Nonlinear Model Predictive Control of a Human-sized Quadrotor

Zanelli, Andrea; Horn, Greg; Frison, Gianluca; Diehl, Moritz

doi:10.23919/ecc.2018.8550530

Cited by 37 publications

(31 citation statements)

References 11 publications

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“…This ultimately allows the QP to find the active set in less iterations, resulting in no violations on the shooting points at bigger block sizes whilst performing slightly better because of the relaxation of the intermediate constraints. 3. Although the non-shifted solutions gave presumably "good" results for the Hildreth's case, they present significant cost suboptimalities.…”

Section: Performance and Recursive Feasibility Comparisonmentioning

confidence: 95%

“…One of the main challenges is that the required optimisation represents a significant computational burden, which has limited its application to relatively slow systems such as chemical reactors [2]. However, given the improvements in electronics in the last two decades, its application to fast real-time systems is now looking more feasible [3]. A key requirement for the implementation in real-time of NMPC is the use of efficient solutions.…”

Section: Introductionmentioning

confidence: 99%

“…Authors from [16] proposed methods for solving the blocked optimisation using highly parallelizable algorithms, which allow for even faster computation times. However, most works in this area, including [3,[16][17][18] have used blocking for NMPC with no regard to the recursive feasibility problem it presents.…”

Section: Introductionmentioning

confidence: 99%

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Shifting strategy for efficient block‐based non‐linear model predictive control using real‐time iterations

Villarreal

Rossiter

2020

IET Control Theory & Applications

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Nonlinear Model Predictive Control (NMPC) requires the use of efficient solutions and strategies for its implementation in fast/real-time systems. A popular approach for this is the Real Time Iteration (RTI) Scheme which uses a shifting strategy, namely the Initial Value Embedding (IVE), that shifts the solution from one sampling time to the next. However, this strategy together with other efficient strategies such as Move Blocking, present a recursive feasibility problem. This paper proposes a novel modified shifting strategy which preserve both recursive feasibility and stability properties, as well as achieves a significant reduction in the computational burden associated with the optimisation. The proposed approach is validated through a simulation of an inverted pendulum where it clearly outperforms other standard solutions in terms of performance and recursive feasibility properties. Additionally, the approach was tested on two computing platforms: a laptop with an i7 processor and a Beaglebone Blue Linux-based computer for robotic systems, where computational gains compared to existing approaches are shown to be as high as 100 times faster.

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Section: Performance and Recursive Feasibility Comparisonmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

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Shifting strategy for efficient block‐based non‐linear model predictive control using real‐time iterations

Villarreal

Rossiter

2020

IET Control Theory & Applications

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“…As benchmark problems in the numerical simulations, we use three examples with different dimensions and properties, namely, the control of a chain of oscillating masses back to its equilibrium position after an initial perturbation, 38 the attitude control of a quadrotor, 39 and the point-to-point motion of a crane. 40 Table 4 x(t) = Ax(t) + Bu(t) are discretized using matrix exponentials, ie, under piecewise constant controls on intervals of length equal to T s , the discrete system is written as…”

Section: Benchmark Problemsmentioning

confidence: 99%

A dual Newton strategy for tree‐sparse quadratic programs and its implementation in the open‐source software treeQP

Kouzoupis

Klintberg

Frison

et al. 2019

Intl J Robust & Nonlinear

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Summary This paper presents a dual Newton scheme for tree‐sparse quadratic programs as they may arise in the field of stochastic programming. Previous work suggests to introduce auxiliary variables to decompose the tree into scenarios and use Newton's method to solve a dual problem formulation. Following a different approach, we apply the same principle directly on the tree‐sparse problem, avoiding the increase in dimensionality. In combination with a tailored algorithm for the calculation of the step direction, which is typically the most expensive operation per iteration, the proposed algorithm achieves a linear complexity in the number of nodes and supports parallel processing of the tree branches in a stage‐wise fashion. An open‐source implementation of the presented dual Newton strategy is publicly available in treeQP, a toolbox of open‐source solvers for tree‐sparse quadratic programs.

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“…Over the last decade, quad-rotors have become a very popular research topic, given their relatively low-cost, complex nonlinear dynamics and high maneuverability. This has led to all kinds of different applications, such as surveillance, aerial photography, surface mapping, search and rescue, inspection, transport, military and the recently, more popular, FPV racing [1]. Apart from their own inherent complexity, these vehicles are constantly affected by external disturbances, such as wind, as well as changes in the systems' dynamics, which can affect their performance and may require re-tuning to achieve good stability characteristics.…”

Section: Introductionmentioning

confidence: 99%

Laguerre-Based Adaptive MPC for Attitude Stabilization of Quad-Rotor

Villarreal

Rossiter

Shin

2018

2018 UKACC 12th International Conference on Control (CONTROL)

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The application of predictive control methods in real-time to fast systems, such as quad-rotors, remains a challenge for its implementation in low-power embedded systems. This paper presents the application of an Adaptive Laguerre-based Model Predictive Controller (MPC) to the Attitude Stabilization of a Quadrotor. The formulation uses an Online System Identification algorithm based on Recursive Least Squares (RLS) with forgetting factor for parameter estimation, and a Laguerrebased Model Predictive Controller for achieving real-time calculation/update of the control law. The developed control system was experimentally tested in a real quad-rotor, and the results demonstrate its real-time applicability in a low-power embedded platform.

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Nonlinear Model Predictive Control of a Human-sized Quadrotor

Cited by 37 publications

References 11 publications

Shifting strategy for efficient block‐based non‐linear model predictive control using real‐time iterations

Shifting strategy for efficient block‐based non‐linear model predictive control using real‐time iterations

A dual Newton strategy for tree‐sparse quadratic programs and its implementation in the open‐source software treeQP

Laguerre-Based Adaptive MPC for Attitude Stabilization of Quad-Rotor

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