Multiconstraint adaptive three-dimensional guidance law using convex optimization

Abstract

The traditional guidance law only guarantees the accuracy of attacking a target. However, the look angle and acceleration constraints are indispensable in applications. A new adaptive three-dimensional proportional navigation (PN) guidance law is proposed based on convex optimization. Decomposition of the three-dimensional space is carried out to establish threedimensional kinematic engagements. The constraints and the performance index are disposed by using the convex optimization method. PN guidance gains can be obtained by solving the optimization problem. This solution is more rapid and programmatic than the traditional method and provides a foundation for future online guidance methods, which is of great value for engineering applications.

Optimization of the PNG Law for a Dual-Spin Mortar with Fixed Canards

“…For a fin-stabilized projectile with a low spin rate, the mutual coupling effects between the pitching and yawing motions are relatively weak and can be ignored [2,13,16]. Accordingly, the three-dimensional PNG problem can be decoupled into two two-dimensional problems in the vertical and horizontal planes of the velocity vector without loss of convergence [2,6,[17][18][19][20].…”

Multivariable Adaptive Super-Twisting Guidance Law Based on Barrier Function

“…On the basis of H-infinite theory, reference [7,8] proposed robust guidance laws by regarding unpredictable target maneuvers as bounded unknowns. Reference [9] disposed of the constraints and the performance index by using the convex optimization method to obtain guidance gains. Utilizing model predictive control, reference [10] designed a suboptimal terminal angle constrained guidance law.…”