Abstract
A new algorithm was developed for the initial parameters optimization of guided projectiles with multiple constraints. Due to the relationship between the analytic guidance logic and state variables of guided projectiles, the Radau pseudospectral method was used to discretize the differential equations including control variables and state variables with multiple constraints into series algebraic equations that were expressed only by state variables. The initial parameter optimization problem was transformed to a nonlinear programming problem, and the sequential quadratic programming algorithm was used to obtain the optimal combinations of initial height and range to target for the final velocity of guided projectiles maximum with constraints. Comparing with the appropriate initial conditions solved by Monte Carlo method and the flight characteristics solved by integrating the original differential equations in the optimal initial parameters computed by the new algorithm, the feasibility of new algorithm was validated.
Highlights
A New Method for Initial Parameters Optimization of Guided ProjectilesA new algorithm was developed for the initial parameters optimization of guided projectiles with multiple constraints
The initial parameter optimization problem of guided projectiles with multiple constraints is considered
Several studies are conducted for developing the guidance logic with multiple constraints [1, 2] and searching the launch acceptable region (LAR) of a guided bomb, while the initial conditions are known [3, 4]
Summary
A new algorithm was developed for the initial parameters optimization of guided projectiles with multiple constraints. Due to the relationship between the analytic guidance logic and state variables of guided projectiles, the Radau pseudospectral method was used to discretize the differential equations including control variables and state variables with multiple constraints into series algebraic equations that were expressed only by state variables. The initial parameter optimization problem was transformed to a nonlinear programming problem, and the sequential quadratic programming algorithm was used to obtain the optimal combinations of initial height and range to target for the final velocity of guided projectiles maximum with constraints. Comparing with the appropriate initial conditions solved by Monte Carlo method and the flight characteristics solved by integrating the original differential equations in the optimal initial parameters computed by the new algorithm, the feasibility of new algorithm was validated
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