578 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 provides an exoskeleton robot self-adaptive control method and related equipment, and relates to the technical field of exoskeleton robots. The method comprises the following steps: acquiring motion information and position information of each movable joint in the exoskeleton robot; inputting the motion information and the position information into a pre-trained angle prediction model to obtain a target angle of each movable joint; the difference value between the target angle and the actual angle output by the exoskeleton controller serves as an angle error; constructing a virtual control quantity based on the angle error; the virtual control quantity is combined with motion parameters of the exoskeleton robot to be input into a disturbance observer, and estimated disturbance is generated; the angle error, the virtual control quantity and the estimated disturbance are input into an adaptive neural network controller, and the control torque of each movable joint is obtained; and based on the control torque of each movable joint, generating a control signal of each movable joint. The method and the device have good control precision.

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 belongs to a robot control method, and provides a human-guided robot-environment interaction self-adaptive control method and a related device for solving the technical problems that an existing human-guided robot-environment interaction control method is insufficient in motion stability, low in human operator safety and low in control precision. And estimating an optimal impedance parameter through a state space model, and learning a human-guided reference trajectory through a neural network in combination with the optimal impedance parameter. Then, in combination with a robot Jacobian matrix and a human-guided reference trajectory, a reference joint speed and an estimated acceleration of a joint space are obtained through closed-loop inverse kinematics, then network parameters of a robot dynamic model are obtained through approximation of an uncertain dynamic model, and finally, the robot dynamic model is obtained through combination with the reference joint speed and the network parameters of the joint space. And the mechanical arm control torque is obtained through the offset width fuzzy neural network. Accurate and compliant control under uncertain motion and dynamics conditions is realized.

The invention discloses an underwater propeller thrust distribution control method and system based on QP optimization, which are used for avoiding redundant power consumption caused by improper distribution under redundant propeller configuration and prolonging underwater operation time and endurance mileage of a robot. The method comprises the steps that a preset attitude control instruction of the underwater robot and actual attitude information fed back by a current sensor are acquired, total disturbance acting on the underwater robot is estimated in real time based on the active disturbance rejection control principle, and expected total control force and total control torque instructions are calculated; constructing a quadratic programming problem based on the total control force and the total control moment instruction; solving a quadratic programming problem to obtain a first thrust instruction of each propeller after optimization; whether a propeller fault exists or not is diagnosed in real time, and when the fault is detected, a control efficiency matrix or a physical limitation constraint in the quadratic programming problem is dynamically adjusted; and solving again based on the adjusted quadratic programming problem to obtain a second thrust instruction of each propeller under fault tolerance.

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 discloses an improved FWN-based torque double-domain constraint control method for a flexible arm space robot, and the method comprises the steps: constructing a dynamic model of a flexible arm space robot system, and constructing a torque double-domain constraint control system mathematical model in combination with the posture of a body and the constraint of the amplitude and the amplitude change rate of the control torque of a joint hinge; a torque double-domain constraint controller based on the improved fuzzy wavelet network is constructed, the torque double-domain constraint controller meets a torque double-domain constraint control system mathematical model, and corresponding control laws comprise an improved fuzzy wavelet network control law and an improved fuzzy wavelet network parameter self-adjusting control law; and the body attitude angle and the joint angle of the robot and the deformation coordinate and the vibration amplitude of the flexible arm are adjusted through the control torque which is generated by the torque double-domain constraint controller and subjected to double-domain constraint till the control target is achieved. According to the method, the problems of saturation effect and dynamic performance degradation of the actuator caused by insufficient consideration of double-domain constraints of the torque amplitude and the change rate of the joint driving mechanism are solved.

The invention discloses a cooperative control method for conversion of torque control and rotating speed control of an engine and a generator and a medium. The method comprises the following steps: calculating available recovery torque of a generator, and requesting an engine to load reserve torque by a vehicle control unit; activating an engine rotation speed control flag bit, an engine control rotation speed mode and a generator control torque mode; determining a target rotating speed and a target torque, further determining a generator torque filtering rate, and respectively controlling and adjusting the rotating speed and the torque; and exiting the engine rotation speed control flag bit, the engine control torque mode and the generator control rotation speed mode. By increasing the reserve torque of the engine, the torque adjusting capacity of the engine is improved, the engine and the generator are cooperatively controlled, and engine speed fluctuation is reduced.

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.

The invention provides a flywheel unloading method based on an electric pushing mechanical arm in a position protection period. The flywheel unloading method comprises the steps that a joint corner combination is selected when the thrust direction is in a position protection allowable range; the control torque under the joint rotation angle combination of each mechanical arm is determined, and an initial table look-up matrix is established; determining an optimal torque and a torque error allowable range; according to the control torque, the optimal torque and the torque error allowable range, grade division is conducted on the joint corner combination; constructing a cost function according to the optimal torque and the control torque; on the basis of grade division, the smaller the cost function is, the higher the priority of the joint corner combination is; selecting a joint corner combination with the highest priority from the initial look-up table matrix, performing permutation and combination of joint corners around the joint corner combination in a fine step length manner, determining a corresponding control moment, forming a second-order look-up table matrix, and selecting a joint corner combination with the highest priority; and circularly selecting the joint corner combination with the highest priority to obtain a final joint corner combination.

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.

A system for determining a secondary axle torque of a hybrid vehicle is disclosed. The hybrid vehicle includes a primary axle driven by an engine and a secondary axle driven by an electric motor. The system includes one or more sensors configured to detect a driver torque request, and a control module in communication with the one or more sensors. The control module is configured to receive data from the one or more sensors indicative of the driver torque request, calculate a primary torque target for the primary axle based on an optimal engine torque, calculate a secondary torque target for the secondary axle based on the calculated primary torque target and the driver torque request, and generate a secondary torque command to drive the secondary axle based on the calculated secondary torque target and the driver torque request. Other example systems and methods are also disclosed.

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 relates to a vehicle escape method, device and equipment and a medium. The method comprises the steps that the suspension height and the first slip rate of each wheel are determined; judging the escape working condition of the vehicle according to the suspension height and the first slip rate; wherein the detrapping working conditions comprise a wheel slipping working condition and a working condition that wheels sink into the ground; when the disengagement working condition is the wheel slipping working condition, a first disengagement strategy is executed, and the first disengagement strategy comprises the steps that the slip rate of slipping wheels is increased, and torque transfer is controlled between a front axle and a rear axle; and when the detrapping working condition is that the wheels are trapped in the ground, a second detrapping strategy is executed, and the second detrapping strategy comprises the step of controlling the height of the suspension. The method can adapt to various different escape working conditions, the suspension, the slip rate, the torque of the front shaft and the torque of the rear shaft and the like can be comprehensively controlled in the escape strategy, and the escape capacity of the vehicle is effectively improved.

The invention discloses an anti-interference flight control method for a multi-rotor unmanned aerial vehicle. The method comprises the following steps: establishing an attitude dynamic model of the multi-rotor unmanned aerial vehicle; according to a moment of momentum theorem and an Euler equation, establishing an unmanned aerial vehicle attitude kinetic equation; setting a control moment in the man-machine attitude kinetic equation as a dependent variable, and performing first-order Taylor expansion at any point; adding expectation into the expanded kinetic equation to obtain an improved incremental nonlinear dynamic inverse controller; using real-time measured values of motion variables of the multi-rotor unmanned aerial vehicle in the improved incremental nonlinear dynamic inverse controller, and optimizing the improved incremental nonlinear dynamic inverse controller by adopting a control closed-loop transfer function of an attitude angular acceleration loop and a disturbance closed-loop transfer function of the attitude angular acceleration loop; and controlling the attitude of the multi-rotor unmanned aerial vehicle by using the optimized improved incremental nonlinear dynamic inverse controller. According to the method, the dependence of the unmanned aerial vehicle control method on the model can be reduced, and the stability of the multi-rotor unmanned aerial vehicle is improved.

The invention discloses a vehicle, a control method and device thereof and a controller, and relates to the technical field of vehicles. Under the condition that the vehicle runs on the road of the target type and an acceleration instruction is received, if the controller determines that the expected output torque of the power system is larger than the target torque and the torque rising gradient is larger than the gradient threshold value, the output torque of the power system can be increased according to the target gradient smaller than the torque rising gradient. Under the conditions that the output torque of the power system reaches the expected output torque and the slip rate of the wheels is larger than the slip rate threshold value, the controller can trigger the traction force control system to conduct torque control. Therefore, when the wheels slip, the stability of the vehicle can be improved by controlling the torque through the traction force control system. And before, when the vehicle predicts that the vehicle slips on the basis of the expected output torque and the torque rise gradient, the torque rise gradient can be limited in advance, so that the vehicle is prevented from slipping to a great extent, and the driving stability of the vehicle is further 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 present disclosure relates to a torque compensation method and related device for a steer-by-wire system of a vehicle. The method includes: determining a required torque for steering feel of the steering system of the vehicle; obtaining vehicle speed information and steering wheel angle information of the vehicle, and obtaining a first output torque of a steering column in the steering system; determining a first required torque of a torque compensation motor from a preset torque compensation torque table according to the vehicle speed information and the steering wheel angle information; determining a compensation torque of the torque compensation motor according to the first output torque, the first required torque, and the required torque for steering feel, and compensating the first required torque according to the compensation torque to obtain a second required torque of the torque compensation motor; and controlling the torque compensation motor to output a torque for steering the steering system according to the second required torque. The present disclosure can not only improve the NVH performance, driving stability and safety of the vehicle, but also reduce the size of the feel simulation motor of the steer-by-wire column, and is more easily arranged in a vehicle with a small space.

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 embodiment of the invention provides a control method and device of a driving motor and a motor controller. The control method of the driving motor comprises the following steps: when it is determined that a current road is a non-bumpy road, identifying whether the driving motor enters a torque zero-crossing conversion working condition or not; and under the condition that the driving motor enters the torque zero-crossing conversion working condition, compensation torque is determined, control torque is determined based on the compensation torque, and the control torque is used for controlling the driving motor to output torque. By the adoption of the scheme, the problem that when a current road is a bumpy road, torque zero-crossing conversion control is carried out, and consequently vehicle vibration is more serious can be solved.

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.

A method for limiting active acceleration of a vehicle based on driving situations and a vehicle drivable thereby are provided. The method includes detecting presence of an acceleration limitation situation based on driving situation information. The method also includes, in response to detecting the presence of the acceleration limitation situation, generating an acceleration limit based on situation type information identified in the driving situation information. The method additionally includes determining, as control torque, a smaller torque among an acceleration torque limit based on the acceleration limit and required torque according to a driving maneuver request. The method further includes controlling driving of the vehicle based on acceleration according to the control torque on a path corresponding to the acceleration limitation situation.

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 relates to flight control of a tilt rotorcraft, in particular to a nonlinear super-spiral robust control method for the tilt rotorcraft, and aims to realize nonlinear control of the tilt rotorcraft on the basis of not simplifying or linearizing a dynamical model and quickly track expected speed and attitude instructions, and the technical scheme adopted by the invention is that the nonlinear super-spiral robust control method for the tilt rotorcraft comprises a nonlinear super-spiral robust control method for the tilt rotorcraft. Establishing a tilting rotorcraft dynamic model; and designing a super-spiral attitude control law based on the rotation matrix to obtain a control moment of the aircraft, then carrying out real-time approximation on an inverse model of the dynamic model by using an approximation characteristic of an RBF neural network, and calculating an actual control quantity of the aircraft by using the control moment so as to realize automatic control of the tilt rotorcraft. The method is mainly applied to design, manufacturing and flight control occasions of tilt rotorcrafts.