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...

If there are grey variables in the constraint conditions in uncertain programming, the programming is called grey chance constrained programming. In this paper we provide the concept of grey chance constrained programming. When the whitenization weight functions of grey variables are known and the distribution functions are constructed, we studied the certainty equivalence solution of grey chan...

In order to mitigate the environmental pollution caused by sea freight, we focused on optimizing carbon emissions in container terminal operations. This paper establishes a mixed integer programming (MIP) model for continuous berth allocation problem (CBAP) considering tide time window. We aimed minimize total waiting time, consumption and deviation preference. overcome influence of an uncertai...

The mean-variance model proposed by Markowitz has received greatly acceptance as a practical methodology to manage portfolio selection, and has been widely extended in a variety of literatures. The aim of this paper is to extend the mean-variance model in uncertain decision systems. We present a new mean-TVaR model for portfolio selection when the returns of securities are described as uncertai...