281 results about "Control torque" patented technology

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 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.

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 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 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.

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 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 invention provides a control method and system for a five-degree-of-freedom marine crane under a non-inertial system, and relates to the technical field of automatic control of cranes. The method comprises the following steps: acquiring a real-time state variable of the crane under a non-inertial system; the state variables are input into a self-adaptive radial basis function neural network, a lumped disturbance estimated value is obtained, and the neural network is designed based on a five-degree-of-freedom dynamical model established by utilizing a Lagrange equation and a virtual work principle under a ship coordinate system and considering ship six-degree-of-freedom motion and installation position offset; calculating a tracking error function according to the state variable and the expected trajectory; and inputting the disturbance estimation value and the error function into a feedback controller, calculating to generate a control torque, and outputting the control torque to an execution mechanism to drive the crane to track an expected trajectory and suppress load swing. According to the method, direct modeling and control under a non-inertial system are realized, the problems of coordinate transformation disturbance and singularity caused by inertial system modeling are solved, and the trajectory tracking precision and the anti-interference robustness are improved.

The invention provides a Markov jump-based mechanical arm preset time trajectory tracking control method, which comprises the following steps of: calculating a trajectory tracking error by establishing a two-degree-of-freedom mechanical arm dynamic model with a Markov jump characteristic; a trajectory tracking error is subjected to nonlinear transformation, a nonsingular terminal sliding mode surface is constructed in combination with a preset convergence time upper limit function, and then a control torque is synthesized through an equivalent control item and a robust switching item containing a sliding mode surface sign function and a switching gain to drive a mechanical arm. And the trajectory tracking error is difficult to converge in the preset time.

The invention provides a wafer transmission mechanical arm control method, system and equipment, and relates to the technical field of automatic control of semiconductor manufacturing equipment. The method comprises the steps that the joint position and the joint angular velocity of the mechanical arm are obtained; calculating a joint position tracking error; the joint position and the joint angular velocity are input into a model identifier, and the compensation amount for the uncertainty of a dynamic model of the mechanical arm is obtained; a self-adaptive dynamic programming framework is used, the joint position tracking error, the performance index function and the compensation amount are combined to generate an optimal control strategy, and the compensation amount is used for correcting a preliminary control strategy output by the framework; finally, control torque is output to drive the mechanical arm to move. Through the cooperation of the model identifier and the self-adaptive dynamic planning framework, the dependence on an accurate mathematical model is effectively reduced, the long-term comprehensive performance of the mechanical arm in the aspects of speed, precision and energy consumption can be learned and optimized online, and the wafer transmission efficiency and the equipment adaptability are improved.

The invention discloses a multi-degree-of-freedom flying mechanical arm aerial operation stability control method and system, and relates to the technical field of aircraft control. The method comprises the steps that attitude information and current contact force of a flying mechanical arm are obtained; constructing an attitude control model according to the attitude information; constructing an impedance model according to expected inertia, damping, a stiffness matrix, a tail end pose, a tail end speed, a tail end acceleration, a tail end reference trajectory, the current contact force and the expected contact force; calculating a joint control moment according to the impedance model; calculating a comprehensive performance index according to the attitude control model and the impedance model; and according to the comprehensive performance index and the joint control torque, stable control over the flying mechanical arm is conducted. The attitude control model and the impedance model can be combined to calculate the comprehensive performance index so as to adjust the control parameters of the flying mechanical arm, so that stable control of the flying mechanical arm is realized, and the control precision and the flight stability are improved.

The invention provides a jet pipe array missile pitching channel jet flow opening method, device and equipment and a medium. The method comprises the steps that corresponding total thrust is calculated according to pitching control torque needed by a missile; generating a plurality of spray pipe opening combinations capable of providing total thrust according to the thrust of a single spray pipe in the spray pipe array, and taking the spray pipe opening combinations as initial candidate modes; a sequential constraint rule from the middle to the two sides is applied to each nozzle opening combination in the initial candidate modes, and candidate modes conforming to the constraint rule are obtained; calculating a jet amplification factor of the candidate mode conforming to the constraint rule in the current flight state, and evaluating the influence degree of jet interference; the candidate modes with the jet amplification factors smaller than the preset minimum threshold value of the jet amplification factors and conforming to the constraint rule are removed, and the remaining candidate modes conforming to the constraint rule serve as jet opening modes, so that the problem that the control effect is poor due to poor control torque adjustability, control coupling, insufficient spray pipe utilization rate and jet interference influence is solved.

This application relates to a vehicle control method. The method includes: when the vehicle is in an anti-motion sickness mode, determining the vehicle's driving information, including lateral acceleration; if the vehicle meets torque control activation conditions based on the lateral acceleration, determining a control torque that matches the lateral acceleration and the rate of change of the vehicle's lateral acceleration; determining a required wheel-side torque that matches the anti-motion sickness mode; and determining a target torque based on the control torque and the required wheel-side torque, so as to control the vehicle's movement according to the target torque. This method helps alleviate motion sickness and improve passenger comfort.

A method of controlling stability of a motorized vehicle having an electric motor as a drive source includes determining a slope of a road ahead, when sensing a sudden slope change point as a result of determination, determining a correction section based on the sudden slope change point, and correcting stability control torque in the correction section to compensate for motion of the vehicle body due to a change in the slope of the road using a pitching motion of the vehicle body caused by the torque of the electric motor.

The application provides a mechanical arm control method and system based on an adaptive force field, wherein 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 an adaptive force field model constructed, an auxiliary force, including a normal force, a tangential force and a viscous force, applied to the patient is calculated. Based on the end posture of the mechanical arm and a target posture, an auxiliary torque applied is calculated. According to the auxiliary force and the auxiliary torque, a joint control torque is obtained, and a dynamic torque of a robot dynamics model and a null space control torque are obtained. In combination with the joint control torque, the dynamic torque and the null space control torque, a comprehensive control torque for controlling the mechanical arm is obtained. In this way, adaptive adjustment of the auxiliary force is realized based on the position, speed and direction of the patient, time freedom is obtained in the motion of the adaptive force field, and the patient can obtain more active motion freedom under the assistance of the space force field.

The invention discloses a control torque determining method of a motor in a wheel steering system and a rear wheel steering method, the wheel steering system comprises the motor and a rack, the control torque determining method of the motor comprises the steps that input information is acquired, and the input information comprises target parameter information and actual parameter information of the rack or the motor; according to an error between the actual parameter information and the target parameter information, performing proportional-integral-differential operation to obtain a target control torque for controlling the motor, so that the motor drives the rack to move under the control of the target control torque; wherein when the integral operation of the proportional-integral-differential operation is carried out, the integral operation result is limited within a set range, and the set range is related to the error. According to the method for determining the control torque of the motor in the wheel steering system, the operation range of the integral term in PID control is limited, so that overlarge motor control torque and system oscillation caused by excessive accumulation of the integral term are avoided, and the energy consumption of continuously outputting high torque by the motor is reduced.

The application provides a water surface and underwater heterogeneous collaborative control method and device based on a preset time disturbance observer, and the control method mainly comprises the following steps: a water surface unmanned ship controller calculates an expected control torque according to a specified expected trajectory, actual state information of the unmanned ship body and a compensation value obtained by an observer; a underwater unmanned vehicle controller calculates an expected control torque according to an expected trajectory obtained by a guidance method, actual state information of the water surface unmanned ship, actual state information of the underwater unmanned vehicle body and the compensation value obtained by the observer; and the water surface unmanned ship and the underwater unmanned vehicle are collaboratively controlled in a heterogeneous mode. The application combines vertical projection and line-of-sight method to complete the guidance of the water surface and underwater heterogeneous collaborative control; the preset time disturbance observer is used to estimate external disturbance, and the disturbance is compensated in the controller to improve the anti-interference ability of the system; and the improved adaptive integral terminal sliding mode control method improves the robustness and rapidity of the system while increasing the tracking accuracy of the system.

Device (110) and method for controlling a steering wheel actuator (106) of a steering system (102) for creating a steering feel, wherein an actual steering speed and a target steering speed are provided for controlling the steering speed of the steering system (102), a control torque for the steering wheel actuator (106) is determined on the basis of a difference between the actual steering speed and the target steering speed, and the steering wheel actuator (106) is controlled to apply the control torque. Vehicle (100) comprising the device (110).

The invention discloses a simulation-to-reality migration method and device based on a residual torque network. The method comprises the steps that real joint movement tracks of a real robot under multiple reference tracks are collected; in a simulation environment, initializing according to a real track state, jointly driving a simulation robot by combining a control torque output by a simulation controller and a compensation torque generated by a residual torque network, and generating a simulation joint motion track; a residual torque network is trained by taking minimization of an error between simulation and a real track as a target, and dynamic deviation between simulation and a real machine is compensated; training a reinforcement learning control strategy network in a simulator integrated with the network; and finally, directly deploying the trained strategy network to a real robot. According to the method, the dynamic difference between simulation and reality can be effectively reduced, the stability and success rate of strategy migration are improved, and the method is suitable for simulation-to-reality migration of various robots.

The invention discloses a knee joint orthosis and an orthosis torque quantitative control and data acquisition method, the knee joint orthosis comprises a thigh frame, a shank frame, a thigh bandage, a shank bandage and a hinge connecting the thigh frame and the shank frame, and the knee joint orthosis further comprises an angle quantitative adjusting mechanism and a torque monitoring system. The included angle between the bandage and the horizontal plane can be accurately changed and adjusted by changing the first slot position of the first sliding block part or changing the second slot position of the second sliding block part or simultaneously changing the slot positions of the first sliding block part and the second sliding block part. The change of the geometric parameter directly causes the change of the tension of the bandage, so that the accurate control of the orthopedic torque is realized. The torque monitoring system can monitor and output quantitative data of orthopedic torque in real time, and a complete closed-loop control system is formed. Compared with a traditional device, according to the scheme, the orthopedic torque capable of being quantitatively adjusted is provided, more importantly, a complete monitoring feedback mechanism is established, and the whole mechanical adjusting process is visible, measurable and controllable.

This application provides a preset performance dynamic surface trajectory tracking control method for a robotic arm system. The method includes the following steps: Step 1, analyzing the total kinetic and potential energy of the robotic arm system using the Lagrange formula, and solving for the control torque using a pneumatic artificial muscle mechanics model and rotational laws to establish a dynamic model of the robotic arm system; Step 2, designing a fixed-time disturbance observer to monitor the total disturbance of the system in real time, addressing the strong nonlinearity and joint coupling and frictional disturbance problems of the robotic arm system; Step 3, designing a preset performance fixed-time dynamic surface controller to compensate for the total disturbance of the system in real time, and designing a control law to enable the angular positions of each joint of the robotic arm system to quickly track the desired target trajectory signal within the allowable error range, thereby achieving the preset transient and steady-state performance constraints within a fixed time and ensuring that all signals of the multi-joint pneumatic robotic arm closed-loop system are bounded.

The application discloses a kind of asymmetric configuration satellite attitude maneuvering process coupling compensation method, comprising: establishing the satellite attitude dynamics model including the non-diagonal item of moment of inertia matrix;Read current attitude sensor data, and calculate deviation quaternion and deviation angular velocity;According to the attitude dynamics model and current angular velocity data, calculate coupling compensation feedforward control torque;Based on the coupling compensation feedforward control torque, deviation quaternion and deviation angular velocity, the control torque after compensation is calculated;The control torque after compensation is limited and priority torque distribution, and the final control torque is obtained;Final control torque is sent to actuator drive satellite and carries out attitude maneuvering.Solve the problem that coupling effect caused by inertia product cannot be effectively compensated when asymmetric configuration satellite is in large-angle attitude maneuvering in prior art, and then affect control precision and stability.