CALCULATION OF SUBOPTIMAL HIGH-ELLIPTICAL ORBIT TO GEOSTATIONARY ORBIT TRAMSFERS FOR SPACECRAFT WITH LOW THRUSTERS

Author(s):  
V.V. Salmin ◽  
K.V. Petrukhina ◽  
A.A. Kvetkin

At present the geostationary orbit is where communication satellites are preferably placed. Conventional orbital insertion profiles using chemical propulsion are insufficiently effective and require the use of heavy launch vehicles. Combining electric thrusters with chemical propulsion increases the mass of payload. On the other hand, orbital injection of a spacecraft using electrical propulsion brings up the problem of looking for an optimal control law. The paper discusses the transfer of a spacecraft with low-thrust electrical thruster from a high elliptical orbit to geostationary orbit. It proposes a suboptimal control law for the thrust vector. It provides examples of simulations of the transfer using the control law for various initial conditions. Parameters of intermediate high-elliptical orbits were selected to minimize the time of transfer to the final orbit, and estimates were made of the effects of the residual atmospheric drag during flight in the vicinity of the perigee of the orbit. Considering the low level of error, simplicity and high computational speed the proposed method can be used for trajectory design calculations. Key words: Suboptimal control law, local optimization theory, electric thruster, high-elliptical orbit, geostationary orbit, math model of controlled motion, Pontryagin's maximum principle.

2010 ◽  
Vol 439-440 ◽  
pp. 805-810 ◽  
Author(s):  
Peng Liu

In this paper, a new congestion controller is developed to obtain a feedforward and feedback optimal control for networked control systems (NCS) with persistent disturbances. The disturbances have known dynamic characteristics but unknown initial conditions. The disturbance observer is proposed to make the feedforward control law realizable physically. In the approach only the non-linear compensating term, solution of a sequence of adjoint vector differential equations, is required iteration. By taking the finite iteration of non-linear compensating term of optimal solution sequence, a suboptimal control law for NCS with time delay can be obtained.


PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0257958
Author(s):  
Miguel Navascués ◽  
Costantino Budroni ◽  
Yelena Guryanova

In the context of epidemiology, policies for disease control are often devised through a mixture of intuition and brute-force, whereby the set of logically conceivable policies is narrowed down to a small family described by a few parameters, following which linearization or grid search is used to identify the optimal policy within the set. This scheme runs the risk of leaving out more complex (and perhaps counter-intuitive) policies for disease control that could tackle the disease more efficiently. In this article, we use techniques from convex optimization theory and machine learning to conduct optimizations over disease policies described by hundreds of parameters. In contrast to past approaches for policy optimization based on control theory, our framework can deal with arbitrary uncertainties on the initial conditions and model parameters controlling the spread of the disease, and stochastic models. In addition, our methods allow for optimization over policies which remain constant over weekly periods, specified by either continuous or discrete (e.g.: lockdown on/off) government measures. We illustrate our approach by minimizing the total time required to eradicate COVID-19 within the Susceptible-Exposed-Infected-Recovered (SEIR) model proposed by Kissler et al. (March, 2020).


Author(s):  
Peichao Mi ◽  
Qingxian Wu ◽  
Yuhui Wang

This paper presents a novel suboptimal attitude tracking controller based on the algebraic Riccati equation for a near-space hypersonic vehicle (NSHV). Since the NSHV’s attitude dynamics is complexly nonlinear, it is hard to directly construct an appropriate algebraic Riccati equation. We design the construction based on the Chebyshev series and the Koopman operator theory, which includes three steps. First, the Chebyshev series are considered to transform the error dynamics of the NSHV’s attitude into a polynomial system. Second, the Koopman operator is used to obtain a series of high-dimensional linear dynamics to approximate each of the polynomial system’s vector fields. In this step, our contribution is to determine a well-posed linear dynamics with the minimal dimension to approximate the original nonlinear vector field, which helps to design the control law and analyze the control performance. Third, based on the high-dimensional dynamics, the NSHV’s attitude error dynamics is separated into the linear part and the nonlinear part, such that the algebraic Riccati equation can be constructed according to the linear part. Then, the suboptimal error feedback control law is derived from the algebraic Riccati equation. The closed-loop control system is proved to be locally exponentially stable. Finally, the numerical simulation demonstrates the effectiveness of the suboptimal control law.


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