Magnetic levitation actuators (MLAs) are increasingly employed in the modern high-precision manufacturing industry. Since the current-wrench transformation matrix is calculated inaccurately in the controller, the existing MLA finds it hard to undertake high-precision multi-degrees-of-freedom (DOF) movement in the large stroke. A high-fidelity real-time model is required to design better controllers for MLAs. This paper proposes a universal FPGA-based real-time wrench model (RTWM); meanwhile an MLA capable of translation and rotation in the horizontal plane is employed as the modeling object. To obtain the high accuracy with excellent generality, the force and torque distribution is solved through the magnetic node, coordinate transformation, and Gaussian quadrature. The corresponding calculation components are developed on the field-programmable gate array (FPGA) by exploiting the fully pipelined arithmetic and parallel architecture processing. Utilizing the high level synthesis tool, the final register transfer level structure is optimized adequately to reduce the time and hardware overhead. In the experiment, the RTWM of the proposed MLA and an existing MLA from the literature are obtained together to highlight the generality, and the computational accuracy is compared with the finite element method (FEM) software Comsol Multiphysics and a boundary element method software package Radia, respectively. The results show that the relative deviation is less than 2% choosing the FEM results as benchmark.

Magnetic levitation positioning systems have attracted an increasing amount of attention for many modern industrial applications because they can work in a large range of motion and in multiple degrees of freedom (DoFs) with resolutions as small as nanometer and microradian levels. In this paper, a 6-DoF positioning system based on 4 linear magnetic levitation actuators (MLAs) is designed and tested. In contrast to the existing modeling method, this work takes the yaw angle into account in the magnetic force and torque solutions of the linear MLA, and the revised model is employed in motion control. The raw data from the sensing system are processed by the Newton-Raphson method for the position and rotation motions of the translator. The PID compensator controls the equivalent second-order system as the motions in different axes are decoupled by the proposed wrench model. Experimental results related to the motion resolution, motion range, step response, trajectory tracking, and payload capacity are given to evaluate the performance of the prototype. The results show that the stroke of the maglev system is a volume of 20mm×20mm×4mm with a rotational range of 0.05rad×0.05rad×0.2rad and that the positioning precision depends on the resolution of the sensing system.

This paper presents a fault-tolerant control method based on the integral sliding mode (ISM) output feedback technique for the dynamic positioning control of an unmanned marine vehicle (UMV) subject to signal quantization and thruster faults. By using output information and estimates of thruster effectiveness factors, a novel integral sliding manifold is first constructed to maintain that the sliding function of system output equals the one of quantized output, which removes the region restriction that exists in the literature. Then based on the quantized signals of system output, a compensator is designed to introduce some degrees of design flexibility. To conquer the quantization effects, we incorporate a dynamic quantization parameter adjustment strategy and the fault-tolerant technique into the ISM output feedback control algorithm. The relation between the attraction area and quantization range has been revealed for the first time. Finally, the closed-loop stability can be guaranteed from every beginning time in despite of the quantization and thruster faults. Simulation through a typical floating production ship has verified the effectiveness of the proposed method.

An accurate wrench model is significant for the simulation, manufacture, and control of the commutated magnetically levitated planar actuator (CMLPA). With plenty of coils and permanent magnets employed in the coil set and magnet array of CMLPA, the computational burden of the corresponding wrench model can be substantial. This paper proposes an accurate, universal, and robust parallel massive-thread wrench model (PMWM) for the CMLPA. In PMWM, the magnetic node, Gaussian quadrature, and coordinate transformation are employed to express the interaction between magnet array and coil set. All of these calculation modules are implemented on the graphics processing unit in a massively parallel framework by CUDA. In order to highlight the performance of this PMWM, the wrench model of three different CMLPAs is computed. The computation accuracy and efficiency of proposed PMWM are compared with the finite-element method software Ansys Maxwell and a boundary element method software package named Radia, respectively. The same wrench model is also implemented on a multicore CPU through OpenMP and the comparative results are presented to show significant acceleration of the proposed massive-thread model.

The Aquila Optimizer (AO) algorithm is a meta-heuristic algorithm with excellent performance, although it may be insufficient or tend to fall into local optima as as the complexity of real-world optimization problems increases. To overcome the shortcomings of AO, we propose an improved Aquila Optimizer algorithm (IAO) which improves the original AO algorithm via three strategies. First, in order to improve the optimization process, we introduce a search control factor (SCF) in which the absolute value decreasing as the iteration progresses, improving the hunting strategies of AO. Second, the random opposition-based learning (ROBL) strategy is added to enhance the algorithm’s exploitation ability. Finally, the Gaussian mutation (GM) strategy is applied to improve the exploration phase. To evaluate the optimization performance, the IAO was estimated on 23 benchmark and CEC2019 test functions. Finally, four real-world engineering problems were used. From the experimental results in comparison with AO and well-known algorithms, the superiority of our proposed IAO is validated.