442 results about "Control torque" patented technology

The invention relates to the technical field of extended-range electric vehicle control, and discloses an engine starting control method and system for an extended-range electric vehicle, and the method comprises the following steps: obtaining the operation information of the extended-range electric vehicle, the operation information comprises the actual temperature of an engine, the actual rotating speed of a range extender, the state of charge (SOC) of a power battery and the maximum dischargeable power; when the starting request mark position of the engine is set, the generator is controlled to enter a torque control mode, and the engine enters a starting mode; and based on the actual temperature of the engine and the actual rotating speed of the range extender, the pre-control torque of the generator is activated through the enabling flag bit. By accurately controlling the rotating speed and the torque of the generator, smooth starting of the engine is achieved, the requirement for starting the engine in various vehicle using scenes is met, meanwhile, the actual temperature of the engine, the SOC of a power battery and the like are considered, the target rotating speed of the started engine and the starting torque of the generator are flexibly controlled, and the starting efficiency is improved. The starting performance of the engine is improved.

The invention provides a vehicle anti-skid control method, device and system and a vehicle. According to at least one driving wheel of the vehicle, the chassis wheel speed, the actual wheel speed, the wheel end actual torque, the adhesion coefficient, the total wheel load, the target slip rate, the wheel radius and the vehicle speed are obtained; a feedforward control torque is determined according to an attachment coefficient, a total wheel load and a wheel radius, a wheel speed deviation is determined according to a target slip rate, a chassis wheel speed and an actual wheel speed, a torque deviation is adjusted through a vehicle speed, the attachment coefficient and the wheel speed deviation to obtain a feedback control torque, and the feedback control torque and the attachment coefficient are superposed to serve as an output torque for vehicle anti-skid control. Dynamic wheel load changes and wheel load changes caused by the vehicle on the ramp road surface are considered, the total wheel load is estimated in real time, feed-forward control is introduced to obtain the feed-forward control torque, feedback control is compensated, and the stability and accuracy of anti-skid control are enhanced when the ramp road surface and the loads change.

The invention discloses a force sense feedback control method for an intelligent mechanical arm, which comprises the following steps of: 1, acquiring data through a multi-modal sensor and fusing the data to obtain a multi-dimensional perception vector; 3, calculating a force sense tracking error and a change rate and triggering an event-driven control decision mechanism; 4, designing a nonlinear compensation control rule and outputting a control torque instruction, wherein a control system comprises a multi-mode sensing module, a dynamic prediction module, an event-driven control module and a cooperative calculation module; according to the method, multi-mode sensing information is fused with the lifting force sense representation capacity, advanced adjustment is achieved in combination with a dynamic force sense prediction mechanism, event-driven control is used for reducing calculation redundancy, robustness to complex interference is enhanced through a nonlinear compensation strategy, and finally high-precision and low-delay force sense control of the mechanical arm in a dynamic interaction scene is achieved.

The invention provides a four-rotor unmanned aerial vehicle anti-wind-disturbance robust flight control method and system, and belongs to the technical field of unmanned aerial vehicle control, and the method comprises the steps: collecting the real-time state data of an unmanned aerial vehicle, the real-time state information comprises the position, speed, height, three-axis attitude angle and three-axis angular speed; acquiring an expected inspection track instruction, generating an expected attitude angle instruction and a total lift instruction in combination with the real-time state data, performing wind disturbance estimation by adopting a neural network, and compensating the expected attitude angle instruction and the total lift instruction; calculating a control torque increment by adopting an increment backstepping method based on the expected attitude angle instruction and the real-time state data, and obtaining a control torque instruction by combining the control torque at the previous moment; and the control torque instruction and the total lift instruction are distributed to the rotating speeds of four motors of the four-rotor unmanned aerial vehicle, and the motors execute the rotating speed instructions to drive the unmanned aerial vehicle to complete a wind disturbance resisting flight task. The method can actively adapt to wind field changes, and it is guaranteed that the unmanned aerial vehicle can still fly accurately, stably and safely under disturbance.

The invention provides a driving anti-slip optimization control method based on vehicle-road cooperation road fusion estimation, and the method comprises the following steps: S1, fusing vehicle-mounted and roadside visual recognition information, and obtaining a vehicle-road cooperation road state recognition result through employing a weighted voting method in combination with road invariant hypothesis and historical information assistance judgment; s2, adaptively adjusting parameters of a dynamic estimator by using a pavement state recognition result, establishing a sample set based on a pavement fusion estimation result, introducing a fuzzy clustering algorithm of particle swarm optimization to realize self-evolution optimization of the structure and the parameters of the estimator, and outputting a fused attachment coefficient estimation result; and S3, designing a slip rate and wheel acceleration combined control strategy to deal with potential slip in advance, and outputting a control torque result of a slip rate controller. Compared with the prior art, the method integrates visual perception and dynamic information to realize accurate estimation of the pavement state, supports advanced intervention of the slip rate controller before slip, and improves the driving stability of the whole vehicle.

The invention relates to the technical field of hoisting equipment intelligent control based on multi-sensor cooperation, and discloses a hoisting equipment intelligent control method based on multi-sensor cooperation. A control unit reads and stores parameters such as air density, windward projection area, wind load arm length, arm section rotational inertia, rated output force of a hydraulic cylinder, sampling period and the like, and static self-inspection and dynamic calibration are performed on a wind speed sensor, a rotary encoder and a pressure sensor respectively; multiple paths of wind speeds are collected in parallel during operation, fused wind speeds are obtained through weighted fusion after abnormities are removed, and the wind load torque is calculated and limited by combining the windward area and the force arm length; reading two continuous encoder angle differences, performing amplitude limiting, calculating an angular velocity and kinetic energy, performing adaptive adjustment according to kinetic energy deviation, and performing amplitude limiting on a damping coefficient to generate a damping torque; and the amplitude-limited wind load torque and damping torque are synthesized into total control torque, and after amplitude limiting, the total control torque is converted into amplitude-limiting hydraulic cylinder operation output force which is issued and executed by a control unit.

The invention relates to the technical field of intelligent traffic control, and discloses a self-balancing two-wheeled vehicle queue formation control system which comprises a cloud scheduling platform, a formation control unit and a vehicle end execution unit. And the cloud scheduling platform generates a global avoidance path based on the accumulated gravitational potential energy change and the pavement flatness coefficient, and executes dynamic position complementing. The formation control unit constructs a communication topology and executes formation switching based on environmental perception; the cooperative control module adopts an attitude position coupling algorithm, an expected acceleration is corrected through a gain function attenuating along with an attitude angle index, and the attitude balance is maintained preferentially when a tracking error is eliminated. The vehicle end execution unit is provided with an environment sensing and composite actuating module, and a hub motor and a control moment gyroscope are used for responding to longitudinal driving and transverse balance instructions respectively, so that dynamic decoupling is achieved. According to the invention, the control conflict between two-wheeled vehicle formation trajectory tracking and attitude stability is effectively solved, and the driving safety of the system is improved.

The invention relates to the technical field of rehabilitation robot control, and particularly discloses a gait prediction compensation admittance control method and system for lower limb rehabilitation exoskeleton, and the method comprises the steps: inputting a multi-dimensional motion vector into a time sequence prediction model, and outputting a prediction result of a gait phase at a future moment; if the maximum probability output by the time sequence prediction model is lower than a preset threshold value, automatically switching to a pre-constructed rule criterion to carry out gait phase recognition; an admittance control parameter matched with the gait phase prediction result is called from an admittance parameter mapping table, and a main control torque is calculated based on the called admittance control parameter; calculating a compensation torque based on the deviation between the actual human-computer interaction force and the expected interaction force; and the main control torque and the compensation torque are superposed to serve as a final torque driving instruction of the exoskeleton motor. Real-time gait prediction, admittance parameter self-adaptive adjustment and interaction force error dynamic compensation can be fused, and high-flexibility and high-safety man-machine collaborative rehabilitation training is achieved.

According to the mechanical arm control method and system based on the self-adaptive force field, the motion state of a patient is monitored, the motion state is compared with a demonstration space trajectory, and training performance information of the patient is obtained. Based on the training performance information and the constructed adaptive force field model, auxiliary force applied to the patient is obtained through calculation, wherein the auxiliary force comprises normal force, tangential force and viscous force. And the applied auxiliary torque is calculated based on the tail end posture of the mechanical arm and the target posture, the joint control torque is obtained according to the auxiliary force and the auxiliary torque, and the dynamic torque and the null space control torque of the robot dynamic model are obtained. And the joint control torque, the dynamic torque and the null space control torque are combined to obtain the comprehensive control torque for controlling the mechanical arm. Therefore, the self-adaptive adjustment of the auxiliary force is realized based on the position, speed and direction of the patient, and the time degree of freedom can be obtained in the motion of the self-adaptive force field, so that the patient obtains more freedom of active motion under the assistance of the space force field.

The present invention relates to the field of electric vehicles and to a highly adaptable creep control method for pure electric heavy-duty trucks. After the pure electric heavy-duty truck enters creep mode, the method performs P-term dynamic proportional control to obtain P-term dynamic proportional control torque; performs I-term dynamic integral proportional closed-loop control to obtain I-term dynamic proportional integral closed-loop regulation control torque; performs slope feedforward torque compensation control to obtain slope compensation torque; and performs vehicle weight feedforward torque compensation control to obtain vehicle weight compensation torque. The P-term dynamic proportional control torque, I-term dynamic proportional integral closed-loop regulation control torque, slope compensation torque, and vehicle weight compensation torque are added together to obtain creep closed-loop regulation control torque. The creep closed-loop regulation control torque is then subjected to a fixed limit to prevent abnormal torque output caused by closed-loop regulation. Through the method of the present invention, stable creep speed control can be achieved for pure electric heavy-duty trucks operating with or without a trailer, unloaded, fully loaded, and under various slope conditions.

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 reconfigurable robot control method and system for a zero-sum game optimization event triggering mechanism. The method comprises the steps that a reconfigurable robot dynamic model based on joint torque feedback is established, an error dynamic state space is established, and a preset performance function is set to restrain the transient performance of the error dynamic state space; the error dynamics state space constraining the transient performance is mapped to the unconstrained error dynamics augmented system state space, and an event triggering mechanism is introduced, so that the unconstrained error dynamics augmented system state space meets the zero-sum game of maximizing the event triggering interval and minimizing the control input; setting a performance index function based on a zero-sum game, and obtaining an optimal control law under an event triggering mechanism through the performance index function; according to the invention, the precision and stability of robot system control are improved through the predetermined performance function; the zero-sum game of an event triggering mechanism is introduced to obtain an optimal control law under a Nash equilibrium condition, so that communication resources and calculation burdens are effectively reduced; and the control torque of each subsystem is smoother under the action of the optimal control law, so that the energy consumption is reduced and the service life of the motor is prolonged.

The invention discloses a robot operation arm constraint safety system based on communication perception and a method thereof. The method comprises the steps that communication parameters with an upper computer and the angular speed and control torque of a robot operation arm are obtained in real time; de-noising the communication parameters, and performing evaluation calculation to obtain a network score; judging whether the network score is greater than a preset first threshold value, if so, judging that communication is abnormal and accumulating, if the communication is abnormal in continuous N periods, smoothly switching from an RL online mode to a local TDE prediction mode, and calculating a disturbance estimation value of the current period after mode switching; calculating an impact trend index of the current period based on the current control torque, the angular velocity and the historical period data difference value, and outputting a degradation factor from the disturbance estimation value and the impact trend index through a fuzzy rule; and adjusting the control parameter through the reduction factor, and generating the control torque of the next period. The fuzzy rule is fused with multi-factor decision, and control stability and system responsiveness are both considered.

The invention provides a suspension main power control method and device and a medium, and the method comprises the steps: determining an expected roll angle according to a current lateral acceleration and roll angle planning scheme, and determining an expected pitch angle according to a current longitudinal acceleration and pitch angle planning scheme; determining an active roll control moment according to the current lateral acceleration, the current roll angle and the expected roll angle, and determining an active pitch control moment according to the current longitudinal acceleration, the current pitch angle and the expected pitch angle; according to the active roll control moment and a preset roll distribution coefficient, roll control active force corresponding to each suspension is determined; determining pitching control active force corresponding to each suspension according to the active pitching control moment and a preset pitching distribution coefficient; and for each suspension, the control main power corresponding to the suspension is determined according to the corresponding roll control main power and pitching control main power, and the effect of actively controlling the roll pitching attitude of the vehicle body in combination with the motion working condition of the vehicle is achieved.

The invention discloses a mechanical arm state limited preset time point control method and system, and relates to the technical field of robot control, and the method comprises the steps: obtaining a joint position tracking error and a joint speed tracking error based on a joint motion state and an expected trajectory of a mechanical arm; based on constrained system states corresponding to the joint position tracking error and the joint speed tracking error, nonlinear transformation is carried out on the joint position tracking error and the joint speed tracking error through an unconstrained state function, and an equivalent unconstrained virtual error variable is constructed in combination with coordinate transformation; based on the unconstrained virtual error variable, designing a sectional sliding mode variable; and designing a second-order reaching law based on the sectional sliding mode variable to form a closed-loop dynamic state, and solving based on the closed-loop dynamic state to obtain a control torque so as to control the mechanical arm joint. According to the method, the trajectory tracking error of the mechanical arm can be converged at the moment specified by a user, the system state is ensured to meet strict physical constraints in the whole process, and the method can be applied to accurate trajectory control in a complex task scene.

The invention discloses a parameter self-adaptive control method for a low-orbit satellite with a solar panel driving device. Belongs to the technical field of aerospace, and particularly relates to the technical field of low-orbit satellite parameter control. The satellite attitude control method solves the technical problems of overcoming the influence of the rotational inertia of the satellite and compensating the influence of the SADA vibration disturbance torque and the atmospheric resistance torque on the satellite attitude control precision. The method comprises the following steps: constructing a satellite attitude kinematics and dynamics equation in a quaternion form, and constructing a satellite attitude kinematics and dynamics equation for designing an attitude controller on the basis of the satellite attitude kinematics and dynamics equation; defining an error attitude kinematics and dynamics equation of the satellite through the attitude control error and the angle control error; carrying out segmentation conversion on a to-be-estimated parameter and a known state variable, and expressing the negative influence of a rotational inertia error on the attitude by matrix operation; designing the control torque of the attitude controller by adopting a mode of combining nonlinear feedback control with self-adaptive control; and updating the self-adaptive estimated value in the control parameters of the attitude controller by adopting a parameter self-adaptive law.

The invention discloses a decoupling motion control method and system for a four-footed mobile operation robot considering the acting force of a mechanical arm, and belongs to the field of motion control of foot type mobile operation robots. An expected motion track input by a user can be tracked by performing planning through linear model prediction control MPC; on the basis of the tracked motion trail, mechanical arm joint control torque is calculated through a mechanical arm dynamic model and PD feedback; through nonlinear model predictive control NMPC planning, a quadruped robot whole-body motion trail of mechanical arm acting force obtained through calculation according to a mechanical arm dynamic model is considered, and an expected speed trail and an expected force trail input by a tracking user are obtained; and according to an expected speed trajectory and an expected force trajectory input by a tracking user, a whole body controller WBC based on hierarchical quadratic programming calculates a joint driving torque for tracking the expected trajectory according to task priorities. According to the method, the acting force / torque of the mechanical arm to the robot body is considered during motion control of the quadruped robot, and decoupling control over the mechanical arm and the quadruped robot in the quadruped mobile operation robot is achieved.

The invention relates to the technical field of aircraft control, in particular to a control-surface-free aircraft control system based on synthetic jet and a momentum wheel, which comprises a lift force and attitude control subsystem, a steering control subsystem, a propulsion subsystem, a cooperative control unit and an attitude and navigation sensor. The lift force and attitude control subsystem independently controls different areas to generate local lift force difference through a synthetic jet generator matrix integrated on the surface, and rolling and pitching control is achieved. And the steering control subsystem changes the angular momentum direction of a flywheel through a control moment gyroscope arranged in the steering control subsystem, and generates reaction moment to control yawing. The propulsion subsystem provides a primary forward thrust. The cooperative control unit receives a sensor signal, generates an instruction according to a preset strategy, coordinates the subsystems to work cooperatively, and achieves whole-airspace flight control without an exposed control surface.

The invention discloses a method for predicting the remaining service life of a control moment gyroscope based on parameter fusion, and relates to the technical field of health management of spacecraft attitude control systems. According to the method, optimal fusion of measurement parameters and implicit parameters is realized through adversarial learning feature extraction and a channel attention mechanism, and the method is particularly suitable for high-precision residual life prediction of the spacecraft control moment gyroscope under variable working conditions. The method comprises four main steps of data preparation and multi-source input, adversarial learning feature extraction, SE-Attention feature fusion and three-stage training optimization. In the data preparation step, original time sequences of voltage and current of a rotor motor are collected through a built-in electrical sensor of a CMG, and key physical parameters of a full-film lubrication friction coefficient, lubricating oil viscosity, a bearing clearance and contact stiffness are inverted based on an electromechanical coupling model; in the adversarial learning step, a game framework of a feature extractor and a working condition discriminator is constructed, and working condition-independent robust feature extraction is realized through a gradient inversion layer; in the SE-Attention feature fusion step, importance weights are adaptively distributed to different feature channels through an extrusion-excitation mechanism; and the three-stage training optimization step adopts a preheating-confrontation-fine tuning strategy to ensure the network convergence. The method solves the problem of domain adaptation, has the technical advantages of strong robustness, high precision, strong generalization, interpretability and self-adaptation, and can realize high-precision RUL prediction under variable working conditions.

The invention relates to the technical field of heavy-load robot control, in particular to a self-adaptive robust control method of a heavy-load robot fusing differential homeomorphic mapping. According to the method, position information of each joint is collected in real time and accurately compared with an expected trajectory, a ternary input vector is output, differential homeomorphic mapping parameters are updated in real time through a T-S fuzzy inference system, and a joint space state is mapped to a new coordinate space based on the optimized parameters, so that the position information of each joint is accurately compared with the expected trajectory. Neighbor joint information is obtained through distributed communication to generate a cooperative control item, a sliding mode surface is constructed in combination with a local tracking error to generate a robust control item, a compensation item is generated based on adaptive law estimation parameter uncertainty, three-item parallel control output is formed, dynamic weight distribution and fusion are performed on the three control items, a basic control moment is obtained, and the control precision is improved. And then a feed-forward compensation item based on a nominal dynamical model is superposed to generate a final comprehensive control torque, and the comprehensive control torque optimizes energy distribution while ensuring the performance.

A system is provided for controlling torque delivered by an electric motor over a dual inverter. In its primary embodiment, a Digital Differential Co-Processor (DDCP) connects with any automotive grade micro-controller that is principally concerned with controlling motor torque for two motors distributed on an axle.

The invention belongs to the technical field of robot intelligent control, provides a robot double-source joint information impedance control method and system, a medium and a robot, and aims at motion control of a 3R-configuration robot. Joint motion information including a filtering angle, a filtering angular velocity and a filtering angular acceleration is obtained, the pose and / or velocity information of the end effector is mapped to a joint space based on a kinematic model of the robot, and joint motion information including a mapping angle and a mapping angular velocity is obtained; fusing the angle and the angular velocity to obtain a fused angle and a fused angular velocity; and generating a control torque by combining the fusion angle, the fusion angular velocity and the filtering angular acceleration with a preset target impedance parameter and an expected trajectory. The angular velocity and the angular acceleration can be obtained without adding velocity and acceleration sensors on the motor, and the increase of the size, the complexity and the cost of the joint control motor is avoided.

Disclosed are systems, apparatuses, and methods for and related to dynamic control of torque and or lateral thrust applied to a load suspended load on a suspension cable to thereby achieve a target orientation or position or to otherwise move through use of a hyperparameter, wherein the hyperparameter comprises a normalized moment of inertia, wherein the hyperparameter comprises a ratio of a force command to a thruster and an angular acceleration.

The invention relates to an unmanned aerial vehicle attitude control method based on motor state disturbance compensation, belongs to the technical field of unmanned aerial vehicle control, and solves the problems of hysteresis and limited control effect of an existing unmanned aerial vehicle attitude control method. The position controller calculates to obtain expected tension, a roll angle and a pitch angle; the attitude feedback controller calculates a feedback torque according to the expected attitude, the actual Euler angle and the body angular velocity; the load identification module calculates an estimated disturbance torque based on the target rotating speed, the actual rotating speed and the current of each motor; the feedforward neural network module adopts a trained RBF neural network to calculate torque residual error estimation, and torque synthesis is carried out to obtain a torque feedforward compensation amount; adding the feedback torque and the feed-forward compensation amount to obtain a total control torque; and the mixing controller calculates the target rotating speed of each motor according to the expected tension and the total control torque, and finally the control distributor drives the motors to execute. The attitude stability and the control response speed of the unmanned aerial vehicle in the wind disturbance environment are remarkably improved.

A method for controlling torque generated by at least one traction motor of a vehicle before a vehicle launch includes: determining that torque demand increases while simultaneously at least one brake of the vehicle is in an applied state; in dependence on the determination, limiting torque generation by the traction motor in response to torque demand; and removing the limit in dependence on release of the at least one brake.

The invention discloses a near-submarine robot disturbance observation controller and method based on neural network correction, and the controller consists of three parts: 1) a disturbance observer with RBF neural network correction, which is used for monitoring and compensating external disturbance in real time; the double-closed-loop integral sliding mode controller comprises a position ring and a speed ring and generates control torque according to expected and actual positions to guide navigation of the near-submarine robot; and 3) the comparator combines the outputs of the two, realizes accurate interference compensation by comparing the control torque with the disturbance estimation, and finally outputs the control torque containing the interference compensation. According to the method, under the condition that speed information is unobservable, the control precision and the anti-interference capability are improved by intelligently estimating modeling errors and external disturbance, and high-precision heading, pitch angle and depth control is achieved.

The invention discloses a multi-joint torque control method of a mechanical arm for cleaning foreign matters on a power distribution line. The multi-joint torque control method comprises the following steps: S1, setting an initial value and an expected track of a joint in the mechanical arm; s2, a mechanical arm multi-joint torque control model is constructed based on a fuzzy neural network; s3, performing initialization processing on the fuzzy rule, and determining an initial value of a fuzzy neural network parameter; s4, constructing an error function to calculate an error, and performing adjustment and iterative correction on each parameter; s5, the error and the error change rate are calculated to serve as input of the fuzzy neural network, and the control torque parameter of the mechanical arm serves as output; s6, performing iterative optimization processing on the output parameters of the fuzzy neural network based on a particle swarm and grey wolf hybrid optimization algorithm to obtain a global optimal solution of the output parameters of the fuzzy neural network, and obtaining the joint torque of the mechanical arm; according to the method, the joint output torque can be accurately controlled, the joint position tracking error is reduced, and the overall robustness and stability of a mechanical arm control system are improved.

The present application relates to a kind of narrow body vehicle balance control method based on control moment gyro, belong to narrow body vehicle active roll control system field.The dynamics equation of control moment gyro is established, the active roll dynamics model of narrow body vehicle is calculated to obtain the roll angle error and roll angular velocity error of vehicle, then the active roll controller is designed using sliding mode control method to control the roll angle error and roll angular velocity error, and the rotational angular velocity of control moment gyro frame is obtained;Finally, the control moment gyro on narrow body vehicle is adjusted in real time, and vehicle balance is realized.The vehicle roll scheme in the present application uses control moment gyro device, with high control precision, fast response speed, and independent of suspension system, can realize greater balance torque.By controlling the frame angular velocity of control moment gyro, the dynamic balance of narrow body vehicle when steering can be realized, to assist the safe steering of driver.

The invention discloses a model prediction control method for efficient power generation of a floating eagle type wave power generation device, and belongs to the technical field of renewable energy utilization. The method comprises the following steps: firstly, establishing a kinetic model of the floating eagle-type wave power generation device and a motion model of an eagle-type wave-absorbing floater, and converting into a state space form; acquiring data through a wave test sensor to predict future wave excitation, determining an optimization scheme with maximization of average capture power as a target, applying PTO torque, motion range of the wave absorbing floater and speed constraint, and performing rolling solution to obtain optimal control torque; and finally, data are acquired through hardware such as an inertial measurement unit and a wave measurement buoy, and the PTO system is driven to apply control torque after the data are processed by the main controller.

The invention relates to a control method for dynamically optimizing contact force distribution of a foot-type robot, belongs to the technical field of foot-type robots, and solves the problem that the foot end is easy to sink when the foot-type robot advances in a soft terrain in the prior art. The method comprises the following steps: acquiring real-time ground counter-acting force of each foot of the foot robot in a current gait cycle support phase and joint control information of each foot in a previous gait cycle support phase; based on the joint control information of each foot in the previous gait cycle support phase and the standard ground reaction force time curve, obtaining an expected ground reaction force time curve of each foot in the current gait cycle support phase; based on the expected ground reaction force time curve of each foot in the current gait cycle supporting phase and the corresponding real-time ground reaction force, a PID controller is used for obtaining the control torque of each foot at each moment, the control torque is applied to each joint motor of each foot, and the contact force distribution of each foot is optimized. The walking stability of the foot type robot in the unstructured terrain is achieved.