The increased usage of electric and electronic devices on board the aircraft requested by the “More Electric Aircraft” (MEA) requires the adoption of multi-objective control algorithms, with controllers (supervisors) able to autonomously switch among different objectives. However, the operating point changes during operations, and “small signal” analysis becomes inconclusive to assess overall stability. Thus, the use of standard Proportional–Integral (PI) or Proportional–Integral–Derivative (PID) controllers may become an issue. In this paper, by using nonlinear mathematical tools, the theoretic stability of the controlled electrical devices is considered. Two different control tasks are considered, namely battery charging and generator current limiting. Then an automaton supervisor switches between the two control objectives. Each objective is achieved by using a sliding mode control with adaptive sliding manifold. The adaptation strategy increases robustness, and is crucial for MEA applications, since the controlled system parameters are highly uncertain, due to their harsh environment. Rigorous stability proofs are given, along with detailed simulations in different scenarios. Also hardware implementation is proposed and a comparison with existing strategies (i.e., the Proportional–Integral) is presented, showing the effectiveness of the proposed approach.

“更多电动飞机”（MEA）要求飞机上电气和电子设备使用的增加，要求采用多目标控制算法，并且控制器（主管）能够在不同目标之间自动切换。但是，操作点在操作过程中会发生变化，因此“小信号”分析对于评估整体稳定性并不确定。因此，使用标准比例积分（PI）或比例积分微分（PID）控制器可能会成为一个问题。在本文中，通过使用非线性数学工具，考虑了受控电气设备的理论稳定性。考虑了两种不同的控制任务，即电池充电和发电机电流限制。然后，自动机监控器在两个控制目标之间切换。通过使用带有自适应滑动歧管的滑模控制来实现每个目标。自适应策略提高了鲁棒性，对于MEA应用至关重要，因为受控系统参数由于其恶劣的环境而高度不确定。给出了严格的稳定性证明，以及在不同情况下的详细仿真。还提出了硬件实施方案，并与现有策略（即比例-积分）进行了比较，显示了所提出方法的有效性。以及在不同情况下的详细模拟。还提出了硬件实施方案，并与现有策略（即比例-积分）进行了比较，显示了所提出方法的有效性。以及在不同情况下的详细模拟。还提出了硬件实施方案，并与现有策略（即比例-积分）进行了比较，显示了所提出方法的有效性。