Comparison of Static and Dynamic Control Allocation Techniques for Integrated Vehicle Control

Tavasoli, Ali; Naraghi, Mohammad

doi:10.3182/20110828-6-it-1002.00398

Cited by 10 publications

(13 citation statements)

References 14 publications

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“…Notice that the latter is not an obvious feature due to the fact that this dynamic control allocation is only asymptotically optimal, and may deviate at every time-instant from the instantaneous optimal allocation of the corresponding static control allocation problem. This is leading to some loss of performance as shown in a case study in (Tavasoli & Naraghi 2011). The main advantage of the method is that no direct numerical optimization is needed (optimality tracking is built into the dynamic update law (39)) leading to modest computational complexity.…”

Section: Dynamic Optimum-seeking Methodsmentioning

confidence: 99%

“…Estimation of maximum tire-road friction coefficient is an integral part of the adaptive control allocation strategy. In (Tavasoli & Naraghi 2011), the performance of the method is further compared to a (static) nonlinear programming approach. A simpler gradient-based dynamic control allocation approach is shown to be effective in (Gerard & Verhaegen 2009).…”

Section: Yaw Stability Controlmentioning

confidence: 99%

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Control allocation—A survey

2013

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The control algorithm hierarchy of motion control for over-actuated mechanical systems with a redundant set of effectors and actuators commonly includes three levels. First, a high-level motion control algorithm commands a vector of virtual control efforts (i.e. forces and moments) in order to meet the overall motion control objectives. Second, a control allocation algorithm coordinates the different effectors such that they together produce the desired virtual control efforts, if possible. Third, low-level control algorithms may be used to control each individual effector via its actuators. Control allocation offers the advantage of a modular design where the high-level motion control algorithm can be designed without detailed knowledge about the effectors and actuators. Important issues such as input saturation and rate constraints, actuator and effector fault tolerance, and meeting secondary objectives such as power efficiency and tear-and-wear minimization are handled within the control allocation algorithm. The objective of the present paper is to survey control allocation algorithms, motivated by the rapidly growing range of applications that have expanded from the aerospace and maritime industries, where control allocation has its roots, to automotive, mechatronics, and other industries. The survey classifies the different algorithms according to two main classes based on the use of linear or nonlinear models, respectively. The presence of physical constraints (e.g input saturation and rate constraints), operational constraints and secondary objectives makes optimization-based design a powerful approach. The simplest formulations allow explicit solutions to be computed using numerical linear algebra in combination with some logic and engineering solutions, while the more challenging formulations with nonlinear models or complex constraints and objectives call for iterative numerical optimization procedures. Experiences using the different methods in aerospace, maritime, automotive and other application areas are discussed. The paper ends with some perspectives on new applications and theoretical challenges.

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Section: Dynamic Optimum-seeking Methodsmentioning

confidence: 99%

Section: Yaw Stability Controlmentioning

confidence: 99%

Control allocation—A survey

2013

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“…Next, the approximation function yields the (approximate) optimal front-to-total torque ratios, γ * l and γ * r . The traction force and yaw moment targets are used in conjunction with the torque ratios in equations (1), (2), (6) and (7) (2), (6), (7) F ref…”

Section: Approximation Function For Online Applicationmentioning

confidence: 99%

“…Indeed, there are a variety of cost functions for control allocation optimisation which relate tyre slip [5], actuator effort [6] and power losses from the electric motor drives [7,8,9] with the torques produced at the four wheels. The latter studies demonstrate a marginal power saving using an optimisation procedure during wheel torque allocation.…”

Section: Introductionmentioning

confidence: 99%

Reducing the motor power losses of a four-wheel drive, fully electric vehicle via wheel torque allocation

Pennycott

Novellis

Sabbatini

et al. 2014

Proceedings of the Institution of Mechanical Engineers, Part D:

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Individually-controlled electric motors provide opportunities for enhancing the handling characteristics and energy efficiency of fully electric vehicles. Online power loss minimisation schemes based on electric motor efficiency data may, however, be impractical for real-time implementation due to the heavy computational demand. In this paper, the optimal wheel torque distribution for minimal power losses in the electric motor drives is evaluated in an offline optimisation procedure and then approximated using a simple function for online control allocation. The wheel torque allocation scheme is evaluated via a simulation approach incorporating constant speed driving at constant speed, ramp and step steer manoeuvres. The energy efficient wheel torque allocation scheme provides motor power loss reductions and yields savings in the total power utilisation compared to a simpler method in which the torques are evenly distributed across the four wheels. The method does not rely on complex online optimisation and can be applied on real electric vehicles in order to improve efficiency and thus reduce power consumption during different manoeuvres.

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“…however, its performance during manoeuvres with high nonlinear behaviour of vehicle and tires is lower compared to static control allocation [45]. Some examples of allocation configurations of input control are given below:…”

Section: Control Allocation For Automotive Tasksmentioning

confidence: 99%

Coordinated control of multi-actuated electric vehicle

Shyrokau¹

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Comparison of Static and Dynamic Control Allocation Techniques for Integrated Vehicle Control

Cited by 10 publications

References 14 publications

Control allocation—A survey

Control allocation—A survey

Reducing the motor power losses of a four-wheel drive, fully electric vehicle via wheel torque allocation

Coordinated control of multi-actuated electric vehicle

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