Actuator allocation for integrated control in tokamaks:Architectural design and a mixed-integer programming algorithm

\u3cp\u3ePlasma control systems (PCS) in tokamaks need to fulfill a number of control tasks to achieve the desired physics goals. In present-day devices, actuators are usually assigned to a single control task. However, in future tokamaks, only a limited set of actuators is available for multiple control tasks at the same time. The priority to perform specific control tasks may change in real-time due to unforeseen plasma events and actuator availability may change due to failure. This requires the real-time allocation of available actuators to realize the requests by the control tasks, also known as actuator management.In this paper, we analyze possible architectures to interface the control tasks with the allocation of actuators inside the PCS. Additionally, we present an efficient actuator allocation algorithm for Heating and Current Drive (H&CD) actuators. The actuator allocation problem is formulated as a Mixed-Integer Quadratic Programming optimization problem, allowing to quickly search for the best allocation option without the need to compute all allocation options. The algorithms performance is demonstrated in examples involving the full proposed ITER H&CD system, where the desired allocation behavior is successfully achieved. This work contributes to establishing integrated control routines with shared actuators on existing and future tokamaks.\u3c/p\u3

Plasma internal profile control using IDA-PBC:application to TCV

\u3cp\u3eIn this paper, new results of plasma ι-profile and β control on TCV, using total plasma current I \u3csub\u3e p \u3c/sub\u3e, and ECCD (Electron Cyclotron heating and Current Drive) heating source have been discussed. The control model is governed by the resistive diffusion equation coupled with the thermal transport equation, written in PCH (Port-Controlled Hamiltonian) formulation. The IDA-PBC (Interconnection and Damping Assignment - Passivity based Control) controller is developed and tested on simulation as well as on TCV real plant. Two test scenarios are considered: ι control only, and ι and β control. The spatial distributions of ECCD profiles are pre-defined and only input powers are used for control design. Thus, a stationary control is defined in order to consider all non-linearity and actuator constraint, and a linear feedback IDA-PBC will ensure the convergence speed and the robustness of the closed-loop system. The obtained results are encouraging towards using routinely such plasma advanced control algorithm in a near future.\u3c/p\u3

Model predictive control of the current density distribution and stored energy in Tokamak Fusion Experiments using trajectory linearizations

\u3cp\u3eTokamaks are used to confine high temperature plasmas for nuclear fusion research.In this work we apply model predictive control to the transport process in a tokamak plasma that can be described by a set of nonlinear coupled partial differential equations, where the controlled quantities are the current density distribution and stored thermal energy. Applying trajectory linearizations around already commonly predefined feedforward trajectories enables us to use linear MPC techniques that are computationally tractable for implementation on existing tokamaks. Special requirements for the MPC controller are that it should be able to handle real-time-varying references and constraints, whereas the system size, required prediction horizon and available computational time imposes additional challenges. An MPC controller is designed according to the requirements and its performance is analyzed in simulations that approach high performance plasma experiments in the ASDEX Upgrade tokamak. The results show the potential of the controller and encourage its further exploration and use in experiments.\u3c/p\u3

Offset-free MPC for resource sharing on a nonlinear SCARA robot\u3csup\u3e⁎\u3c/sup\u3e

\u3cp\u3eHigh-precision motion industrial systems must satisfy tight performance requirements. Both positioning accuracy and throughput demands are typically achieved through improvements in hardware, thereby raising the bill of materials. A cost saving alternative could be to strive for a reduction in the hardware components needed, in combination with advanced motion control, to still meet the desired specifications. Particularly, in this paper, the possibility is analyzed to allow for resource sharing among several actuators. This results in a switched system, for which we develop a real-time MPC algorithm for optimization of both the input and the switching signals. This implementation applies to a fairly general class of nonlinear systems and uses a novel offset-free formulation in velocity form for LTV prediction models, to realize good tracking performance under the resource sharing constraints. We provide a proof of concept for this MPC solution on a high fidelity model of an industrial SCARA robot, where it is proposed to use a single amplifier to serve two actuators. The MPC solution is compared to heuristically switched LTI controllers, and the potential of the proposed approach is shown in simulations.\u3c/p\u3

Tokamak-agnostic actuator management for multi-task integrated control with application to TCV and ITER

\u3cp\u3eThe plasma control system (PCS) of a long-pulse tokamak must be able to handle multiple control tasks simultaneously, and must be capable of robust event handling with a limited set of actuators. For ITER, this is particularly challenging given the large number of actuator-conflicting control requirements. To deal with these issues, this work develops a task-based approach, where a plasma supervisory controller and an actuator manager make high-level decisions on how to handle the considered control tasks, using generic actuator resources and controllers. This simplifies the interface for operators and physicists since the generic control tasks (instead of controllers) can be directly defined from the general physics goals. This approach also allows one to decompose the PCS into a tokamak-dependent layer and a tokamak-agnostic layer. The developed scheme is first implemented and tested on TCV for simultaneous β control, neoclassical tearing mode (NTM) control, central co-current drive, and H-mode control tasks. It is then applied to an ITER test scenario to prove its flexibility and applicability to systematically handle a large number of tasks and actuators.\u3c/p\u3

Model predictive control for MR-HIFU-mediated, uniform hyperthermia

\u3cp\u3ePurpose: In local hyperthermia, precise temperature control throughout the entire target region is key for swift, safe, and effective treatment. In this article, we present a model predictive control (MPC) algorithm providing voxel-level temperature control in magnetic resonance-guided high intensity focused ultrasound (MR-HIFU) and assess the improvement in performance it provides over the current state of the art. Materials and methods: The influence of model detail on the prediction quality and runtime of the controller is evaluated and a tissue mimicking phantom is characterized using the resulting model. Next, potential problems arising from modeling errors are evaluated in silico and in the characterized phantom. Finally, the controller’s performance is compared to the current state-of-the-art hyperthermia controller in side-by-side experiments. Results: Modeling diffusion by heat exchange between four neighboring voxels achieves high predictive performance and results in runtimes suited for real-time control. Erroneous model parameters deteriorate the MPC’s performance. Using models derived from thermometry data acquired during low powered test sonications, however, high control performance is achieved. In a direct comparison with the state-of-the-art hyperthermia controller, the MPC produces smaller tracking errors and tighter temperature distributions, both in a homogeneous target and near a localized heat sink. Conclusion: Using thermal models deduced from low-powered test sonications, the proposed MPC algorithm provides good performance in phantoms. In direct comparison to the current state-of-the-art hyperthermia controller, MPC performs better due to the more finely tuned heating patterns and therefore constitutes an important step toward stable, uniform hyperthermia.\u3c/p\u3

POD-based recursive temperature estimation for MR-guided RF hyperthermia cancer treatment:a pilot study

\u3cp\u3eIn this paper, proper-orthogonal-decomposition (POD) reduced models of the body's heat response to radio-frequency hyperthermia cancer treatment are used for recursive temperature estimation. First, efficient low-dimensional models are obtained by projecting high-resolution finite-difference discretized models on low-dimensional subspaces spanned by empirical simulation modes. These models are then used in a Kalman filter to obtain recursive 3D temperature estimates from noise-susceptible magnetic resonance thermometry (MRT). The strategy is tested on an experimental setup containing an anthropomorphic phantom. It is found that recursive estimation reduces the mean absolute temperature error for the phantom experiment by 38% when compared to MRT and may be a valuable addition to MRT, most notably in the case where high quality thermometry is temporally interleaved with thermometry of degraded quality.\u3c/p\u3

Experiments on actuator management and integrated control at ASDEX Upgrade

\u3cp\u3eThe established field of integrated multivariable control promises improved performance and stability for strongly coupled processes, given a control-oriented model of the system. Fusion plasmas are strongly coupled, but there is currently no model which accurately reflects the nature of these complex interactions. Therefore, experiments were performed specifically to investigate coupling between controlled parameters, as a step towards designing integrated controllers in the future. The parameters chosen were core density, divertor neutral pressure and divertor temperature. For control of the plasma pressure and Neoclassical Tearing Modes, where a simple model of the coupling is known, it will be shown that linking the two controllers gives reliably good plasma performance. An additional complication with integrated control is that limited actuator resources are often oversubscribed when trying to control multiple parameters simultaneously. In order to achieve the optimum result, some form of actuator management is a pre-requisite for integrated control. An algorithm has been developed to automatically allocate Electron Cyclotron Resonant Heating gyrotrons to targets, by evaluating a cost function in real-time. Results will be shown to demonstrate the flexibility of this routine to changes in plasma state, gyrotron availability and the goals of the physics experiment.\u3c/p\u3