Nonlinear dynamic allocator for optimal input/output performance trade-off: Application to the JET tokamak shape controller

Tommasi, G. De; Galeani, Sergio; Pironti, A.; Varano, G.; Zaccarian, Luca

doi:10.1016/j.automatica.2011.01.080

Cited by 37 publications

(15 citation statements)

References 7 publications

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“…In order to increase the reliability of the overall system, the PF current control problem should include also the management of the current saturation in the coils. If the nominal currents are within the plant limits, this latter problem is usually tackled when designing the plasma current and shape control system (for example see [13] and [29]). …”

Section: The Pf Currents Control Problemmentioning

confidence: 99%

Plasma Magnetic Control in Tokamak Devices

Tommasi

2018

J Fusion Energ

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In tokamak experimental reactors, the magnetic control system is one of the main plasma control systems that is required, together with the density control, since the very beginning, even before first operations. Indeed, the magnetic control drives the current in the external poloidal circuits in order to first achieve the breakdown conditions and, after plasma formation, to track the desired plasma current, shape and position. Furthermore, when the plasma poloidal cross-section is vertically elongated, the magnetic control takes also care of the vertical stabilization of the plasma column, and therefore it is an essential system for operation. This chapter introduces a reference architecture for plasma magnetic control in tokamaks. Given the proposed architecture, the techniques to design all the required control algorithms is also presented. Experimental results obtained on the JET and EAST tokamaks and simulations for machines currently under construction are shown to prove the effectiveness of the proposed architecture and control algorithms.

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Section: The Pf Currents Control Problemmentioning

confidence: 99%

Plasma Magnetic Control in Tokamak Devices

Tommasi

2018

J Fusion Energ

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“…This rules out the possibility of using state-or input-dependent weighting functions or incorporating barrier functions to penalized trajectories as they approach the boundaries of given constraints. Consider, for example, the case of saturating actuators discussed in [5] and [6], where u = y c +u r is replaced by u = sat L (y c + u r ), where sat L (·) is the decentralized saturation function with saturation limits 1 , . .…”

Section: Nonlinear Dynamic Allocation Formentioning

confidence: 99%

“…The approach of [5], however, still considers the redundancy as pertaining essentially to the input/output mapping. Consequently, the assignment of steady-state trajectories in the state space was not addressed in the cited reference as well as in related work [6], [7].…”

Section: Introductionmentioning

confidence: 99%

Output regulation for over-actuated linear systems via inverse model allocation

Serrani

2012

2012 IEEE 51st IEEE Conference on Decision and Control (CDC)

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The synthesis of a full-information regulator for over-actuated linear systems is considered in this paper. Overactuation with injective input maps allows for redundancy in the steady-state trajectory in the state space compatible with a given reference output. This type of redundancy is completely characterized by means of geometric techniques and the results of the analysis are used to define an extended servomechanism that allows allocation of the reference trajectory in the state space to optimize certain cost functionals while maintaing invariance of the error-zeroing subspace. Examples of linear static and nonlinear dynamic allocation strategies are presented.

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“…The control strategy designed on the basis of this virtual input is then ''distributed'' across the redundant set of actuators via optimization of a given cost function. Notwithstanding the fact that multiple actuators are often necessary for technological reasons, an optimal design of the allocation stage has shown to lead to strong advantages in a broad range of applications (ranging from the aerospace to the automotive and several other industrial fields), both in terms of saturation handling (De Tommasi, Galeani, Pironti, Varano, & Zaccarian, 2011;Zaccarian, 2009) and in terms of fulfillment of more general performance goals (Boncagni et al, 2012;Cordiner, Galeani, Mecocci, Mulone, & Zaccarian, 2014;Passenbrunner, Sassano, & Zaccarian, 2012;Trégouët, Arzelier, Peaucelle, Pittet, & Zaccarian, in press;Zhou, Fiorentini, Canova, & Serrani, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…The steady-state optimization for an input-redundant linear system with nonlinear output function has been considered in Johansen and Sbarbaro (2005), with exosystem model restricted to pure integrators. For the same type of exosystem, the results in De Tommasi et al (2011) andZaccarian (2009) provide a framework allowing for nonlinear dynamic allocation solutions. This very framework has been in turn adopted in Serrani (2012), where the output regulation problem for strictly proper over-actuated LTI models is approached by resorting to a redundant servo-mechanism that directly allocates the trajectories of the plant inverse model.…”

Section: Introductionmentioning

confidence: 99%