50results about How to "Improve trajectory tracking accuracy" patented technology

The invention discloses a trajectory tracking control method used for a driverless vehicle. The method includes the following steps that the current position point of a vehicle body is confirmed according to a reference trajectory; a matching point nearest to the current position point of the vehicle is found, and the road curvature of the nearest matching point is obtained according to a two-point curvature obtaining method; according to the current position point of the vehicle and the nearest matching point, a trajectory tracking error is obtained through calculation and comprises a transverse error and a head pointing error; a dynamic model feeding back cornering force on the basis of front wheels is established, and the optimal feedback control rate is obtained by the adoption of an LQR control algorithm; and the cornering force of the front wheels is determined, a front wheel slip angle is obtained on the basis of a reverse tire model, and then the steering wheel angle controlledquantity is obtained and issued to a steering-by-wire system to achieve trajectory tracking control. By the adoption of the method, the stability of trajectory tracking control of the driverless vehicle is improved, the trajectory tracking accuracy is improved, the tire slip angle is restrained, and the possibility that the tire force of the vehicle is saturated under an extreme working conditionand therefore the vehicle loses stability is avoided.

The invention relates to a B spline track planning method of a robot joint space guided by vision, which comprises the following steps: firstly, a 2-DOF (degree of freedom) robot is arranged in a stereoscopic support, an industrial camera is arranged at the front end of the stereoscopic support, and the moving direction of a conveyor belt is perpendicular to the moving plane of the 2-DOF robot; secondly, after the industrial camera obtains a first track point on the conveyor belt, a B spline curve is constructed according to the obtained time node sequence of joints within the time the 2-DOF robot moves to the first track point; thirdly, the constructed B spline curve is prolonged by adding a node vector and a control vertex to allow the B spline curve to go through an added joint position point; and fourthly, a position point on the B spline curve is calculated by adopting a De Boor recursive algorithm, so as to drive the 2-DOF robot to move. The B spline track planning method can realize smooth movement of the robot guided by the vision, and improve the track following precision of the robot.

The invention discloses a robust neural network control system for a micro-electro-mechanical system (MEMS) gyroscope based on sliding mode compensation and a control method of the control system. The control system comprises a given trajectory generation module, a sliding mode surface definition module, a neural network controller, a weight adaptive mechanism module, a sliding mode compensator, an MEMS gyroscope system, a proportional-differential control module, a first adder and a second adder. The control method of the control system comprises the following steps of: establishing an MEMS gyroscope kinetic model based on a sliding mode surface, designing a controller structure, and designing an updating algorithm of a radial basis function (RBF) network weight, so that the trajectory of the MEMS gyroscope is tacked. By the control method, the influence of the unknown dynamic characteristic of the MEMS gyroscope and noise interference can be compensated on line, the vibration trajectory of the MEMS gyroscope completely follows a reference trajectory, and the anti-interference robustness and reliability of the system are improved; the updating algorithm of the network weight is designed on the basis of a Lyapunov stability theory, so that the stability of a closed-loop system is ensured; and a powerful basis is provided for expanding the application range of the MEMS gyroscope.

The invention discloses a micro-gyroscope RBF (Radial Basis Function) network self-adapting control method based on model global approximation. According to the control method, based on a tracking error deign after filtering, a controller comprises a proportion differential item and an RBF neural network item. The RBF neural network item is approximated to an unknown function of a micro-gyroscope system and an updating algorithm based on a weight guarantees the global stability of the system based on a Lyapunov stability theory design. A robust item is added into the updating algorithm to guarantee the boundedness of control input; and the proportion differential item finally maintains a tracking error in any small range. The control method disclosed by the invention can realize high-precision tracking control on the micro-gyroscope system under the condition of no need of knowing about the structure or non-structure parameters of a micro-gyroscope, and in the presence of external interferences; and meanwhile, the robustness and the reliability of the system are improved.

The invention uses the idea of hierarchical structure control optimization to provide a manipulator actuator fault tolerant control system based on a double-layer structure and a method thereof, which belongs to the technical field of automatic control. In order to reduce the computational complexity and improve the instantaneity, a discrete system model under an actuator fault is established in an expansion manner through Taylor series. An FDD unit is designed to initiatively deal with a fault problem. The estimated fault information is introduced into a fault model to realize active fault tolerance. Uncertainties of the actual system are considered. A feedback correction mechanism is used for compensation. A manipulator fault tolerant controller is composed of a trajectory planning layer and a tracking control layer. According to different control objectives of each layer, a controller is designed separately, which is more specific to the problem. The fault tolerant control of the double-layer structure can deal with the existing system constraints, has strong robustness, can effectively solve the problem of the constant deviation fault of a complex manipulator actuator, and ensures the stability and the control performance of the whole system.

The invention discloses a mobile robot trace tracking control method. The mobile robot trace tracking control method comprises the steps of calculating the numerical values of a slip coefficient and the slip rate according to motion mathematical model formulas of the slip coefficient and the slip rate and data detected by A GPS-INS and the information of the expected path, the expected speed and the expected yaw velocity given by a mobile robot decision layer; substituting the numerical values into a kinematic model of a mobile robot and compensating for and calculating the rotating speed of wheels achieving trace tracking to achieve the purpose of accurately tracking an expected trace. The mobile robot trace tracking control method has the advantages that the slippage rate can be calculated at any time; the actual motion state of the mobile robot can be described and represented more truly and accurately; accordingly, the expected trace can be tracked effectively and accurately.

The invention discloses a four-rotor aircraft flight control method based on a backstepping method. The four-rotor aircraft flight control method based on a backstepping method includes the steps: according to the principle of flight mechanics and aerodynamics, establishing a kinetic model of a four-rotor aircraft and simplifying the model: setting the aircraft as a rigid body, setting the structure of the aircraft to be completely symmetrical, setting the center of gravity of the aircraft to coincide with the center of the aircraft, taking the ground coordinate system as the inertia coordinate system, and ignoring changes in the curvature of the Earth and the acceleration of gravity; according to the kinetic model of the four-rotor aircraft, analyzing the coupling relation of the flight control system, and constructing a system control structure graph; and finally according to the kinetic model of the four-rotor aircraft and the system control structure graph, using the backstepping method, combining with the Lyapunov stability principle, and determining the feedback compensation control quantity of the system. The four-rotor aircraft flight control method based on a backsteppingmethod can stably control the position and the attitude of the four-rotor aircraft, and has the advantages of high trajectory tracking accuracy, high response speed, and high anti-interference capability.

The invention discloses a cantilever beam vibration control method based on back-stepping fuzzy sliding mode control. The method comprises the following steps of building a dynamic cantilever beam mathematical model, and performing cantilever beam mathematical model conversion; designing a back-stepping sliding mode controller on the basis of a Lyapunov stability theory, and obtaining a sliding mode control law; designing a fuzzy self-adaptation system on the basis of the Lyapunov stability theory, and obtaining a fuzzy self-adaptation law; simultaneously inputting the output of the back-stepping sliding mode controller and the output of the fuzzy self-adaptation system into the cantilever beam mathematical model; feeding back the output of the cantilever beam mathematical model to the fuzzy self-adaptation system in real time, and ensuring the global stability. The method has the beneficial effects that the relying of a control system on the cantilever beam mathematical model can be avoided; the manufacturing errors and the environment interference are compensated; the parameter study and regulation can be controlled in time, and the global progressive stability of the whole control system is ensured, so that the system reliability and the parameter change robustness can be improved.

The invention discloses an unmanned vehicle route tracking control method based on skid turn and slippage coupling estimation. By the adoption of the method, according to a motion mathematical model expression of a skid turn coefficient and the slip rate, data detected by an GPS-INS, and an expected route, the expected speed and expected yaw velocity information which are given by an unmanned vehicle decision making level, numerical values of the skid turn coefficient and the slip rate are calculated and then reversely substituted to a kinematic model of an unmanned vehicle, the wheel rotationspeed achieving trajectory tracking is obtained through compensation and calculation, and the purpose of accurate tracking of an expected trajectory is achieved. The method has the beneficial effectsthat the skid turn and slippage amount can be calculated in real time, the actual motion state of the unmanned vehicle is described and represented more really and accurately, and the expected trajectory can be tracked effectively and accurately.

The invention discloses an unmanned aerial vehicle flight trajectory tracking control system. The unmanned aerial vehicle flight trajectory tracking control system comprises a trajectory rider, a longitudinal controller and a lateral controller. Under the effect of the unmanned aerial vehicle flight trajectory tracking control system, climb of an unmanned aerial vehicle can be realized fast, and height errors can be eliminated, and flight trajectory tracking can be kept, and overall trajectory tracking accuracy is higher. According to the unmanned aerial vehicle flight trajectory tracking control system of the invention, a sensor can be fully utilized to measure flight state information which is obtained through feedback. The unmanned aerial vehicle flight trajectory tracking control system can realize high control accuracy by fusing more useful information. The unmanned aerial vehicle flight trajectory tracking control system is suitable for complex multi-variable systems such as an aircraft.

The invention discloses a precise trace tracking optimal control method for an uncertain rehabilitation walking training robot. According to the method, a kinetic model of an uncertain rehabilitation walking training robot system is built, a one-order low-pass filter is built, the integral estimation is carried out on the uncertainty influencing the trace tracking precision of the rehabilitation walking training robot, a controller is designed on the basis of a precise feedback linearization method, and a linearization model of the system is built; on the basis of trace tracking errors, speed tracking errors and energy quadrics, a quadratic performance index of the rehabilitation walking training robot system is designed, the optimal control method is adopted, the precise trace tracking of the rehabilitation walking training robot is realized, and the performance index is optimized. Output high-precision PWM (pulse width modulation) signals are provided for a motor driving unit, so that the robot realizes precise tracking on reference trace signals. The control method has the advantages that the uncertainty bound of the system does not need to be known, the trace tracking precision of the rehabilitation walking training robot can be improved, and in addition, the system performance reaches the optimum.

The invention discloses an industrial robot trajectory tracking system and method adopting neural network iterative compensation. The trajectory tracking system is connected with an industrial robot and a measurement device separately, and a follow-up target ball matched with the measurement device is installed on a flange at the tail end of the industrial robot. A trajectory planning module is connected with the input end of the industrial robot through an inverse solution compensation module, a neural network PID module and a robot input interface in sequence, and the output end of the industrial robot is connected with a PID control module through a robot output interface. The trajectory planning module is connected with an error analysis module, the error analysis module is connected with the output end of the measurement device through a measurement output interface, and a measurement control module is connected with the input end of the measurement device through a measurement input interface. By means of the industrial robot trajectory tracking system and method, the inverse solution precision of the robot is improved, the influence of joint errors on the motion trajectory precision is reduced, and the robot is controlled to move according to an expected trajectory through the robot input interface; and the industrial robot trajectory tracking system and method are suitable for occasions with high motion trajectory precision requirements, such as welding, spraying and polishing.

The invention belongs to the technical field of wireless communication and artificial intelligence, and discloses a passive intelligent tracking and positioning method and system, a storage medium, atracking and positioning terminal and Wi-Fi equipment for collecting CSI information. The method comprises: extracting a dynamic propagation path component of each multipath signal by an inter-antennaCSI conjugate multiplication algorithm; estimating the signal parameters of the dynamic propagation path of each multipath signal by a channel parameter estimation algorithm; in combination with an artificial intelligence algorithm, each Wi-Fi device independently estimating a human body motion trail; and fusing the human body motion trails obtained by different Wi-Fi devices in the step 4 by using a multi-device motion trail fusion algorithm. According to the method, multi-channel parameter combination is used for tracking the human body motion trail, and an artificial intelligence algorithmis combined, so that the problems of low precision and poor robustness in the prior art are avoided. According to the invention, a plurality of Wi-Fi devices are combined to carry out human body motion trail tracking, the problem of low human body tracking and positioning precision in the prior art is avoided, and the indoor human body passive tracking and positioning precision is improved.

The invention discloses a path following model prediction control method, system and device, and a storage medium. The method comprises the following steps: constructing a state space model of a vehicle; determining a tire slip angle dynamic constraint, and obtaining tire slip angle information according to the tire slip angle dynamic constraint and the state space model; constructing a path following model of the vehicle, and obtaining front wheel rotation angle information of the vehicle according to the path following model, the state space model and the tire slip angle information; and carrying out path following control on the vehicle according to the front wheel rotation angle information. According to the embodiment of the invention, the tire slip angle can be restrained within a reasonable range under different road adhesion coefficients; and a vehicle trajectory tracking capability is brought into full play, trajectory tracking precision is improved while vehicle driving stability is ensured so that the vehicle automatic driving safety and the vehicle path following control accuracy are improved, the overall performance of the vehicle is increased, and the method, the system, the device and the storage medium can be widely applied to the technical field of vehicle cruise control.

The invention discloses a cross coupling control method for a sliding mode cloud model of a crawler-type mobile robot. The method comprises the following steps of firstly, establishing a crawler-typemobile robot tracking error model and a brushless direct-current motor mathematical model, and then establishing a speed ring sliding mode controller and a cloud model cross coupling controller; for asingle motor, designing the speed ring sliding mode controller, thereby inhibiting non-periodic error and reducing speed tracking error; and for double motors, designing the cloud model cross coupling controller, thereby reducing the composite tracking error. By virtue of the cross coupling control method for the sliding mode cloud model of the crawler-type mobile robot, the tracking error of thecrawler-type robot can be effectively reduced, so that the method achieves relatively high trajectory tracking precision, relatively strong robustness and self-adaptive capability.

The invention discloses a kinetic model of a rehabilitation walking training robot. The mass of a trainee in a coefficient matrix is converted into a random variable, and a random differential equation of the rehabilitation walking robot is established; a controller design method for randomly changing the masses of different trainees is provided; based on a random Lyapunov stability theory, the exponential stability condition of a trajectory tracking error system is constructed, a tracking controller capable of adapting to the random change of the mass of a trainee is obtained, the tracking precision of the rehabilitation walking robot system is improved, and the safety of the trainee is guaranteed. The controller is simple in design and easy to realize, and the controller has no mass information of the trainee, so that the rehabilitation walking robot can be applied to different trainees, the influence of the mass change of the trainee on the tracking performance is avoided, the trajectory tracking precision is improved, and the safety of the trainee is guaranteed.

The invention provides an optimal prediction control method of tracking errors of all shafts of a redundancy rehabilitation walking training robot. According to the control method, on the basis of characteristics of a redundant robot and a dynamic model, a nonlinear feedback predictive controller is designed and discretization prediction models of all shaft sub systems are established; an objective optimization performance function is established by using trajectory tracking errors of all shafts as variables and constraint conditions of the trajectory tracking errors of all shafts, speed tracking errors, and control increments are constructed to obtain optimal prediction control, thereby realizing optimal performances of trajectory tracking errors of all shafts; and the trajectory tracking error and speed tracking error of the redundancy rehabilitation walking training robot are restricted in a designated range to guarantee safety training of a rehabilitee. With the control method, the trajectory tracking precision is improved and safety of the trainer is guaranteed.

The invention discloses a combined sliding mode motion control method of a flexible mechanical arm. Under multiple time scales, the motion control problem of the flexible mechanical arm with disturbance and system uncertainty is researched. Because the flexible mechanical arm has a multi-time-scale characteristic, a controller designed by applying a traditional method is easy to cause an ill-conditioned numerical value problem, and based on a singular perturbation theory, the flexible mechanical arm is modeled into a singular perturbation system with singular perturbation parameters and decomposed into a fast subsystem and a slow subsystem which describe rigid body motion and flexible vibration. Under the slow time scale, with consideration of the influence of external disturbance and parameter uncertainty on the system, a self-adaptive sliding mode controller (slow controller) with a disturbance observer is designed to track the trajectory of the flexible mechanical arm. Under a fasttime scale, a robust sliding mode controller is designed to achieve flexible vibration suppression in order to eliminate the influence of vibration states and the like under an unmodeled dynamic scaleand a slow time scale on the design of the controller. Finally, the slow controller and the fast controller are combined by using a singular perturbation theory to realize a dual control target of trajectory tracking and vibration suppression. The test results show that the method is high in robustness and good in control effect.

The invention discloses an unmanned ship group formation cooperative control method considering a time-varying drift angle and attitude adjustment. The method comprises the following steps of establishing a unified unmanned ship group formation graph theory representation method; establishing a three-degree-of-freedom kinetic model and a kinematics model which are universal for the unmanned ship; giving an objective function of formation control according to the planned path, the attitude parameter and the expected course; according to the established kinetic model and kinematic model, constructing an expansion observer for model uncertainty and external disturbance estimation; and according to the established expansion observer and the control target, designing an unmanned ship formation cooperative active-disturbance-rejection control law. The anti-disturbance control method based on linear tracking is provided, the self-adaptive control rate is given, time-varying drift angle compensation and attitude adjustment of the unmanned ship group formation are achieved, and therefore integrated regulation and control of formation position tracking and attitude adjustment of the unmanned ship group can be achieved.

The invention discloses a steering wheel zero offset self-learning unmanned vehicle trajectory tracking method. The method comprises a road line type fitting algorithm, a steering wheel zero offset estimation algorithm and a vehicle kinematics model control algorithm. The road line type fitting algorithm uses a section of expected road point sequence in front of a vehicle as input to fit road linetype parameters. Steering wheel zero offset is estimated by a steering wheel zero offset estimation algorithm according to the current and historical road line type parameters. A vehicle kinematics model control algorithm is combined with the road line type parameters, the steering wheel zero offset and the vehicle kinematics model to calculate and output a steering wheel angle for vehicle trajectory tracking control. The method aims to improve the intelligent level of unmanned vehicle trajectory tracking control and improve the tracking precision.

The invention discloses a speed constraint tracking control method for service robots suitable for different users. The method comprises the following steps: 1) establishing a stochastic differentialequation for depicting mass changes of different users; 2) constraining the movement speed of a robot in the axial direction and the rotation angle direction; and 3) establishing a tracking error system by using the movement speed constrained in the step 2) and combining the stochastic differential equation in the step 1), and constructing an index stability condition of the tracking error systembased on a stochastic stability theory to realize a speed constraint tracking control method suitable for different users. An adopted controller is simple in design and easy to implement, quality information of a user does not exist in the controller, and therefore the service robot can be applied to different users, and the trajectory tracking precision is improved; meanwhile, the method for constraining the movement speed is provided for a service robot system described by a stochastic differential equation, sudden change of the speed of the robot is avoided, and the safety of a user is guaranteed.

According to the optimal trajectory planning method for the multi-degree-of-freedom mechanical arm based on the model, the optimal trajectory planning method is completed through cooperation of the upper computer, the mechanical arm controller, the feedback control module, the mechanical arm and the optimal trajectory planning module, and the optimal trajectory planning method for the multi-degree-of-freedom mechanical arm based on the model is reasonable in design; a mechanical arm dynamic system model is established by adopting a non-causal modeling language, so that a differential state equation of a mechanical arm system with four or more axes is expressed, and the application of an optimal control method in an optimal trajectory planning task of the mechanical arm with four or more axes can be realized.

The invention discloses a multi-rotor flight control method based on nonlinear inverse compensation. The method comprises the following steps: firstly, performing kinetic analysis on a multi-rotor aircraft, and establishing a multi-rotor kinetic equation according to the Newton's second law and the kinetic moment theorem; secondly, establishing an equivalent model of the brushless direct current motor, deriving a relational expression between the rotating speed of the motor and the force and moment borne by the multiple rotors, and determining a multi-rotor flight control equation set; and finally, establishing inverse mapping of a nonlinear link, establishing a pseudo-linear system through inverse mapping, and designing a controller based on an inner and outer loop control structure. Themulti-rotor flight control method based on nonlinear inverse compensation is high in trajectory tracking precision, high in response speed and high in anti-interference capability, and can stably andaccurately control the position and attitude of the multi-rotor aircraft.

The invention relates to nonlinear control of a tilting three-rotor unmanned aerial vehicle, and aims to consider the influence of external disturbance on position control of the tilting three-rotor unmanned aerial vehicle, coordinate the relation between a position subsystem and an attitude subsystem and realize accurate control. The invention discloses a tilting type three-rotor unmanned aerial vehicle trajectory tracking control method based on an observer, and the method comprises the steps: firstly designing a position controller based on a backstepping method, and giving a given attitude angle of an inner ring attitude subsystem; then, a finite time convergence observer is designed to compensate for external disturbance, attitude tracking errors are asymptotically converged in combination with a robust controller based on a sliding mode, and finally trajectory tracking control over the tilting type three-rotor unmanned aerial vehicle is achieved. The method is mainly applied to the nonlinear control occasion of the tilting three-rotor unmanned aerial vehicle.

The invention belongs to the technical field of rotor wing unmanned aerial vehicles, and discloses a multi-bullet-type gun-carrying striking type police unmanned aerial vehicle and a control method. The method comprises the steps of collecting target images through binocular camera shooting motion, face recognition is conducted, and the recognized images are transmitted to a single-chip microcomputer with an information processing function; performing target tracking through a sighting device, and transmitting the acquired moving position information of the target to a single-chip microcomputer with an information processing function; after the single-chip microcomputer processes the information, transmitting the information to a target end mobile phone APP through the wireless communication device for manual or automatic control. According to the method, aiming is carried out through the carried binocular camera shooting movement and sighting device, the accuracy is high, face recognition, target tracking and selective striking can be carried out, and the practicability is higher.

The invention relates to a spacecraft tracking control method, in particular to a spacecraft tracking control method based on an integrated linear operator and an anti-saturation technology. The objective of the invention is to solve the problem of low attitude orbit tracking maneuvering control performance of a spacecraft caused by the fact that the spacecraft is subject to unfavorable working conditions such as inertia parameter uncertainty and input saturation in a short-distance space task. The method comprises the following steps: measuring and obtaining attitude and orbit states of a target and a tracking spacecraft, determining a relative pose configuration between the target and the tracking spacecraft, and obtaining a pose tracking error of the tracking spacecraft; determining a speed tracking error under a tracking spacecraft body coordinate system; defining a filtering error of the target and the tracking spacecraft under the coordinates of the tracking spacecraft body; introducing a linear operator, and determining an inertial parameter updating matrix; obtaining real-time estimation of inertial parameters; obtaining an anti-saturation auxiliary system state vector; and obtaining a control input vector to execute a pose integrated tracking control strategy. The method is applied to the field of spacecraft tracking control.