4results about How to "Improve trajectory tracking accuracy" patented technology

The application discloses a kind of based on improved model predictive control unmanned ship trajectory tracking control method and device.The method includes, H-PINN method is introduced into unmanned ship hydrodynamics model, obtains the simplified hydrodynamics model of unmanned ship;Based on the prediction model of the trajectory tracking of unmanned ship obtained in simplified hydrodynamics model, the expected trajectory and control quantity of model predictive control MPC are designed using differential flatness theory, and stability analysis is designed according to Lyapunov function.The method improves model predictive control using differential flatness theory, and Lyapunov function optimization analysis is combined, improves trajectory tracking precision, reduces the change amplitude of control quantity, so that the speed change in navigation process is more smooth.

This invention belongs to the technical field of robotic arm motion planning and discloses a robotic arm motion planning method and system based on an error-driven adaptive gradient model. The method includes: S1 establishing the joint velocity at two adjacent moments with respect to the adaptive coefficient λ based on a Lyapunov function. n The gradient relationship is obtained; S2. The joint velocity at time n+1 is calculated using the gradient relationship, and the error between the calculated joint velocity at time n+1 and the adaptive coefficient is updated using the central finite difference method; S3. n = n+1; return to step S2 until the joint velocities at all times are obtained; S4. The joint position is calculated using the relationship between the joint velocity and position; the velocity of the end effector is calculated using the robotic arm motion planning model and the joint velocities at each time, thereby realizing the motion planning of the robotic arm. This invention solves the problem of low computational efficiency in robotic arm motion planning.

This invention discloses a model prediction trajectory tracking control method for a multi-joint robotic arm based on Q-learning, belonging to the field of robotic arm control technology. The method includes the following steps: S1, linearizing the nonlinear dynamic model of the multi-joint robotic arm to construct a discrete-time state-space model; S2, using the cost function of the linear MPC as an approximator for the action value function in a reinforcement learning framework; S3, introducing an adaptive weighted perturbation exploration strategy based on state error to replace traditional random exploration, generating control actions that satisfy the joint position and torque constraints of the robotic arm; S4, under the constraint of system stability, using the discrete model from S1 as the dynamic basis and the cost function from S2 as the basis for evaluating the value of candidate actions, combined with the candidate action set generated by the adaptive weighted perturbation exploration strategy in S3, adjusting the parameters of the MPC based on the Q-learning algorithm. This invention improves the trajectory tracking performance of multi-joint robotic arms under model uncertainty conditions.

The application discloses a high-precision PID trajectory tracking control method for a space manipulator, and relates to the technical field of spacecraft control. The method first establishes a dynamic model of the rotating motion of the manipulator containing system uncertainty; a nonlinear disturbance observer is constructed to estimate the unmodeled dynamics and external disturbances of the system in real time; a PID compound controller is designed in combination with the uncertainty estimation value; a PID parameter optimization problem is established with the minimum trajectory tracking error as a target and the joint angle, angular velocity and control torque as physical constraints; the physical constraints are converted into finite-dimensional constraints by using a constraint transcription method, and the gradient of the objective function and the constraints with respect to the PID parameters is calculated, and the optimal PID parameters are solved by an iterative optimization algorithm. The application realizes high-precision trajectory tracking of the free-flying space manipulator by using the compound control architecture and parameter optimization, effectively suppresses system uncertainty, and ensures strict satisfaction of multiple physical constraints, and has good engineering generality.