On the solution of the motion control problem as a finite-horizon optimal control problem

2002 ◽  
Author(s):  
J.A. De Abreu-Garcia ◽  
L.A. Cabrera-Arevalo ◽  
J.M. Madaras
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Motion Control ◽  
Finite Horizon

Adaptive periodic event-triggered control for missile-target interception system with finite-horizon convergence

2020 ◽  
Vol 42 (10) ◽  
pp. 1808-1822 ◽  
Author(s):  
Dandan Duan ◽  
Chunsheng Liu ◽  
Jingliang Sun
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Sufficient Conditions ◽  
Finite Horizon ◽  
Adaptive Dynamic Programming ◽  
Critic Neural Network ◽  
Target Interception ◽  
Event Based ◽  
Event Triggered

In this paper, the optimal control problem for finite-time missile-target interception systems is posed in a finite-horizon two-player zero-sum (ZS) differential game framework using a periodic event-triggered (PET) scheme. To solve the optimal control problem, a time-varying Hamilton-Jacobi-Issac (HJI) equation and a time-dependent cost function are constructed to deal with finite-horizon constraints, and an event-based periodic adaptive dynamic programming (ADP) algorithm is employed to find the Nash equilibrium solution for the designed HJI equation. Comparing with the traditional continuous event-triggered (ET) scheme, the proposed PET scheme only verifies the event-triggered conditions at periodic sampling instants, which reduces resource consumption in monitoring and excludes the Zeno behavior. A single critic neural network (CNN) is used to implement the proposed event-based optimal control algorithm, which reduces approximate errors bust also simplifies structures. Further, an additional error term is added in the designed weight updating law to such that the terminal constraint is also minimized over time. By resorting to Lyapunov function approach, some sufficient conditions are derived to achieve the uniformly ultimately bounded (UUB) of the ET closed-loop system and the estimation weight error of CNN. Finally, a missile-target interception system is introduced to illustrate the efficiency of the presented methods.

USING PSEUDOSPECTRAL METHOD TO SEARCH FOR PROPELLANT-OPTIMAL TRAJECTORIES OF THE INTERNATIONAL SPACE STATION ATTITUDE CONTROL MANEUVERS

2019 ◽  
pp. 121-133
Author(s):  
A.A. Prutko ◽  
S.N. Atroshenkov ◽  
A.V. Bogachev ◽  
A.E. Starchenko
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
International Space Station ◽  
Motion Control ◽  
Attitude Control ◽  
Space Station ◽  
Pseudospectral Method ◽  
Optimal Trajectories ◽  
International Space

The paper discusses the problem of searching for propellant-optimal trajectories of the International Space Station attitude control maneuvers involving spatial turns through large angles using attitude control jet thrusters. Development of such algorithms for controlling the ISS angular motion is currently a crucial task for Russian developers of the onboard software. In order to generate the optimal trajectory for the attitude control maneuver, the paper proposes to use the Lobatto pseudospectral method. This method allows stating the optimal control problem as a nonlinear mathematical programming problem which can be solved using the method of sequential quadratic programming. Simulation results demonstrated significant savings of attitude control thrusters propellant and life during station attitude control maneuvers in comparison with the algorithms that are currently used in the motion control system of the ISS Russian Segment. Key words: International Space Station, optimal control problem, angular motion control, pseudospectral method, nonlinear programming

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