Paper Info
Title
Minimized Tracking Error Randomness Control for Nonlinear Multivariate and Non-Gaussian Systems Using the Generalized Density Evolution Equation
Abstract
In this technical note, a new stochastic control algorithm is presented for nonlinear and non-Gaussian continuous-time systems. Based on the recently developed generalized density evolution equation, which is more tractable than the classical Liouville equation, the relationship is established among the probability density function (PDF) of tracking error, control input and disturbances. An improved performance index is then constructed for this stochastic control strategy, which includes quadratic information potential of the tracking error, mean value of squared tracking error and constraints on the control input energy. By minimizing the performance index, a recursive optimal control algorithm is obtained using the gradient descent method. Moreover, the statistical linearization technique is adopted to formulate the boundedness condition of the closed-loop system. An illustrative example is given to demonstrate the validity and efficiency of the proposed stochastic optimal control methodology.
Year
DOI
Venue
2014
10.1109/TAC.2014.2305932
IEEE Trans. Automat. Contr.
Keywords
Field
DocType
Performance analysis,Equations,Mathematical model,Optimal control,Probability density function,Entropy,Stochastic processes
Mathematical optimization,Optimal control,Nonlinear system,Performance index,Multivariate statistics,Control theory,Density evolution,Gaussian,Mathematics,Tracking error,Randomness
Journal
Volume
Issue
ISSN
59
9
0018-9286
Citations 
PageRank 
References 
6
0.50
17
Authors
3
Name
Order
Citations
PageRank
Mifeng Ren1167.85
Jianhua Zhang27114.22
Hong Wang31332179.97