance controller and a control method, and belongs to the technical field of unmanned aerial vehicle flight control. The method runs on an independent processing module which is connected in series between a main flight controller and an electronic speed regulator of the unmanned aerial vehicle, a dynamic reference is constructed by collecting motor current in real time, deviation is calculated, and wind disturbance equivalent disturbance torque is estimated in a prospective mode through a third-order linear extended state observer (LESO) with bandwidth parameterization design; in combination with a'user operation state + flight mode 'two-dimensional intelligent decision compensation strategy, a'look-ahead wind resistance + attitude backup' dual-redundancy channel is matched, so that the wind disturbance is compensated in advance, and the flight stability in a complex scene is ensured. A corresponding controller adopts a standardized independent hardware design, the adaptability is high, the integration cost is low, and the method can be widely applied to high-precision operation scenes of various multi-rotor unmanned aerial vehicles.

The invention discloses an integrated optimization method of a flywheel energy storage system. The corresponding system is formed by connecting a plurality of flywheel monomers in parallel through a direct current bus. The method comprises the steps that the real-time rotating speed, the direct-current bus voltage, the maximum charging and discharging power capacity and a power grid frequency modulation power instruction of each flywheel single body are collected; calculating current stored kinetic energy based on the rotating speed and the rotational inertia of the rotor, and normalizing to obtain an energy state index SoE; a double-layer collaborative architecture is adopted for power scheduling; at the moment of charging and discharging mode switching, the total disturbance of the system is estimated on line through a cascade expansion state observer, and feed-forward compensation is implemented in control output to suppress instantaneous fluctuation of the voltage of the direct-current bus. According to the method, the SoE is obtained by calculating the kinetic energy and normalizing the kinetic energy, so that the accurate representation of the energy storage state is realized; and voltage fluctuation can be effectively suppressed when working conditions suddenly change. The method avoids overcharge and overdischarge of individual units, guarantees high reliability and safety, prolongs the service life of equipment, and is especially suitable for power grid frequency support application in a high-proportion renewable energy access scene.

The invention discloses a humanoid robot joint motor control method with model prediction control, and relates to the technical field of robot motion control. The method is used for solving the problems of control instruction infeasibility and model disturbance caused by voltage saturation during high-speed motion. An error state space model of a joint motor system is established, and non-linear terms such as gravity are used as nominal feed-forward quantities for stripping; then, the rotating speed of the motor and the bus voltage of the driver are collected in real time, the back electromotive force is calculated, and the voltage margin is mapped into a dynamic torque physical limit value at the current moment; and meanwhile, estimating an unmodeled lumped disturbance value of the model by using an extended state observer. And finally, taking the dynamic limit as a real-time inequality constraint, introducing a disturbance value correction prediction equation, constructing and solving a quadratic programming problem, extracting an optimal compensation torque, superposing the optimal compensation torque with an inverse dynamic feedforward torque, and converting the superposed torque into a current signal to drive a motor, thereby realizing high-dynamic and high-precision robust control under the physical boundary constraint.

The invention relates to the technical field of aircraft control, in particular to a four-rotor unmanned aerial vehicle robust trajectory control method based on a sliding mode control-improved extended state observer. The method comprises the following steps: firstly, establishing a nonlinear dynamic model of the quad-rotor unmanned aerial vehicle, and decomposing the system into a hierarchical control structure of a position outer ring and an attitude inner ring; secondly, a third-order extended state observer (ESO) is designed to estimate composite disturbance of each channel in real time, an improved sliding mode control law with observation error compensation is provided, and the vibration bearing phenomenon is effectively restrained; and finally, proving the asymptotic stability of the closed-loop system through the Lyapunov stability theory. The method is used for solving the problems of low trajectory tracking precision and control signal buffeting caused by underactuation, strong coupling nonlinear characteristics and external disturbance of the four-rotor unmanned aerial vehicle. High-precision trajectory tracking under complex disturbance can be realized, and control signal buffeting can be suppressed at the same time.

The invention belongs to the technical field of control, and discloses a water surface robot high-precision trajectory tracking control method and related equipment, and the method comprises the steps: constructing a dynamic multi-modal environment map containing water surface three-dimensional geometric topology information and water flow field vector information; according to the dynamic multi-modal environment map, an improved quantum particle swarm optimization algorithm embedded into a water flow kinetic equation constraint is adopted to carry out global path planning, smooth parameterization processing is carried out on a global path obtained through planning, and a reference trajectory is generated; according to the vector information of the water flow field, flow field disturbance is predicted based on a fluid-structure interaction dynamics model, system residual disturbance is estimated by using an extended state observer, and feedforward control quantity is generated in combination; according to the real-time flow velocity of the water flow field and the trajectory tracking error, a nonlinear model prediction controller and an adaptive sliding mode controller are adaptively switched, and a control instruction is generated in combination with a feedforward control quantity to drive the water surface robot to track a reference trajectory; therefore, high-precision trajectory tracking control is realized.

The invention discloses a grid-connected inverter control method based on an MAGRNN neural network observer, and aims to solve the problems that a model prediction control method is insufficient in state estimation precision and worsened in control performance under the conditions of model mismatch, parameter offset and power grid voltage distortion. For an LCL type grid-connected inverter, firstly, a prediction model is established based on a state-space equation; secondly, real-time estimation parameters of an inductance parameter state observer are constructed; the method comprises the following steps: firstly, estimating an interference compensation item through a neuron self-adaptive adjustment mechanism, then introducing an MAGRNN neural network as a dynamic error compensator, using input and output of the observer as MAGRNN input, estimating the interference compensation item through the neuron self-adaptive adjustment mechanism, and finally, feeding back the interference item predicted by the MAGRNN to a model prediction controller for interference compensation. By utilizing the strong nonlinear fitting capability of the MAGRNN, the state estimation precision under complex working conditions such as parameter change and power grid disturbance is remarkably improved, and the control performance of the system is effectively improved.

The invention belongs to the technical field of permanent magnet synchronous motor control, and particularly discloses a permanent magnet synchronous motor finite time switching active-disturbance-rejection rotating speed control method, which comprises the following steps: acquiring a reference rotating speed and an actual rotating speed of a permanent magnet synchronous motor; the absolute value of the error between the reference rotating speed and the actual rotating speed is calculated and compared with a preset first threshold value and a preset second threshold value, and the stage of the permanent magnet synchronous motor is judged; constructing a finite time cascade expansion state observer comprising a first-stage finite time ESO and a second-stage linear ESO to observe the state and lumped disturbance of the permanent magnet synchronous motor; and based on the stage of the permanent magnet synchronous motor, selecting a composite state of the observation value of the first-stage finite time ESO, the observation value of the second-stage linear ESO or the observation value of the first-stage observer and the observation value of the second-stage observer generated based on the Bezier curve to generate the rotating speed loop control law of the permanent magnet synchronous motor. According to the invention, the problems that the transient anti-interference capability is weak and the current performance is reduced due to the fact that transient control and steady-state control are not distinguished in the prior art are solved.

The invention discloses a nonlinear adaptive control system design method and device based on a pseudo-inverse matrix, and relates to the field of adaptive control, and the method comprises the steps: S1, constructing a controlled object state-space equation comprising matching uncertainty and non-matching uncertainty; non-matching uncertainty is converted into matching uncertainty through pseudo-inverse transformation; s2, introducing the state vector into a regression vector to obtain an expansion regression vector, and obtaining an uncertainty function based on the expansion regression vector; s3, constructing a state observer, and obtaining a state observation value of the controlled object; s4, taking the difference between the state observation value and the state actual value as the excitation of the adaptive law, and updating the parameters of the uncertain function; s5, constructing a self-adaptive control law by taking the estimated value of the uncertain function as input; and S6, filtering an output signal of the adaptive control law through L1 to obtain a final control law. Through the expansion regression vector comprising the state vector, accurate compensation of the uncertain function is realized, and the self-adaptive efficiency is improved.

The invention discloses a mutual inductor error self-compensation method based on dynamic flux linkage reconstruction, and relates to the technical field of mutual inductor error self-compensation. According to the method, a weighted double-domain integral noise suppression flux linkage reconstruction algorithm is used for processing, the fast response of time domain integral and the anti-noise capability of frequency domain integral are fused, and then a dynamic error extension state observer is constructed by taking a flux linkage estimation value as input; and estimating system errors caused by nonlinearity, hysteresis and environmental disturbance of the iron core and dynamic characteristics of the system errors based on extended Kalman filtering recursion. And finally, generating a time-varying compensation amount according to the estimated error and the derivative thereof. According to the method, the contradiction between precision and response speed in traditional flux linkage reconstruction is overcome, the problem that a static error model cannot adapt to dynamic working conditions is solved, high-precision real-time self-compensation of nonlinear time-varying errors of the mutual inductor is realized, and the measurement accuracy and dynamic performance of electric energy metering and protection equipment under complex operation conditions are improved.

The invention provides a high-order robust control method for a mobile robot in combination with a weighted double-Q learning algorithm. The high-order robust control method comprises the following steps: step 1, constructing an intelligent trolley motion scene including time-varying friction, variable gradient, random external disturbance and sensor noise complex uncertainty; step 2, designing a weighted double-Q learning adaptive nonlinear expansion state observer; step 3, based on the step 2, constructing a reward function including a trajectory tracking error, a disturbance estimation error and a stability constraint; 4, designing an improved super-spiral sliding mode control law based on the weighted double-Q learning adaptive nonlinear extended state observer; and 5, setting a plurality of groups of working condition simulation comparison schemes, and carrying out simulation experiment verification. According to the invention, real-time adaptive control of the mobile robot on different working conditions is realized, the trajectory tracking precision of the system is improved, and sliding-mode control buffeting is inhibited at the same time.

The invention discloses a deadbeat predictive current control method based on a composite disturbance observer, and belongs to the technical field of dual three-phase permanent magnet motor control. The dual three-phase permanent magnet motor is composed of two sets of stator three-phase windings, and the space phase shift angle is 30 degrees. The method comprises the following steps: establishing a discretized motor model containing total disturbance under a double-dq coordinate system; a composite disturbance observer is designed, and direct current disturbance and alternating current disturbance are synchronously estimated through a second-order disturbance expansion state observer embedded into a generalized integrator; and performing feed-forward compensation by using the disturbance estimation value, and calculating a voltage control quantity in combination with deadbeat prediction. By introducing the second-order disturbance expansion state observer and the generalized integrator, synchronous compensation of direct current disturbance and alternating current disturbance is realized, so that current harmonics are effectively reduced, and the current waveform quality is improved. Meanwhile, complete decoupling of the current control loop and the disturbance suppression loop is realized. In addition, the method still shows high robustness under the condition of motor parameter mismatch.

The invention relates to the field of control, in particular to a flight attitude control method and system for an unmanned aerial vehicle, and the method comprises the steps: obtaining an expected attitude angle instruction and actual attitude angle feedback of the unmanned aerial vehicle, calculating an attitude angle error, employing a tracking differentiator to calculate a transition process for the expected attitude angle instruction, and enabling a tracking rate factor to achieve the control of the flight attitude of the unmanned aerial vehicle when the instruction is subjected to step change. Based on initial attitude angle error setting, instruction smooth transition is ensured, based on a transition signal output by a tracking differentiator and an estimated value of an expansion state observer, a basic control quantity is generated through nonlinear state error feedback, and control gain is adjusted on line according to a lumped disturbance amplitude. And predicting the lumped disturbance historical sequence by using a grey prediction model, calculating a predicted value at a future moment, and carrying out algebraic summation on the basic control quantity, a compensation component of the lumped disturbance predicted value and a gyroscopic moment decoupling component to generate an attitude control moment signal so as to realize stable flight of the unmanned aerial vehicle.

The invention provides an alternating-current side third harmonic weakening modulation method of a railway power regulator under the condition that direct-current bus voltage contains frequency doubling ripples. The method comprises the following steps: constructing a bus voltage state space model of the railway power regulator, and designing a non-delay adaptive state observer to extract direct current component information of bus voltage; separating information of a direct current component and a double frequency ripple component of the bus voltage through a self-adaptive state observer; introducing the direct-current component information into voltage and current double-closed-loop control; designing a secondary pulse modulation ratio opposite to a ripple voltage phase through the extracted ripple pulse parameters; the third harmonic on the alternating current side of the RPC is weakened by injecting an opposite pulsation modulation ratio into a modulation coefficient; according to the method, under the condition that circuit topology and control strategy complexity are not increased, output voltage third harmonics are effectively weakened, direct current side voltage double frequency fluctuation is reduced, meanwhile, power coupling between the alternating current side and the direct current side can be compensated, the requirement for the capacitance value of a bus capacitor is reduced, the total harmonic distortion rate is reduced, and the service life of the bus is prolonged. And long-term stable operation of the system is guaranteed.

The present application relates to the technical field of control adjustment, and particularly relates to a temperature control method, system, device and medium for titanium alloy forging, which constructs a model library describing the thermodynamic behavior of a forging, and dynamically generates a double-target temperature trajectory; a state observer is run in real time to estimate the internal temperature field of the forging online, and a feedforward control set value is calculated based on a model predictive control framework; at the same time, a feedback correction loop is used to generate a feedback correction control amount and correct the model online; finally, the feedforward and feedback control amounts are adaptively fused to generate and apply a final driving signal; by combining a physical model and a data-driven method, the accuracy of the modeling of deformation heat and the estimation of core temperature is improved, the metallurgical and cost constraints are balanced, the forging is ensured to be formed within an optimal temperature window, and the problem that the existing technology is difficult to control the microstructure of the forging within the optimal temperature window is solved.

The invention discloses a piezoelectric micro-positioning platform preset performance control method based on an extended state observer, and the method mainly comprises the steps: firstly, building a piezoelectric micro-positioning platform system model considering input hysteresis and unknown disturbance; secondly, designing an extended state observer based on a radial basis function neural network to estimate an unmeasurable state of the system and lumped disturbance containing input hysteresis; then, a preset performance function is used, so that the overshoot performance of the system is effectively improved; thirdly, in combination with a preset performance function, a first-order sliding mode differentiator and an expansion state observer, providing a virtual control law and an adaptive control law; and finally, a preset performance controller is utilized, a Lyapunov stability theory is combined, proper parameters are selected to ensure that the closed-loop system is kept stable within preset time, and tracking errors are controlled within a set error range.

The invention discloses a robot screw turning method and system based on a dynamic spiral field and compliance control. The system comprises a sensing module, a dynamic spiral field generator and a compliance coupling controller. The sensing module calculates parameters such as screwing-in progress, radial deviation and meshing confidence coefficient in real time through multi-sensor fusion and a state observer, and estimates the friction coefficient and the contact state. The dynamic spiral field generator adaptively adjusts the screw pitch, the spiral radius, the expected force and the expected speed according to the sensing state, and an intelligent screwing-in track is generated. And the compliant coupling controller adopts parameter self-adaptive axial admittance control and rotation impedance control, so that high-precision and high-compliant force-position cooperative operation is realized. The system can dynamically adapt to different screwing-in stages and abnormal working conditions, and the reliability, the self-adaptability and the operation precision of the screw turning process are improved.

The invention discloses a high-precision clamping force estimation method of an electronic mechanical braking system, and belongs to the technical field of automobile braking system control. The method comprises the following steps: acquiring real-time signals such as motor rotation angle, angular velocity and current, and acquiring a steady-state clamping force estimation value by using a seven-degree polynomial static model; then based on a motor angular speed judgment working condition, correcting a tightening force estimation value through an inertia and friction dynamic compensation model under a high-speed dynamic working condition to obtain a model output force; estimating unmodeled disturbances such as friction change and temperature excursion in real time through an extended state observer to obtain disturbance compensation force; and finally, obtaining a final clamping force estimated value by adopting working condition self-adaptive weighted fusion. According to the method, errors caused by factors such as friction change, temperature excursion and structure aging can be effectively reduced, and high-precision estimation of the clamping force is achieved.

The invention belongs to the field of robot control, and particularly relates to a quadruped robot accurate gait control method based on dynamic optimization. The method comprises the steps that phase states of four legs of the quadruped robot are judged, supporting phase foot end force is calculated for the legs in a supporting phase according to a real-time motion state and an expected motion state, and swinging phase correction force is calculated for the legs in a swinging phase; an expansion state observer is constructed based on the leg Cartesian space dynamics model, and the expansion state observer is used for observing the total disturbance term of the four legs of the quadruped robot in real time; calculating to obtain a disturbance value to be compensated based on the total disturbance term, obtaining an uncompensated joint torque based on the support phase foot end force or the swing phase correction force, and superposing to obtain a joint torque instruction; and driving the quadruped robot according to the joint torque instruction. According to the method, an advanced observation and compensation mechanism is introduced in a bottom layer execution link, accurate implementation of an upper layer optimization target is ensured, and finally accurate gait control is achieved.