Nonlinear model predictive control strategy for low thrust spacecraft missions

Starek, Joseph A.; Kolmanovsky, Ilya

doi:10.1002/oca.2049

Cited by 29 publications

(19 citation statements)

References 20 publications

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“…Accordingly, employ a 1‐norm cost function on inputs to reflect the direct correlation between impulsive accelerations and fuel consumption. Moreover, a variable prediction horizon (VH) helps facilitate finite time manoeuvre completion . VH‐LTV‐MPC imposes a particularly high computational burden, because the prediction model must be updated at each time step, and the VH optimisation is not convex.…”

Section: Background and Design Motivationsmentioning

confidence: 99%

Field programmable gate array based predictive control system for spacecraft rendezvous in elliptical orbits

Hartley

Maciejowski

2014

Optim Control Appl Methods

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A field programmable gate array (FPGA) based model predictive controller for two phases of spacecraft rendezvous is presented. Linear time-varying prediction models are used to accommodate elliptical orbits, and a variable prediction horizon is used to facilitate finite time completion of the longer range manoeuvres, whilst a fixed and receding prediction horizon is used for fine-grained tracking at close range. The resulting constrained optimisation problems are solved using a primal-dual interior point algorithm. The majority of the computational demand is in solving a system of simultaneous linear equations at each iteration of this algorithm. To accelerate these operations, a custom circuit is implemented, using a combination of Mathworks HDL Coder and Xilinx System Generator for DSP, and used as a peripheral to a MicroBlaze softcore processor on the FPGA, on which the remainder of the system is implemented. Certain logic that can be hard-coded for fixed sized problems is implemented to be configurable online, in order to accommodate the varying problem sizes associated with the variable prediction horizon. The system is demonstrated in closed-loop by linking the FPGA with a simulation of the spacecraft dynamics running in Simulink on a PC, using Ethernet. Timing comparisons indicate that the custom implementation is substantially faster than pure embedded software-based interior point methods running on the same MicroBlaze and could be competitive with a pure custom hardware implementation.During the impulsive phase, the control objective is to guide the chaser towards the vicinity of the target via a sequence of predetermined 'holding points' at which it must remain pending clearance to continue (Figure 1(b)). Such trajectories are often informally described as hopping, because in the ideal case (without any parametric or additive uncertainties), they comprise impulsive inputs at the start and finish separated by a long period of free drift. In the present scenario, the holding Recently, interest has arisen in using FPGAs to exploit opportunities for parallelism in the numerical algorithms used to implement MPC, with a variety of approaches proposed. A hybrid softwarehardware design is advocated by [32][33][34]. The first uses a primal barrier method, and the custom accelerator is used to calculate the gradient vector and Hessian matrix of the augmented cost function at each iteration, whilst the latter two use an active set method, with a custom circuit expediting At a high level, the custom PCORE is split into two major parts. The first component performs steps 6-8 and 10 of the Algorithm in Figure 2(a), building the linear system, whilst the second more complex component performs step 9.

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Section: Background and Design Motivationsmentioning

confidence: 99%

Field programmable gate array based predictive control system for spacecraft rendezvous in elliptical orbits

Hartley

Maciejowski

2014

Optim Control Appl Methods

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“…Weiss while optimizing a user defined cost function based on a predictive model for the system dynamics. The ability to explicitly handle multivariable systems, constraints, and performance objectives has rendered MPC very attractive in various fields such as automotive, factory automation, and spacecraft control [3], [4], where it has been proposed for orbital rendezvous [5]- [7], attitude control [8], formation flight [9], and interplanetary transfer [10]. Even though MPC requires higher computational load than conventional closedloop controllers (e.g., PID), linear-quadratic MPC results in quadratic programs that can be solved quickly and efficiently in resource constrained hardware by compact and easyto-verify algorithms, see, e.g., [11] and references therein.…”

Section: Introductionmentioning

confidence: 99%

Opportunities and potential of model predictive control for low-thrust spacecraft station-keeping and momentum-management

Weiss

Cairano

2015

2015 European Control Conference (ECC)

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While electric propulsion generates fuel-efficient thrust for spacecraft control, it can only produce low levels of thrust, necessitating continuous actuation to impart an equivalent impulse to that of chemical thrusters. Thus, many of the standard open-loop propulsion scheduling techniques, developed for impulsive thrust, do not transfer to low-thrust architectures. Continuous actuation, together with tighter anticipated requirements for spacecraft station keeping, e.g., in geostationary Earth orbit (GEO), provides great opportunity for the application of feedback control. We demonstrate that model predictive control (MPC) can provide significant advantages as a control strategy for station keeping of low-thrust spacecraft, provided that its features, such as the capability to enforce output constraints, and the use of a prediction model for the plant and disturbances, are fully exploited. We develop a basic MPC design for station keeping in GEO, and compare its performance with an advanced MPC design that includes output constraints and disturbance prediction. We show that the basic MPC achieves precise regulation, albeit with unsustainable fuel consumption, whereas the advanced MPC satisfies the target mission requirements with fuel consumption in line with that of carefully designed open-loop strategies.

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“…The minimum-time MPC approach has been used in Starek and Kolmanovsky (2012), Petersen et al (2013) for low thrust orbital maneuvering and for hypersonic glider guidance, respectively. In these applications, minimumtime MPC has been exploited to improve robustness to unmeasured disturbances and uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Parametric Integrated Perturbation Analysis - Sequential Quadratic Programming Approach for Minimum-time Model Predictive Control

Park

Kolmanovsky

Sun

2014

IFAC Proceedings Volumes

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Nonlinear model predictive control strategy for low thrust spacecraft missions

Cited by 29 publications

References 20 publications

Field programmable gate array based predictive control system for spacecraft rendezvous in elliptical orbits

Field programmable gate array based predictive control system for spacecraft rendezvous in elliptical orbits

Opportunities and potential of model predictive control for low-thrust spacecraft station-keeping and momentum-management

Parametric Integrated Perturbation Analysis - Sequential Quadratic Programming Approach for Minimum-time Model Predictive Control

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