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Model Predictive Control (MPC) can effectively handle control problem with disturbances, multicontrol variables, and complex constraints and is widely used in various control systems. In MPC, the control input at each time step is obtained by solving an online optimization problem, which will cause a time delay in real time on embedded computers with limited computational resources. In this paper, we utilize adaptive Alternating Direction Method of Multipliers (a-ADMM) to accelerate the solution of MPC. This method adaptively adjusts penalty parameter to balance the value of primal residual and dual residual. The performance of this approach is profiled via the control of a quadcopter with 12 states and 4 controls and prediction horizon ranging from 10 to 40. The simulation results demonstrate that the MPC based on a-ADMM has a significant improvement in real-time and convergence performance and thus is more suitable for solving large-scale optimal control problems. [ABSTRACT FROM AUTHOR]

The lack of robust interphases between carbon and most metals prevent the exploration of the full scope potential of carbon-based metal matrix composites. Here, we demonstrated a scalable and straightforward way to produce strong interphase between copper (Cu) and carbon fibers (CFs) by designing a tailored titanium oxide-carbide coating (TiO y -TiC x) on CFs in a molten salt process. The oxide-carbide composition in the graded layer strongly depends on the coating temperature (800–950 °C). A coating with a high TiO y content obtained at a low coating temperature (800 °C) contributes to better molten-Cu wetting and strong adhesion energy between CFs and Cu during a subsequent exposure at 1200 °C. The Cu wetting angle for the TiO y -TiC x -CF sample obtained at 800 °C was ∼80° ± 5° with a Cu surface coverage of ∼50% versus ∼115° and ∼10% for the TiC x -CF sample made at 950 °C. The kinetic analysis of the coating process step by step suggests a growth rate limited by the mass-transfer through the coated layer. This method provides a novel approach to improve the thermal conductivity of Cu/C composite for thermal management applications. Image 1 [ABSTRACT FROM AUTHOR]

In the quest for novel, scalable and energy-efficient computing technologies, spin-based logic devices are being extensively explored due to their potential for nonvolatility, small cell area, and low operational power. Spin torque majority gate (STMG) is one of the most promising options for beyond CMOS nonvolatile logic circuits for normally-off computing. However, significant problems arose with cascade-ability, signal nonreciprocity, and complicated circuit configurations based on STMG. In this paper, a novel magnetic majority gate (MMG) logic has been proposed, utilizing both spin transfer torque and spin–orbit torque effects. A logic family including and/nand and or/nor functions can be achieved with an easy configuration and under a stable operation. Communication between logic units is realized by spin current injection through a nonferromagnetic metal wire to ensure its cascade-ability and nonreciprocity to design multiple logic-depth circuits. With all of these advantages, the proposed cascadable MMGs can be utilized to design logic functions such as the BUFFER/ NOT, XOR/ XNOR, and complicated logic gates, which pave the pathway for designing robust and comprehensive logic circuits using full spintronic devices. [ABSTRACT FROM AUTHOR]