The invention discloses a design method for a variable parameter neural
solver for
motion planning of a redundancy mechanical arm. The method comprises the following steps that the solved task is converted into a
performance index and a constraint condition of the redundancy mechanical arm; the
performance index and the constraint condition is converted into a time-varying quadratic
programming standard form of a to-be-solved
system; according to a lagrangian
multiplier method, the optimal value in the time-varying quadratic
programming standard form is optimized; optimized information is converted into a
standard time-varying matrix equation form; a
deviation function is designed according to the
standard time-varying matrix equation form; according to the
deviation function and a power
type variable parameter
recursion neural dynamics method, the variable parameter neural
solver used for the
motion planning of the redundancy mechanical arm on a real number field is designed; and a network state solution obtained through the variable parameter neural
solver is the optimal solution for the
motion planning of the redundancy mechanical arm
system. The method has the advantages of being high in calculation speed, high in precision, fast in convergence, high in instantaneity, and good in robustness.