Active magnetic compensation technology can effectively reduce magnetic field disturbances within a magnetic shielding room (MSR) and improve the signal-to-noise ratio of magnetoencephalography (MEG) measurement. But, for small-sized MSRs with external compensation coils, achieving high-precision magnetic field control is challenging, because it is difficult to establish an accurate mathematical model. In this article, an active magnetic compensation system is constructed based on model-free adaptive control with a radial basis function neural network (MFAC-RBFNN) method, which addresses the limitations of magnetic field control accuracy caused by the requirement for precise system model information. The nonlinear and coupling characteristics of the active magnetic compensation system were analyzed, and a model-free adaptive control (MFAC) controller is designed based on the input current and output magnetic field, and the utilization of radial basis function neural network (RBFNN) for estimating magnetic field disturbances. The experimental results are given to prove that the algorithm proposed can achieve high-precision control of magnetic field within the MSR without an accurate system model, and compared with proportional–integral–derivative (PID), the magnetic field disturbance reduction effect is improved by $2.4\times $ . It contributes to generating a near-zero magnetic field environment with low magnetic field disturbance.

The Magnetoencephalography (MEG) based on atomic magnetometer has high demand for the uniformity in the measurement area. Due to the door and holes of the magnetically shielding room (MSR), the distribution of residual magnetic field is non-linear, introducing much trouble into the magnetic field compensation. This study proposes a method for improving the uniformity of the residual magnetic field in the compact MSR by injecting different currents into the two coils in each pair of the outside compensation coils. The model and theoretical analysis method have been established, the feasibility has been verified both by the simulation and the experimental test. Results show that the maximum of the three components of the residual magnetic field in the direction of the three axes can be reduced by 18 times, 10.6 times and 8.1 times, respectively, when compared with the results without compensation, and 2.4 times, 2.3 times and 2.2 times, respectively, when compared with the results compensated with the same current. This study can provide certain help for achieving ultra-weak magnetic environment with high uniformity for the MEG measurement Note to Practitioners —In this article, we focus on the problem of compensating the residual magnetic field in the compact MSR with high efficiency and low cost, which remains the key factor that limits the promotion of the MEG. Method based on the compensation coils in series outside the MSR only deals with the linear or symmetric components, but has nothing to do with the non-linear and asymmetric one caused by the door. We propose a new method for compensating the residual magnetic field based on the coupling between the active and passive shielding, high compensation efficiency and uniformity can be achieved. In future work, we will aim at applying this method to create an ultra-weak magnetic field environment with high uniformity for the MEG measurement.

Evaluating and enhancing the alternating current (AC) shielding performance of magnetic shielding cylinders (MSCs) is important to improve the sensitivity of magnetometers and the signal-to-noise ratio of magnetocardiography (MCG). The dynamic radial shielding factor (RSF) of single-ended open MSC rapidly decreases with increasing frequency. To accurately analyze and improve the dynamic RSF, a high-performance and low-cost permalloy-nanocrystalline composite structure (P-N-MSC) is innovatively proposed based on the analytical and finite element model in this paper. The structural reason why placing nanocrystals in the innermost layer of P-N-MSC performs significantly better than placing nanocrystals in the middle and outer layers is analyzed in detail through experiments and finite element simulations. The average dynamic RSF of P-N- MSC is 2.05 times higher than that of MSC among 0.5 ~ 95 Hz. The average noise at 0.5 ~ 95 Hz is reduced by 63.58%. This study provides a theoretical basis and technical support for constructing magnetic shielding devices with high magnetic shielding performance.

Active magnetic compensation (AMC) is of significant importance in enhancing the signal-to-noise ratio of cardiac magnetic signals. However, in practical environments, multiple magnetic disturbances exist and need to be suppressed to ensure the accuracy of magnetocardiography (MCG) measurements. This paper proposes a model reference adaptive extended state observer with tracking filter (MRA-TESO) based high-precision active magnetic compensation method. It addresses the model errors in the AMC system and the insufficient capability of a typical extended state observer (ESO) in estimating complex disturbances. In the MRA-TESO framework, a tracking filter is employed to increase the system type of the equivalent open-loop transfer function for improved disturbance observation. Additionally, a model reference adaptive law is introduced to reduce internal system disturbances, providing more accurate model information and thereby lowering the bandwidth required for disturbance estimation. Experimental results demonstrate that the proposed method achieves satisfactory disturbance rejection performance. Note to Practitioners—In this paper, we focus on the issue of magnetic field disturbances in a magnetic shielding cylinder, which is a critical factor that limits the accuracy of MCG measurements. The disturbance suppression methods based on the typical ESO have inadequate accuracy in estimating complex disturbances. This paper proposes a high-precision disturbance suppression method based on MRA-TESO, which enhances the disturbance suppression capability. In future work, we will strive to create a stable environment for MCG measurements using this method, thus improving the accuracy of MCG measurements.

The magnetoencephalography (MEG) measurement is important for diagnosing and treating brain functional diseases. MEG measurement based on the atomic magnetometer requires highly uniform and stable magnetic field environment, which is usually achieved by combining magnetic shielding room (MSR) and biplanar coils control system. However, the control effect heavily relies on the performance of the MSR. A hybrid control method based on dual-coil is proposed in this study, which reduces the dependence of the control effect on the MSR by actively adjusting the magnetic field distribution in the MSR and ensures high control accuracy based on the Rayleigh model relationship between the compensation coils and the MSR, better results can be achieved compared with the biplanar coils control system. The proposed method can provide certain reference for developing the active and passive combined magnetic shielding system with low cost and high performance for the MEG.

This study addresses the challenge of cross-axis magnetic field coupling in active magnetic compensation (AMC) system for magnetic shielding room (MSR), which limits control accuracy in weak magnetic environment. A three-input three-output (TITO) model of AMC system is constructed, and a simplified generalized predictive control (TITO-SGPC) is proposed, using attenuation sequence to reduce high-dimensional matrix operations. Experimental results show that TITO-SGPC suppresses cross-axis coupling magnetic field within 0.34 nT, achieving over 2.4 times higher suppression than traditional GPC. Compared with multiple-input multiple-output model predictive control (MIMO-MPC), the computational complexity is significantly reduced, the execution time and memory usage are reduced by 14 times and 2.2 times, respectively, and it has better disturbance suppression effect. This method overcomes the limitations of traditional decentralized control and computationally intensive MIMO methods by explicitly establishing a three-axis cross model, and uniquely balances coupling suppression and real-time performance. This study provides a modular and high-precision solution for biomagnetic measurement, enabling stable control in MSRs with different geometries and supporting advancements in weak magnetic measurement technology.