Haopeng Zhang
Research interests:
Control theory and optimization:
dynamical systems, distributed control, multi-agent systems, numerical optimization and swarm intelligence
Applications:
Power systems, swarm robots, glucose insulin regulation
Education
- Ph.D. in Mechanical Enginnering, Texas Tech University, 2014
- B.S. in Electrical Engineering, Sun Yat-Sen Univeristy, 2009
Publications
This paper addresses some fundamental questions towards robust and optimal imperfect information state equipartitioning by means of a computational framework of a system-theoretic approach called semistable Gaussian Linear-Quadratic Consensus (LQC), which is motivated by Optimal Semistable Control (OSC). OSC deals with an optimal regulation problem for dynamical systems with unknown, nonzero set-points. In this paper, we address stochastic OSC for robust and optimal information state equipartitioning under Gaussian white noise disturbance or measurement and random distribution of initial conditions. We develop a new framework for semistable Gaussian LQC and recast the proposed problem into an alternative, constrained optimization problem