Model predictive control application to spacecraft rendezvous in mars sample return scenario

Saponara, M.; Barrena, V.; Bemporad, Alberto; Hartley, Edward N.; Maciejowski, Jan M.; Richards, Arthur; Tramutola, A.; Trodden, Paul

doi:10.1051/eucass/201306137

Cited by 14 publications

(16 citation statements)

References 26 publications

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“…In , an MPC is presented using an approximate discretisation of the continuous linearised parameter‐varying equations of relative motion. The Yamanaka–Ankersen (YA) state transition matrix , which discretises the LTV dynamics more accurately, has been used to form the prediction model for MPC in . Gauss's variational equations, which consider instead the relative position in terms of the differences in Keplerian orbital elements, are also parameterised in terms of the true anomaly of the target and have been used in MPC by .…”

Section: Background and Design Motivationsmentioning

confidence: 99%

“…However, for longer range manoeuvres, minimisation of fuel consumption and completion of the manoeuvre in finite time can be more important than accurate tracking of a reference trajectory. 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 .…”

Section: Background and Design Motivationsmentioning

confidence: 99%

“…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. Nevertheless, a global optimum can be obtained by using mixed‐integer programming or enumeration of a sequence of convex problems . The latter strategy is chosen for the impulsive phase in the present paper.…”

Section: Background and Design Motivationsmentioning

confidence: 99%

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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%

Section: Background and Design Motivationsmentioning

confidence: 99%

Section: Background and Design Motivationsmentioning

confidence: 99%

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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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“…MPC is well suited to aerospace problems mainly because of its ability to explicitly handle constraints and consider the system dynamics, allowing fuel efficient and feasible plans to be determined autonomously and on-line [5][6][7][8][9][10].…”

Section: Model Predictive Controlmentioning

confidence: 99%

Test of attitude control maneuvers with a Satellite Formation Flight testbed

Valmorbida

Mazzucato

Aboudan

et al. 2014

2014 IEEE Metrology for Aerospace (MetroAeroSpace)

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Satellite Formation Flying (SFF) can go beyond mass and volume constraints that today's launchers pose on single satellite missions. However, the high levels of autonomy required by SFF result in stringent requirements on the Guidance Navigation and Control system. These requirements must face up with multitasking problems related to limited on board resources in terms of both computing capacity and control authority.The final aim of the experimental activities presented in this paper is to test optimal control techniques to carry out attitude control maneuvers on the SFF hardware simulator that we are developing at the University of Padova. In particular, we considered both Model Predictive Control (MPC) and quaternion-based Proportional -Integral -Derivative (PID) controllers for two kind of attitude maneuvers: set point reaching maneuvers with a fixed attitude target to be reached, and trajectory tracking maneuvers, where the reference state trajectories are computed using pseudospectral methods.

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“…Special formulations of Model Predictive Control (MPC) have been proposed for line-of-sight rendezvous in [6]- [10]. In [11], assuming a relatively uncluttered spacecraft relative motion environment, the non-convex obstacle avoidance constraint was replaced by a convex, yet time-varying rotating hyperplane constraint.…”

Section: Introductionmentioning

confidence: 99%

Hardware implementation of Model Predictive Control for relative motion maneuvering

Goodyear

Petersen

Pierre

et al. 2015

2015 American Control Conference (ACC)

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In this paper, a Model Predictive Controller (MPC) is experimentally implemented on a robotic test-bed. The test-bed is designed to emulate spacecraft relative motion maneuvers and reflects realistic computational hardware limitations (i.e., limited on-board computational power and memory), which present serious obstacles to implementation of advanced guidance and control algorithms. Both simulation results and experimental results are presented and compared, demonstrating that autonomous constrained maneuvering using MPC is feasible for on-board implementation.

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Model predictive control application to spacecraft rendezvous in mars sample return scenario

Cited by 14 publications

References 26 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

Test of attitude control maneuvers with a Satellite Formation Flight testbed

Hardware implementation of Model Predictive Control for relative motion maneuvering

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