Game-Based Safe Aircraft Navigation in the Presence of Energy-Bleeding Coasting Missile

Alkaher, David; Moshaiov, Amiram

doi:10.2514/1.g001676

Cited by 15 publications

(5 citation statements)

References 19 publications

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“…To highlight the applicability of this study to real-life problems, consider the aeronautical MOGs of Alkaher and Moshaiov (2016) and Harel et al (2020). In these MOG studies, which are solved using an analytical approach, the primary objectives involve distances among the considered aeronautical entities.…”

Section: Generalmentioning

confidence: 99%

Solving zero‐sum multi‐objective games with a‐priori secondary criteria

Harel

Eisenstadt-Matalon

Moshaiov

2022

Multi Criteria Decision Anal

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Solving non‐cooperative zero‐sum multi‐objective Games (zsMOGs), under undecided objective preferences results, for each of the players, in a Set of Rationalizable Strategies (SRS) to choose from. First, this paper deals with finding for each of the players a preferred subset of such rationalizable strategies based on a‐priori incorporation of partial preferences of the decision‐makers using secondary criteria. The obtained subset is termed the Set of Preferred Strategies (SPS). Here, a novel archive‐based co‐evolutionary algorithm is suggested to search for the SPS for each of the players. An academic example is suggested to demonstrate and validate the algorithm. It concerns a zsMOG that involves two adversarial planar manipulators. Based on a theorem that is proven here, a theoretic reference SRS is found for each of the players. This reference SRS is applied to find a reference SPS, which is used for validating the algorithm. Next, a comparison study is performed between the proposed archive‐based co‐evolutionary algorithm and an elite‐based version of this algorithm. The results clearly show that the archive‐based algorithm is superior to the elite‐based version, yielding results that correspond well to the theoretic sets.

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Section: Generalmentioning

confidence: 99%

Solving zero‐sum multi‐objective games with a‐priori secondary criteria

Harel

Eisenstadt-Matalon

Moshaiov

2022

Multi Criteria Decision Anal

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“…Imado et al [19] proposed a method to find many solutions of comparable values to the differential game, that is, "a family of local solutions". For the constrained optimization problem of closing the distance to the target, while avoiding the threatening missile, the problem is formulated as a two-team zero-sum differential-game model between the navigator and an adversary coalition of the target and the missile in [20]. Moreover, for optimal evasive maneuvers, the optimal support time of a missile and the dynamic-escapezone of a fighter were solved based on a differential game in [21] and [5], respectively.…”

Section: Introductionmentioning

confidence: 99%

Nondominated Maneuver Strategy Set With Tactical Requirements for a Fighter Against Missiles in a Dogfight

et al. 2020

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Dogfight is often a continuous and multi-round process with missile attacks. If the fighter only considers the security when evading the incoming missile, it will easily lose the superiority in subsequent air combat. Therefore, it is necessary to maintain as much tactical superiority as possible while ensuring a successful evasion. The amalgamative tactical requirements of achieving multiple evasive objectives in a dogfight are taken into account in this paper. A method of generating a nondominated maneuver strategy set for evading missiles with tactical requirements is proposed. The tactical requirements include higher miss distance, less energy consumption, and higher terminal superiority. Then the evasion problem is defined and reformulated into a multi-objective optimization problem, which is solved by a redesigned multiobjective evolutionary algorithm based on decomposition (MOEA/D). Simulations are used to demonstrate the feasibility and effectiveness of the approach. A set of approximate Pareto-optimal solutions satisfying the tactical requirements are obtained. These solutions can not only guide the fighter to avoid being hit but also achieve the goal of relatively reducing energy consumption and improving terminal superiority. INDEX TERMS dogfight, decision-making, evasive maneuvers, multi-objective evolutionary algorithm, tactical requirements.

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“…Many approaches, such as differential games [3]- [6], optimum control [7]- [11], model predictive control [12]- [15], and evolutionary algorithms [16]- [21], have been applied to obtain the optimal or approximate optimal evasive maneuver command for a fighter.…”

Section: Introductionmentioning

confidence: 99%

“…To obtain the analytic solution of optimal maneuver, the problem could be formulated as a two-sided optimization called a zero-sum two-person differential game [3], [6]. It was solved by semidirect collocation with nonlinear programming in [3].…”

Section: Introductionmentioning

confidence: 99%

“…Carr et al [4] obtained an initial guess for the physically unintuitive costates through solving a one-sided optimal control problem. This study was extended in [5] to a family of local solutions, and Alkaher and Moshaiov [6] also solved this game through an optimal controller in a closed-loop form, which resulted in a safe-navigation strategy for the fighter.…”

Section: Introductionmentioning

confidence: 99%

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Evasive Maneuver Strategy for UCAV in Beyond-Visual-Range Air Combat Based on Hierarchical Multi-Objective Evolutionary Algorithm

et al. 2020

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This study deals with the autonomous evasive maneuver strategy of unmanned combat air vehicle (UCAV), which is threatened by a high-performance beyond-visual-range (BVR) air-to-air missile (AAM). Considering tactical demands of achieving self-conflicting evasive objectives in actual air combat, including higher miss distance, less energy consumption and longer guidance support time, the evasive maneuver problem in BVR air combat is defined and reformulated into a multi-objective optimization problem. Effective maneuvers of UCAV used in different evasion phases are modeled in threedimensional space. Then the three-level decision space structure is established according to qualitative evasive tactical planning. A hierarchical multi-objective evolutionary algorithm (HMOEA) is designed to find the approximate Pareto-optimal solutions of the problem. The approach combines qualitative tactical experience and quantitative maneuver decision optimization method effectively. Simulations are used to demonstrate the feasibility and effectiveness of the approach. The results show that the obtained set of decision variables constitutes nondominated solutions, which can meet different evasive tactical requirements of UCAV while ensuring successful evasion.INDEX TERMS BVR air combat, evasive maneuver, hierarchical evolutionary algorithm, multi-objective optimization, UCAV.

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Game-Based Safe Aircraft Navigation in the Presence of Energy-Bleeding Coasting Missile

Cited by 15 publications

References 19 publications

Solving zero‐sum multi‐objective games with a‐priori secondary criteria

Solving zero‐sum multi‐objective games with a‐priori secondary criteria

Nondominated Maneuver Strategy Set With Tactical Requirements for a Fighter Against Missiles in a Dogfight

Evasive Maneuver Strategy for UCAV in Beyond-Visual-Range Air Combat Based on Hierarchical Multi-Objective Evolutionary Algorithm

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