Integrated Game Based Guidance with Nonlinear Autopilot Design for Maneuvering Target Interception

Hsueh, Ming-Hsiung; Wang, Ting-Kuo; Fu, Li‐Chen

doi:10.1002/asjc.685

Cited by 4 publications

(6 citation statements)

References 25 publications

(24 reference statements)

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“…. The implementation of three‐dimensional PN and nonlinear autopilot have been examined in and , respectively.…”

Section: ‐D Interceptor‐ Target Engagementmentioning

confidence: 99%

“…It is shown that APN is a simplified version [8] under some specific engagements conditions. The integrated game theory based guidance law with nonlinear autopilot system has been worked out in [14]. Nonlinear H ∞ guidance law is the subject of research in [11].…”

Section: Introductionmentioning

confidence: 99%

“…An adaptive integrated guidance and control scheme using back‐stepping is addressed in . The integrated game theory based guidance law with nonlinear autopilot system has been worked out in . Other techniques investigated are differential game, Lyapunov‐based and L 2 gain guidance laws .…”

Section: Introductionmentioning

confidence: 99%

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On an Optimized Fuzzy Supervized Multiphase Guidance Law

Rezaee

Seyedtabaii

2016

Asian Journal of Control

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Proportional navigation (PN) is an effective guidance law in chasing a constant speed target. However, intercepting a maneuvering target requires extra provisions to contain target acceleration. This is observed in the next generation of guidance laws, namely augmented proportional navigation (APN) and the optimal guidance law (OGL). The other advanced guidance method is integral sliding mode (ISM), which exhibits superb low miss distance (MD), but unfortunately at the cost of disappointing effective lateral acceleration (C eff ), higher than the modest level that APN and OGL demand. Reducing both MD and C eff can be achieved using a multiphase algorithm. A setup of APN, OGL and ISM is proposed to integrate the strength of each and overcome their weaknesses. Hybrid algorithm smooth management is conducted by an optimally tuned fuzzy supervisory controller. The results indicate that in facing a constant acceleration target, an APN-ISM twin yields the best results, while in case of a constant jerk target an APN-OGL-ISM triplet renders excellent interception. Miss distance as low as 0.012m can be achieved with significantly lower control effort than required by ISM alone. The simulations results confirm the conclusions and illustrate the capacity of the algorithm in combating maneuvering targets.

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“…. The implementation of three‐dimensional PN and nonlinear autopilot have been examined in and , respectively.…”

Section: ‐D Interceptor‐ Target Engagementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

On an Optimized Fuzzy Supervized Multiphase Guidance Law

Rezaee

Seyedtabaii

2016

Asian Journal of Control

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“…After the interaction phase, agents can update their strategies by comparing their own payoffs with that of the chosen neighbors . When interactions take place on a network, cooperation can get established, but this strongly depends on the network structure .…”

Section: Introductionmentioning

confidence: 99%

Evolutionary Dynamics of Strategies without Complete Information on Complex Networks

Zhang

2018

Asian Journal of Control

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As for the behaviors of multi-agent system, recent years have witnessed the growing interest in the study of cooperative behaviors by the aid of evolutionary game dynamics on complex networks. Thereinto, the updating rules deciding the evolution of strategies will significantly influence the steady state distribution of the system. The strategy updating rooted in the pursuit of larger benefits, will drive the system to evolve into the coexistence of different states or the domination by some strategies. To relax the often-used rules required explicit knowledge of the exact payoffs, this paper describes a new approach of updating strategy based on switching probabilities, which is independent on players' payoffs and degrees. And then the equilibrium state of the strategy evolution in the networks is studied. Our work here provides a computationally feasible way of estimating the steady characteristics of the strategy adoption of agents situating on complex networks. The stability analysis elucidates two important features: (i) the takeover of cooperation can be enhanced by the appropriate settings of the switching probabilities between strategies and (ii) larger average degree and power exponent in the employed scale-free network can make it easier for the coexistence of strategies. The results can help the design of initial strategy distribution of agents located on social networks to promote cooperation. Fig. 3. The steady states of the gaming system in the adopted BA scale-free network (the power-law exponent of scale-free network is 3), with the variation of the average degree n of the network. Here, n = 4, n = 6, n = 8, n = 10 are adopted for a comparison. is the probability of randomly connecting to D-players. Blue area: D strategy dominates the whole network.Red area: C strategy dominates the system. Other colors: The coexistence of the two strategies. Solid line: boundary lines of coexistence regions. [Color figure can be viewed at wileyonlinelibrary.com]

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“…Adopting a backstepping scheme, Yan et al [25] developed an adaptive nonlinear integrated guidance and control approach for interception of maneuvering targets (evaders). In addition, Hsueh et al [26] combined the linear differential game theory with SMC method to design integrated guidance for a nonlinear autopilot system. Compared with OP and biased PNG guidance laws, SMC guidance laws have superior performances in the control of time-varying uncertain systems.…”

Section: Introductionmentioning

confidence: 99%

Finite time convergent wavelet neural network sliding mode control guidance law with impact angle constraint

Zhang

Han

et al. 2015

Int. J. Autom. Comput.

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This paper presents a novel guidance law to intercept non-maneuvering targets with impact angle and lateral acceleration command constraints. Firstly, we formulate the impact angle control to track the desired line-of-sight (LOS) angle, which is achieved by selecting the missile s lateral acceleration to enforce the sliding mode on a sliding surface at impact time. Secondly, we use the Lyapunov stability theory to prove the stability and finite time convergence of the proposed nonlinear sliding surface. Thirdly, we introduce the wavelet neural network (WNN) to adaptively update the additional control command and reduce the high-frequency chattering of sliding mode control (SMC). The proposed guidance law, denoted WNNSMC guidance law with impact angle constraint, combines the SMC methodology with WNN to improve the robustness and reduce the chattering of the system. Finally, numerical simulations are performed to demonstrate the validity and effectiveness of the WNNSMC guidance law.

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Integrated Game Based Guidance with Nonlinear Autopilot Design for Maneuvering Target Interception

Cited by 4 publications

References 25 publications

On an Optimized Fuzzy Supervized Multiphase Guidance Law

On an Optimized Fuzzy Supervized Multiphase Guidance Law

Evolutionary Dynamics of Strategies without Complete Information on Complex Networks

Finite time convergent wavelet neural network sliding mode control guidance law with impact angle constraint

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