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In this paper, a novel scheme of command to line-of-sight guidance law regarding the outstanding practical limitations is proposed. With the aid of formulating problem in pursuer's line of sight frame, the exact feed-forward acceleration commands are derived for a general target motion in three-dimensional engagement geometry. Then, a nonlinear control scheme constructed from feed-forward terms along with a nested saturated feedback strategy is suggested. Two momentous practical limitations are considered. The first is related to existence of pursuer's acceleration saturation which is ignored in all existing solutions. The required conditions to insure the global stability are derived... 

In this paper, a novel scheme of command to line-of-sight guidance law regarding the outstanding practical limitations is proposed. With the aid of formulating problem in pursuer's line of sight frame, the exact feed-forward acceleration commands are derived for a general target motion in three-dimensional engagement geometry. Then, a nonlinear control scheme constructed from feed-forward terms along with a nested saturated feedback strategy is suggested. Two momentous practical limitations are considered. The first is related to existence of pursuer's acceleration saturation which is ignored in all existing solutions. The required conditions to insure the global stability are derived... 

In this paper, a novel scheme of command to line-of-sight guidance law regarding the outstanding practical limitations is proposed. With the aid of formulating problem in pursuer's line of sight frame, the exact feed-forward acceleration commands are derived for a general target motion in three-dimensional engagement geometry. Then, a nonlinear control scheme constructed from feed-forward terms along with a nested saturated feedback strategy is suggested. Two momentous practical limitations are considered. The first is related to existence of pursuer's acceleration saturation which is ignored in all existing solutions. The required conditions to insure the global stability are derived... 

To achieve an exact three-dimensional command to line of sight (CLOS) guidance law, a novel control scheme comprising feed-forward terms (to exactly compensate known kinematics) accompanied by an adaptive nested saturated feedback strategy is presented. A square-root cubature Kalman filter is designed as the CLOS non-linear guidance filter. Performance of the proposed guidance law is compared with the augmented proportional navigation (APN), at the absence and presence of target maneuvers, autopilot dynamics and non-ideal tracking filter. Simulation results demonstrate the satisfactory performance of proposed strategy. © 2018 Concern CSRI Elektropribor, JSC  

In this paper, terminal engagement of a maneuvering target and a pursuer is investigated. A heuristic nonlinear model predictive guidance algorithm is presented. Nonlinear kinematics of the pursuer and the target is utilized to formulate the guidance problem. Also, the target maneuver is assumed to be unknown. The proposed heuristic guidance algorithm uses an ant-based optimization algorithm to estimate simultaneously the states of the pursuer, the maneuver of the target, and the optimal guidance commands. Performance of the new guidance algorithm against maneuvering and non-maneuvering targets is evaluated using numerical simulations. Also, the results of the guidance algorithm are compared... 

Two-dimensional engagement of a pursuer and a maneuvering target, affected by matched uncertainties, is formulated as a nonlinear differential game. The uncertain guidance problem is converted into a nonlinear model predictive control problem by introducing an appropriate cost function. The objective is to calculate the best guidance commands of the pursuer and the worst possible target maneuvers simultaneously, over a receding horizon. The proposed cost function penalizes the line-of-sight rate, the pursuer acceleration, and the uncertainties. It also rewards the target maneuver. A particle swarm-based dynamic optimization algorithm is developed to solve the nonlinear model predictive...