On active set algorithms for solving bound-constrained least squares control allocation problems

Schofield, Brad

doi:10.1109/acc.2008.4586883

Cited by 8 publications

(4 citation statements)

References 8 publications

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“…The customized P-step is as follows: with fixed D, solving X is a constrained least-squares problem [43]. However, existing solvers [12], [44] can only handle box constraints or upper bound quadratic constraints, whereas we want to constrain the solution to an annulus. Hence, we adapted the state-of-the-art constrained least squares solver of Mead and Renaut [12] to our problem.…”

Section: Solving the Constrained Optimizationmentioning

confidence: 99%

Target Netgrams: An Annulus-Constrained Stress Model for Radial Graph Visualization

Xue

Wang

Han

et al. 2023

IEEE Trans. Visual. Comput. Graphics

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We present Target Netgrams as a visualization technique for radial layouts of graphs. Inspired by manually created target sociograms, we propose an annulus-constrained stress model that aims to position nodes onto the annuli between adjacent circles for indicating their radial hierarchy, while maintaining the network structure (clusters and neighborhoods) and improving readability as much as possible. This is achieved by having more space on the annuli than traditional layout techniques. By adapting stress majorization to this model, the layout is computed as a constrained least square optimization problem. Additional constraints (e.g., parent-child preservation, attribute-based clusters and structure-aware radii) are provided for exploring nodes, edges, and levels of interest. We demonstrate the effectiveness of our method through a comprehensive evaluation, a user study, and a case study.

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Section: Solving the Constrained Optimizationmentioning

confidence: 99%

Target Netgrams: An Annulus-Constrained Stress Model for Radial Graph Visualization

Xue

Wang

Han

et al. 2023

IEEE Trans. Visual. Comput. Graphics

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“…Many techniques to solve online the control allocation problem can be found in the literature (see e.g. [25][26][27][28]), the advantages of online approaches are that actuators failures and time varying saturations can be considered. For the sake of simplicity, since control allocation is not the focus of this paper, the optimization problem (12) is solved offline obtaining the look-up tables represented in Fig.…”

Section: Torque Allocatormentioning

confidence: 99%

A Mixed Sideslip Yaw Rate Stability Controller for Over-Actuated Vehicles

Gimondi

Corno

Savaresi

2021

Volume 1: 23rd International Conference on Advanced Vehicle Technologies (AVT)

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Electronic stability control (ESC) has become a fundamental safety feature for passenger cars. Commonly employed ESCs are based on differential braking. Nevertheless, electric vehicles’ growth, particularly those featuring an over-actuated configuration with individual wheel motors, allows for maintaining driveability without slowing down the vehicle. Standard control strategies are based on yaw rate tracking. The reference signal is model-based and needs precise knowledge of the friction coefficient. To increase the system robustness, more sophisticated approaches that include vehicle sideslip are introduced. Still, it is unclear how the two signals have to be weighted, and rarely proposed controllers have been experimentally validated. In this paper, we present a mixed sideslip and yaw rate stability controller. The mixed approach allows to address the control design as a single-input single-output problem simplifying the tuning process. Furthermore, we explain the rationale behind the choice of the weighting parameter. Eventually, the proposed ESC is validated following EU regulation in simulation and with an experimental vehicle on dry asphalt and snow. The results obtained in all the performed tests demonstrate that the proposed control strategy is robust and effective. The mixed approach is able to halve the sideslip in critical conditions with respect to a pure yaw rate approach.

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“…The allocation strategy command uses the optimization of convex functions to ensure optimum distribution of generalized control inputs to the actuators while ensuring the constraints. In [6] the same strategy was used to distribute commands to the braking forces on the four wheels taking into account the limitations of the actuators.…”

Section: Automotive Safetymentioning

confidence: 99%

A stability control of an electric vehicle using control allocation techniques

Amri

2013

2013 9th International Symposium on Mechatronics and Its Applications (ISMA)

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The main objective of this work is to study the control allocation technique. The context of this technique and the applications made in this framework are presented. An overview of this technique is highlighted and a mathematical formulation is given to show the advantages of the control allocation technique compared to conventional control method of over-actuated systems. An application of this technique was used in a closed-loop system in the case of an electric vehicle in order to control the stability of the yaw rate and to minimize the side slip angle during a turn.

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On active set algorithms for solving bound-constrained least squares control allocation problems

Cited by 8 publications

References 8 publications

Target Netgrams: An Annulus-Constrained Stress Model for Radial Graph Visualization

Target Netgrams: An Annulus-Constrained Stress Model for Radial Graph Visualization

A Mixed Sideslip Yaw Rate Stability Controller for Over-Actuated Vehicles

A stability control of an electric vehicle using control allocation techniques

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