When optimizing electric power system operational decisions, it is of great importance to prevent potential failures in both the system operation and the optimization algorithm. In “An Alternating Direction Method of Multipliers-Based Distributed Optimization Method for Solving Security-Constrained Alternating Current Optimal Power Flow,” Gholami, Sun, Zhang, and Sun propose a novel two-level algorithm that (1) effectively prevents power system operational failures through consideration of impactful contingencies and (2) guarantees convergence when parallelized on a computing cluster with multiple nodes. Extensive numerical experiments suggest that the proposed algorithm is able to provide high-quality feasible solutions under the time limit of 10–45 minutes for various synthetic and industrial networks with up to 30,000 buses and 22,000 contingencies, comparable with the size of the U.S. power grid.

The load side and the motor connected by flexible joints in the manipulators’ joint servo system. During the motion of manipulators driven by tendon-sheath, the status change of the end-effector will result in the change of the load side rotational inertia. The perturbation of the inertia of the load side will result in the modeling mismatch of the servo system. So the modeling uncertainty and the system robustness will decrease. An adaptive sliding mode robust control based on HJI (Hamilton-Jacobi-Issacs) theory is proposed in this paper to improve the robustness of the system. Firstly, according to D-H coordinate method, kinematics and dynamics models of the manipulator are established. Then, the basic strategy of adaptive sliding mode robust control is proposed. The variation of control parameters of a single joint of the manipulator is adjusted to reduce the control cost. Next, the sliding mode control law was established through the design of the Lyapunov function based on the HJI theory. The manipulator dynamics model was taken as the research object. The simulation analysis was conducted in uncertain parameters. Finally, a series of manipulator prototype experiments were carried out to proof our control theory. The experiment results show that our method can better solve the model uncertainty caused by the servo system. The adaptive sliding mode robust control strategy based on HJI theory has lower dependence on accurately modeling and stronger robustness.