Controlling large-scale systems sometimes requires decentralized computation. Communication among agents is crucial to achieving consensus and optimal global behavior. These negotiation mechanisms are sensitive attacks on those exchanges. This paper proposes an algorithm based Expectation Maximization mitigate the effects of in a resource allocation distributed model predictive control. The per...

Robust tube-based model predictive control (MPC) methods address constraint satisfaction by leveraging an a priori determined tube controller in the prediction to tighten constraints. This letter presents system level tube-MPC (SLTMPC) method derived from parameterization (SLP), which allows optimization over online when solving MPC problem, can significantly reduce conservativeness. We derive ...

For the locomotion control of a legged robot, both model predictive (MPC) and reinforcement learning (RL) demonstrate powerful capabilities. MPC transfers high-level task to lower-level joint based on understanding robot environment, model-free RL learns how work through trial error, has ability evolve historical data. In this work, we proposed novel framework integrate advantages RL, learned p...

As a complex system, crowd dynamics emerge bottom-up from the local interactions between pedestrians as component subsystems. This article proposes predictive agent-based simulation model to analyze outcomes of emergency evacuation scenarios taking into account collisions pedestrians, smoke, fire sprinklers, and exit indicators. The is based on decentralized control system structure, where each...

Nowadays, extensive research has been conducted for gas turbine engines control due to growing importance of gas turbine engines for different industries and the need to design a suitable control system for a gas turbine as the heart of the industry. In order to design gas turbine control system, various control variables can be used, but in the meantime, fuel flow inserting into combustion cha...