• Title/Summary/Keyword: Hamilton-Jacobi-Bellman equation

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Variable Structure Control with Optimized Sliding Surface for Spacecraft Slewing Maneuver

  • Cho, Sang-Bum;Moon, Gwan-Young;Kim, You-Dan
    • International Journal of Aeronautical and Space Sciences
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    • v.7 no.1
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    • pp.65-72
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    • 2006
  • A variable structure controller with an optimized sliding surface is proposed for slew maneuver of a rigid spacecraft. Rodrigues parameters are chosen to represent the spacecraft attitude. The quadratic type of performance index is used to design the sling surface. For optimization of the sliding surface, a Hamilton- Jacobi-Bellman equation is formulated and it is solved through the numerical algorithm using Galerkin approximation. The solution denotes a nonlinear sliding surface, on which the trajectory of the system satisfies the optimality condition approximately. Simulation result demonstrates that the proposed controller is effectively applied to the slew maneuver of a rigid spacecraft.

ROBUST OPTIMAL PROPORTIONAL REINSURANCE AND INVESTMENT STRATEGY FOR AN INSURER WITH ORNSTEIN-UHLENBECK PROCESS

  • Ma, Jianjing;Wang, Guojing;Xing, Yongsheng
    • Bulletin of the Korean Mathematical Society
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    • v.56 no.6
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    • pp.1467-1483
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    • 2019
  • This paper analyzes a robust optimal reinsurance and investment strategy for an Ambiguity-Averse Insurer (AAI), who worries about model misspecification and insists on seeking robust optimal strategies. The AAI's surplus process is assumed to follow a jump-diffusion model, and he is allowed to purchase proportional reinsurance or acquire new business, meanwhile invest his surplus in a risk-free asset and a risky-asset, whose price is described by an Ornstein-Uhlenbeck process. Under the criterion for maximizing the expected exponential utility of terminal wealth, robust optimal strategy and value function are derived by applying the stochastic dynamic programming approach. Serval numerical examples are given to illustrate the impact of model parameters on the robust optimal strategies and the loss utility function from ignoring the model uncertainty.

Policy Iteration Algorithm Based Fault Tolerant Tracking Control: An Implementation on Reconfigurable Manipulators

  • Li, Yuanchun;Xia, Hongbing;Zhao, Bo
    • Journal of Electrical Engineering and Technology
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    • v.13 no.4
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    • pp.1740-1751
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    • 2018
  • This paper proposes a novel fault tolerant tracking control (FTTC) scheme for a class of nonlinear systems with actuator failures based on the policy iteration (PI) algorithm and the adaptive fault observer. The estimated actuator failure from an adaptive fault observer is utilized to construct an improved performance index function that reflects the failure, regulation and control simultaneously. With the help of the proper performance index function, the FTTC problem can be transformed into an optimal control problem. The fault tolerant tracking controller is composed of the desired controller and the approximated optimal feedback one. The desired controller is developed to maintain the desired tracking performance at the steady-state, and the approximated optimal feedback controller is designed to stabilize the tracking error dynamics in an optimal manner. By establishing a critic neural network, the PI algorithm is utilized to solve the Hamilton-Jacobi-Bellman equation, and then the approximated optimal feedback controller can be derived. Based on Lyapunov technique, the uniform ultimate boundedness of the closed-loop system is proven. The proposed FTTC scheme is applied to reconfigurable manipulators with two degree of freedoms in order to test the effectiveness via numerical simulation.