This paper proposed a data-driven adaptive optimal control approach for CVCF (constant voltage, constant frequency) inverter based on reinforcement learning and dynamic programming (ADP). Different from existing literature, the load is treated as uncertainty robust state-feedback controller proposed. The stability of inverter-load system has been strictly analyzed. In order to obtain accurate o...

The scheduled electric vehicle (EV) charging flexibility has great potential in supporting the operation of power systems, yet achieving such benefits is challenged by uncertain and user-dependent nature EV behavior. Existing research primarily focuses on modeling arrival battery status rarely discusses uncertainty departure. In this paper, we investigate scheduling strategy to support load fla...

Stabilization and trajectory control of a quadrotor carrying a suspended load with a fixed known mass has been extensively studied in recent years. However, the load mass is not always known beforehand or may vary during the practical transportations. This mass uncertainty brings uncertain disturbances to the quadrotor system, causing existing controllers to have worse stability and trajectory ...

The paper presents a global optimization method to compute the minimum limit load factor of trusses subjected to unknown but bounded loads. We assume that the external forces consist of a part proportional to a load factor and a part that is uncertain around its nominal value. The worst-case limit load factor is introduced as the smallest limit load factor realized with some uncertain parameter...

Optimal design of beams subject to a combination of uncertain and deterministic transverse loads is presented using a min-max approach. The compliance of the beam is maximized to compute the worst case loading and minimized to determine the optimal cross-sectional shape. The uncertain component of the transverse load acting on the beam is not known a priori resulting in load uncertainty subject...

Demand response is nowadays considered as another type of generator, beyond just a simple peak reduction mechanism. A demand response service provider (DRSP) can, through its subcontracts with many energy customers, virtually generate electricity with actual load reduction. However, in this type of virtual generator, the amount of load reduction includes inevitable uncertainty, because it consi...

The divisible load scheduling is a paradigm in the area of distributed computing. The traditional divisible load theory is based on the fact that, the communications and computations are obedient and do not cheat the algorithm. The literature of review shows that the divisible load model fail to achieve its optimal performance, if the processors do not report their true computation rates. The d...

The scheduling strategy on load balancing, used by data center in cloud computing, plays an important role on computing performance, and it is a key technique for the high-performance service. It directly controls the total performance and the efficiency of resource in cloud computing. In this paper, we introduce seven recent patents in the area of load balancing of cloud computing and discuss ...