9results about How to "Realize trajectory tracking" patented technology

The invention discloses a seven-degree-of-freedom upper limb exoskeleton and an on-demand auxiliary control method thereof, provides mechanical structure design and joint modular design of the seven-degree-of-freedom upper limb exoskeleton, and deduces kinematics and dynamics models of an upper limb exoskeleton system according to the mechanical structure design and the joint modular design. On the basis, the design of a control system of an upper limb exoskeleton system is provided, an outer ring uses an impedance model for auxiliary force calculation, an energy function and a Horf controller are combined for online adjustment of training trajectory frequency, radius, auxiliary force and the like, the auxiliary force is converted into an expected trajectory of an exoskeleton through the impedance model, and the expected trajectory is transmitted to an inner ring controller; a trajectory tracking controller based on BLF design is used in an inner ring, and dynamic characteristics are estimated based on time delay estimation and an RBF neural network. According to the method, the adaptability of the upper limb exoskeleton mechanical structure and the human body is improved, the influence of dynamic characteristics in the trajectory tracking process is effectively reduced, the training trajectory can be adjusted online, and a good on-demand auxiliary effect is achieved.

The invention discloses a self-adaptive sliding mode ship trajectory tracking control method based on output redefinition, and the method comprises the steps: S1, building an under-actuated ship mathematical model, and redefining the position of the under-actuated ship mathematical model; s2, designing a position tracking error, and performing derivation on the position tracking error; s3, designing a first linear sliding mode surface and a second linear sliding mode surface according to the position tracking error and the tracking error after derivation; s4, designing longitudinal control force and yawing control torque of the ship based on the first linear sliding mode surface and the second linear sliding mode surface in combination with an adaptive technology; and S5, position tracking errors are adjusted through the longitudinal control force and the yawing control torque, convergence of the position tracking errors is achieved, and therefore trajectory tracking is achieved. According to the method, the under-actuated problem is solved by designing the ship longitudinal control force and the yawing control moment of the under-actuated ship mathematical model; and meanwhile, the position tracking error is adjusted through the longitudinal control force and the yawing control torque, so that the tracking error can be quickly converged, and trajectory tracking is realized.

The invention discloses a four-rotor lifting system anti-swing robust control method suitable for a non-ideal actuator condition, is applied to the field of automatic control of aircrafts, and aims to solve the problem that the influence of a non-ideal actuator on system performance is not considered in the prior art. The method comprises the following steps: firstly, modeling a non-ideal actuator link by using a first-order transfer function, and identifying parameters in a model through experimental data; on the basis of obtained model information, an intermediate ring, namely a robust dynamic compensator, is additionally introduced on the basis of original four-rotor position-attitude double-loop control, so that the influence caused by a non-ideal actuator is eliminated. The link can be decoupled from the original position and attitude control of the four rotors, so that the control of the four-rotor lifting system and the compensation of non-ideal actuator interference can be realized at the same time.

According to the robot self-adaptive controller adopting robust control, control methods of robust control and self-adaptive control are selected, a mechanical arm is adopted as a research object, modeling and control research results of a two-degree-of-freedom mechanical arm can be expanded to an n-degree-of-freedom mechanical arm, and the robot self-adaptive controller adopting robust control is provided. Therefore, the method can be applied to the field of industrial robot control development. Different from other nonlinear control methods such as traditional PID (Proportion Integration Differentiation) control and the like which have the characteristic that different constraints in an actual system are not considered, the mechanical arm is controlled by adopting a model robust adaptive algorithm, and the robust adaptive control method can realize trajectory tracking control without establishing an accurate system model.

This invention relates to an event-triggered system regulation and control method in a network control system. This method ensures the safe operation of the network control system even when it is subjected to a DoS attack, achieving actual trajectory tracking and disturbance suppression. Specifically, this invention ensures that the network control system can achieve actual trajectory tracking and disturbance suppression even under DoS attacks; that is, the system's tracking error can be arbitrarily reduced by adjusting the event triggering mechanism parameters. This invention has excellent practicality and accuracy and can be applied to various practical network control systems, such as vehicle networking control systems and networked motor control systems.

The application relates to the field of finished infusion detection, and discloses a quality online detection method and system for finished infusion in a static preparation center, which comprises the following steps: collecting a continuous transmission image sequence, establishing a space affine mapping relationship by using a characteristic anchor point, offsetting a displacement vector deviation through coordinate system alignment, and determining a dynamic displacement trajectory of a target inside a fluid; laterally injecting a linear polarization detection light beam into a detection channel, synchronously collecting scattering light intensity signals by using orthogonally arranged detection channels to calculate a depolarization rate; extracting a background gray value to correct a judgment threshold value, and identifying a solid foreign matter in combination with a motion trajectory and the corrected judgment threshold value; the application captures tiny particles by virtue of anisotropic characteristics of phase interfaces, strips bubbles from deformation interference, realizes self-adaptive matching of detection parameters to optical properties of a liquid medicine, and guarantees high-throughput operation in the field of medical quality control.

The invention discloses an advanced active learning method for helicopter trajectory tracking based on PID and reinforcement learning, and the method comprises the steps: firstly obtaining an effective flight sample for the construction of a helicopter intelligent flight control system through the parameter selection and multi-source data integration of the multi-source data according to the obtained actual flight multi-source data of a helicopter; the samples are controlled based on helicopter flight. The invention designs a helicopter flight control method based on advanced active learning, and aims to extract a flight control rule from a limited flight sample and improve the performance of a flight control and decision-making system through adaptive model adjustment and self-supervision auxiliary tasks.

The invention discloses a ground truss model-based planar rigid body guide mechanism automatic generation method, which comprises the following steps of: planning a motion track of an end effector, and dividing a design domain to initialize a ground truss model; determining a motion form of a driving rod in the model, adding a load to an end effector, and initializing iteration parameters of a moving asymptote; calculating strain energy in the model, performing kinematics analysis, and calculating a target function value; inputting the target function and the design variable into an optimizer to construct a Lagrange duality problem, and analyzing and calculating the Lagrange duality problem to obtain an updated parameter of the optimization variable; when the iteration step number is greater than a set value or the objective function is satisfied, forcibly stopping the iteration process; otherwise, continuously calculating the strain energy in the model and carrying out kinematics analysis, and repeating iteration until the convergence condition is met; and after the iterative design is finished, the configuration is judged through motion simulation, mechanism simplification is realized, and the design is completed. According to the method, mechanism model selection, size generation and trajectory tracking in the topological optimization process are reliably realized.

The application discloses a two-wheeled vehicle self-balancing trajectory tracking control parameter updating method and a two-wheeled vehicle, and the method comprises the following steps: constructing an ESO-ADRC-MPC layered anti-disturbance controller comprising an upper-layer trajectory controller and a lower-layer roll controller to obtain a target roll angle and a front wheel steering angle control instruction; and constructing a perception-decision-evaluation network comprising a perception module, a decision module and an evaluation module to perform online self-learning updating on a prediction control parameter of the upper-layer trajectory controller and a parameter of the lower-layer roll controller; the ESO-ADRC-MPC layered anti-disturbance controller is designed in a layered manner according to a heading and roll, a target roll angle is used as an intermediate quantity, trajectory tracking and self-balancing are simultaneously realized, and the challenge of under-actuation in a low-speed working condition can be effectively coped with.