Axi-symmetric magnetic control functions are an important part of the ITER Plasma Control System (PCS) which is now at an advanced design stage. They are aimed at plasma current control, plasma shape control, and vertical stabilization. In principle, these control actions could be decoupled using different sets of active CS/PF coils as in many existing tokamaks. However, in large tokamaks with superconducting coils the controller design becomes more challenging given the high level of coupling among control circuits, the long control fields penetration time, and the use of the same actuators for different control purposes (the so-called actuator sharing). The objective of this paper is to make evidence of ITER PCS flexibility with an illustration of the architecture of the axi-symmetric magnetic control. Important features are (i) the capability to implement both a current-driven and a voltage-driven control scheme, (ii) the capability of controlling the plasma current either at the shape control level or at the circuit current control level, (iii) the concurrent use of both in-vessel and ex-vessel coils to tackle the vertical stabilization problem, (iv) and the capability to manage coil current limits and other exceptions in real-time. To guarantee satisfactory performance over all the operating envelope, a scheduling of the controller parameters is implemented at the control functions level, whereas a magnetic control local supervisor is in charge of the interface with the higher level supervisor, as well as of control algorithms selection. The design is carried out according to the general philosophy of the PCS design including also test assessments on the PCSSP platform.

We present new results regarding the stability properties of a stochastic nonlinear quadratic system (NLQS). The paper extends to the stochastic context a previous work concerning the domain of attraction of the zero equilibrium point of a NLQ. In this context, we use the concept of ( Ω ,α )—stability in probability and we achieve sufficient stability condition by exploiting the usual approach based on quadratic Lyapunov. This approach allows us to solve also the stabilization problem obtaining a procedure to design a state feedback control law which guarantees a region of attraction with a certain level of risk. The proposed designed procedure requires the solution of an optimization problem in the form of linear matrix inequalities, which allows us to estimate an upper bound for the quadratic performance functional. Two examples based on biological phenomena illustrate the effectiveness of the developed approach.

In this paper we propose a new hybrid approach, based on a deep reinforcement learning technique and a model-based technique, for the solution of the control problems regarding the magnetic confinement of a plasma in the DEMO tokamak. Reinforcement learning agents are used together with classical model-based controllers to perform the magnetic confinement of the plasma, i.e., to control the position, the shape and the current of the plasma. This hybrid approach allows us to simplify the training procedure of the data-driven control policy and to improve the performance of the model-based solutions. The performance of the proposed approach is shown in numerical simulations by evaluating the vertical stabilization capability and the error in tracking references on the plasma current and shape.

Magnetic confinement nuclear fusion offers a promising solution to the world’s growing energy demands. The DEMO reactor presented here aims to bridge the gap between laboratory fusion experiments and practical electricity generation, posing unique challenges for magnetic plasma diagnostics due to limited space for diagnostic equipment. This study employs Bayesian inference and Gaussian process modeling to integrate data from pick-up coils, flux loops, and saddle coils, enabling a qualitative estimation of the plasma current density distribution relying on only external magnetic measurements. The methodology successfully infers total plasma current, plasma centroid position, and six plasma–wall gap positions, while adhering to DEMO’s stringent accuracy standards. Additionally, the interchangeability between normal pick-up coils and saddle coils was assessed, revealing a clear preference for saddle coils. Initial steps were taken to utilize Bayesian experimental design for optimizing the orientation (normal or tangential) of pick-up coils within DEMO’s design constraints to improve the diagnostic setup’s inference precision. Our approach indicates the feasibility of Bayesian integrated data analysis in achieving precise and accurate probability distributions of plasma parameter crucial for the successful operation of DEMO.

An overview is presented of the progress since 2021 in the construction and scientific programme preparation of the Divertor Tokamak Test (DTT) facility. Licensing for building construction has been granted at the end of 2021. Licensing for Cat. A radiologic source has been also granted in 2022. The construction of the toroidal field magnet system is progressing. The prototype of the 170 GHz gyrotron has been produced and it is now under test on the FALCON facility. The design of the vacuum vessel, the poloidal field coils and the civil infrastructures has been completed. The shape of the first DTT divertor has been agreed with EUROfusion to test different plasma and exhaust scenarios: single null, double null, X-divertor and negative triangularity plasmas. A detailed research plan is being elaborated with the involvement of the EUROfusion laboratories.

In 2021 JET exploited its unique capabilities to operate with T and D-T fuel with an ITER-like Be/W wall (JET-ILW). This second major JET D-T campaign (DTE2), after DTE1 in 1997, represented the culmination of a series of JET enhancements-new fusion diagnostics, new T injection capabilities, refurbishment of the T plant, increased auxiliary heating, in-vessel calibration of 14 MeV neutron yield monitors-as well as significant advances in plasma theory and modelling in the fusion community. DTE2 was complemented by a sequence of isotope physics campaigns encompassing operation in pure tritium at high T-NBI power. Carefully conducted for safe operation with tritium, the new T and D-T experiments used 1 kg of T (vs 100 g in DTE1), yielding the most fusion reactor relevant D-T plasmas to date and expanding our understanding of isotopes and D-T mixture physics. Furthermore, since the JET T and DTE2 campaigns occurred almost 25 years after the last major D-T tokamak experiment, it was also a strategic goal of the European fusion programme to refresh operational experience of a nuclear tokamak to prepare staff for ITER operation. The key physics results of the JET T and DTE2 experiments, carried out within the EUROfusion JET1 work package, are reported in this paper. Progress in the technological exploitation of JET D-T operations, development and validation of nuclear codes, neutronic tools and techniques for ITER operations carried out by EUROfusion (started within the Horizon 2020 Framework Programme and continuing under the Horizon Europe FP) are reported in (Litaudon et al Nucl. Fusion accepted), while JET experience on T and D-T operations is presented in (King et al Nucl. Fusion submitted).

We present new results regarding the stability properties of a stochastic nonlinear quadratic system (NLQS). The paper extends to the stochastic context a previous work concerning the domain of attraction (DA) of the zero equilibrium point of a nonlinear quadratic system. A stabilizing control law is designed by considering the concept of (Omega, alpha) - stability in probability. The devised procedure requires the solution of a convex optimization problem. An example based on a stochastic epidemic model illustrates how to implement the developed approach.

Within the 9th European Framework programme, since 2021 EUROfusion is operating five tokamaks under the auspices of a single Task Force called ‘Tokamak Exploitation’. The goal is to benefit from the complementary capabilities of each machine in a coordinated way and help in developing a scientific output scalable to future largre machines. The programme of this Task Force ensures that ASDEX Upgrade, MAST-U, TCV, WEST and JET (since 2022) work together to achieve the objectives of Missions 1 and 2 of the EUROfusion Roadmap: i) demonstrate plasma scenarios that increase the success margin of ITER and satisfy the requirements of DEMO and, ii) demonstrate an integrated approach that can handle the large power leaving ITER and DEMO plasmas. The Tokamak Exploitation task force has therefore organized experiments on these two missions with the goal to strengthen the physics and operational basis for the ITER baseline scenario and for exploiting the recent plasma exhaust enhancements in all four devices (PEX: Plasma EXhaust) for exploring the solution for handling heat and particle exhaust in ITER and develop the conceptual solutions for DEMO. The ITER Baseline scenario has been developed in a similar way in ASDEX Upgrade, TCV and JET. Key risks for ITER such as disruptions and run-aways have been also investigated in TCV, ASDEX Upgrade and JET. Experiments have explored successfully different divertor configurations (standard, super-X, snowflakes) in MAST-U and TCV and studied tungsten melting in WEST and ASDEX Upgrade. The input from the smaller devices to JET has also been proven successful to set-up novel control schemes on disruption avoidance and detachment.

In this paper we propose a modular approach, based on a deep reinforcement learning technique, for the control of a plasma with a limited configuration in the DEMO tokamak. Three different reinforcement learning agents are used to perform the magnetic confinement of the plasma, i.e. to stabilize the vertical plasma instability, to control the radial centroid position, and to ramp-up the plasma current. This modular approach allows us to simplify the training procedure of the control policy, since it requires a lower overall computational load. Performance of the proposed approach are characterized by numerical simulations.

The paper details the process of developing the ITER Plasma Control System (PCS), that is, how to design and deploy it systematically, in the most efficient and effective manner. The integrated nature of the ITER PCS, with its multitude of coupled control functions, and its long-term development, calls for a different approach than the design and short-term deployment of individual controllers. It requires, in the first place, a flexible implementation strategy and system architecture that allows system re-configuration and optimization throughout its development. Secondly, a model-based system engineering approach is carried out, for the complete PCS development, i.e. both its design and deployment. It requires clear definitions for both the PCS role and its functionality, as well as definitions of the design and deployment process itself. The design and deployment process is shown to allow tracing the relationships of the many individual design and deployment aspects, such as system requirements, assumed operation use-cases and response models, and eventually verification and functional validation of the system design. The functional validation will make use of a dedicated PCS simulation platform that includes the description of the control function design as well as plant, actuator and sensor models that enable the simulation of these functions. By establishing a clear understanding of the interconnected steps involved in designing, implementing, commissioning, and operating the system, a more systematic approach is achieved. This ensures the completion of a comprehensive design that can be deployed efficiently, hence preventing the loss of precious operational time needed to debug and retune control functions and more importantly avoiding tokamak discharge disruptions.

An innovative and very detailed end-to-end system modelling tool has been developed and applied to test on simulated data the actual measurement capabilities of any generic high frequency (HF) magnetic diagnostic systems. The main goal of this rather complex tool is to obtain estimates of the intrinsic measurement uncertainties and then assess the actual vs. intended system measurement performance for correctly detecting individual components in the frequency spectrum of HF magnetic instabilities in the plasma. This has paramount consequences not solely for off-line analyses but also, and more importantly, for any real-time application where, as an example, the mode frequency, amplitude and {toroidal, poloidal} mode numbers are used to determine whether, and which, corrective actions need to be taken to stabilize the discharge. The algorithm has been applied to some of the various ITER HF magnetic diagnostic systems, most notably the AJ (LTCC-1D sensors) system as currently designed, hence providing specific confidence levels and error bounds for detecting the modes highlighted in the ITER measurement specifications. Additional analyses have been performed for the TCV and JET HF magnetic diagnostics, providing further constraints on the results obtained with these systems.

Reinforcement Learning has emerged as a promising approach to implement efficient data-driven controllers for a variety of applications. In this paper, a Deep Deterministic Policy Gradient (DDPG) algorithm is used to train a Vertical Stabilization agent, to be considered as a possible alternative to the model-based solutions usually adopted in existing machines. The agent is trained and validated considering the ITER tokamak magnetic control as case study environment. The tuning of the DDPG algorithm's hyper-parameters is motivated through a sensitivity analysis.

In this paper we consider the class of polynomial systems and we investigate on their finite-time stability properties. In this analysis, for the first time, finite-time stability is defined with respect to domains with polynomial bounds. A sufficient condition for finite-time stability is obtained, which can be solved recasting the feasibility problem in terms of SDP through SOS programming. Moreover, a nonlinear state-feedback control law is developed to stabilize the system in the finite-time notion. The effectiveness of the stabilizing control law is shown by a numerical example.

This paper deals with the use of a model predictive control technique to perform the magnetic confinement of a plasma in the DEMO tokamak. We show how to adapt the proposed strategy for the different phases, and hence different goals, of the plasma discharge and how to take into account the constraints that characterize the normal operations of a nuclear fusion reactor. We validate the performance of the proposed control system by using a nonlinear evolution code describing the plasma in a tokamak.

In this letter we present some new sufficient conditions for the annular stochastic finite-time stability of a class of stochastic linear time-varying systems. These new conditions are obtained adopting time-varying piecewise quadratic Lyapunov functions rather than the classical quadratic ones. The proposed approach allows us to extend the class of consider domains, which are typically limited to ellipsoidal domains. The proposed finite-time stability conditions can be converted into a feasibility problem based on a set of differential linear matrix inequalities. Two numerical examples are considered to perform a comparison with the previous results, and they show that the new proposed conditions are less conservative than the previous ones.

This paper proposes a model predictive controller (MPC) designed to tackle the magnetic control of the DEMO plasma. DEMO is an ambitious EU project aimed at the construction by 2050 of a tokamak demonstrating that energy from nuclear fusion can be conveniently commercially used. Magnetic control is one of the problems to be solved to operate the machine. Using MPC, in this paper it is shown how it is possible to take into account all the various constraints on the input and state variables during the controller design. The effectiveness of the proposed approach is demonstrated by means of simulations, using a validated nonlinear evolution code describing the interactions between the plasma and the surrounding metallic strictures.

In this article, the control approach based on structured input–output finite-time stability (IO-FTS) is extended to tackle the reference tracking problem. IO-FTS was originally introduced to deal with the disturbance rejection problem. By applying the finite-time stability control to a properly augmented system, we show that it is possible to enforce a set of specific requirements on the response of the closed-loop system during the transients, taking also into account saturation constraints on the actuators. Adding IO-FTS constraints to classic-state-feedback control law leads to a feasibility problem with bilinear matrix inequality (BMI) constraints. Herein, we show how the original BMI problem can be relaxed to a linear matrix inequality (LMI) one, which comes at a price of more conservatism, but turns out to be computationally more efficient. To prove the effectiveness of the proposed approach, we consider the case of the longitudinal control of a missile.

An initial concept for the plasma diagnostic and control (D&C) system has been developed as part of European studies towards the development of a demonstration tokamak fusion reactor (DEMO). The main objective is to develop a feasible, integrated concept design of the DEMO D&C system that can provide reliable plasma control and high performance (electricity output) over extended periods of operation. While the fusion power is maximized when operating near to the operational limits of the tokamak, the reliability of operation typically improves when choosing parameters significantly distant from these limits. In addition to these conflicting requirements, the D&C development has to cope with strong adverse effects acting on all in vessel components on DEMO (harsh neutron environment, particle fluxes, temperatures, electromagnetic forces, etc.). Moreover, space allocation and plasma access are constrained by the needs for first wall integrity and optimization of tritium breeding. Taking into account these boundary conditions, the main DEMO plasma control issues have been formulated, and a list of diagnostic systems and channels needed for plasma control has been developed, which were selected for their robustness and the required coverage of control issues. For a validation and refinement of this concept, simulation tools are being refined and applied for equilibrium, kinetic and mode control studies.

Within the European development of a future tokamak demonstration fusion power plant (DEMO) [1] the pre-conceptual studies on the plasma diagnostic and control (D&C) system are progressing to prepare the basis for reliable plasma operation at high overall performance [2]. A variety of plasma diagnostics will be employed on DEMO together with advanced control techniques in order to provide an accurate knowledge of the plasma state, which is needed to maintain plasma operation within the allowed physical and technical limits. The integration of diagnostic front-end components has to cope with strong adverse effects arising from neutron and gamma irradiation, heat loads, impinging particles and forces. In this environment, the quality of measurements can only be ensured for longer periods by using robust diagnostic components, mounting them in sufficiently protected (retracted) locations, and any maintenance can only be performed via remote handling. Major open issues are the durability of magnetic measurements in the presence of irradiation induced effects and the feasibility of detachment control under DEMO conditions. In parallel to diagnostic developments, the details of the main control issues are being formulated and investigated by quantitative plasma control simulations. To obtain the envisaged performance DEMO operates close to some physics limits where even small disturbances, if not properly controlled, can trigger major variations of the plasma parameters. Equilibrium control requires high control power and can drive the poloidal field coil system to its operational limits. Within this paper, we will provide an overview on the current status of the ongoing D&C developments for the European DEMO concept.