126 research outputs found

    Predictive Control with Parameter Adaptation to Achieve α-Protection in the RECONFIGURE Benchmark in the Presence of Icing

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    Undetected ice accretions on aerodynamic surfaces can deeply change the dynamic behaviour of aircraft, leading to poor performance of the automatic control systems. This is characterised by oscillatory behaviour, and overshoot of setpoints and ight envelope protection values. To mitigate this undesirable behaviour, this paper applies predictive control in combination with online estimation of the first and second order partial derivatives of the lift and pitching moment coeffcients with respect to the angle of attack using an Extended Kalman Filter, to achieve a constrained indirect adaptive ight control law. The design is evaluated on the RECONFIGURE benchmark, which is a nonlinear, high fidelity, industrially validated simulator of a large Airbus aircraft. In icing scenarios at high incidence, the resulting trajectories are shown to be better damped and more compliant with constraints when compared to a predictive control law employing only linear disturbance estimation.This is the final version of the article. It was first available from Elsevier via http://dx.doi.org/10.1016/j.ifacol.2015.11.27

    Predictive control for spacecraft rendezvous in an elliptical orbit using an FPGA

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    A field programmable gate array (FPGA)-based predictive controller for a spacecraft rendezvous man{\oe}uvre is presented. A linear time varying prediction model is used to accommodate elliptical orbits, and a variable prediction horizon is used to facilitate finite time completion of man{\oe}uvres. The resulting constrained optimisation problems are solved using a primal dual interior point algorithm. The majority of the computational demand is in solving a set of linear equations at each iteration of this algorithm. To accelerate this operation, 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 soft core processor. The system is demonstrated in closed loop by linking the FPGA with a simulation of the plant dynamics running in Simulink on a PC, using Ethernet.This work was supported by the Engineering and Physical Sciences Research Council (Grant EP/G030308/1) as well as industrial support from Xilinx, Mathworks and the European Space Agency.European Control Conference 2013 (ECC13), July 17-19, Zurich, Switzerlan

    Graphical FPGA design for a predictive controller with application to spacecraft rendezvous

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    A reconfigurable field-programmable gate array (FPGA)-based predictive controller based on Nesterov’s fast gradient method is designed using Simulink and converted to VHDL using Mathworks’ HDL Coder. The implementation is verified by application to a spacecraft rendezvous and capture scenario, with communication between the FPGA and a simulation of the relative dynamics occuring over Ethernet. For a problem with 120 decision variables and 240 constraints, computation times of 0.95 ms are achieved with a clock rate of 50 MHz, corresponding to a speed up of more than 2000 over running the algorithm directly on a MicroBlaze microprocessor implemented on the same FPGA.This work was supported by the Engineering and Physical Sciences Research Council (Grant EP/G030308/1) as well as industrial support from Xilinx, Mathworks and the European Space Agency.52nd IEEE Conference on Decision and Control, December 10-13, 2013, Palazzo dei Congressi, Florence, Italy

    Predictive control using an FPGA with application to aircraft control

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    Alternative and more efficient computational methods can extend the applicability of MPC to systems with tight real-time requirements. This paper presents a “system-on-a-chip” MPC system, implemented on a field programmable gate array (FPGA), consisting of a sparse structure-exploiting primal dual interior point (PDIP) QP solver for MPC reference tracking and a fast gradient QP solver for steady-state target calculation. A parallel reduced precision iterative solver is used to accelerate the solution of the set of linear equations forming the computational bottleneck of the PDIP algorithm. A numerical study of the effect of reducing the number of iterations highlights the effectiveness of the approach. The system is demonstrated with an FPGA-inthe-loop testbench controlling a nonlinear simulation of a large airliner. This study considers many more manipulated inputs than any previous FPGA-based MPC implementation to date, yet the implementation comfortably fits into a mid-range FPGA, and the controller compares well in terms of solution quality and latency to state-of-the-art QP solvers running on a standard PC
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