A Recursive Sparse Learning Method: Application to Jump Markov Linear Systems
نویسندگان
چکیده
منابع مشابه
a new type-ii fuzzy logic based controller for non-linear dynamical systems with application to 3-psp parallel robot
abstract type-ii fuzzy logic has shown its superiority over traditional fuzzy logic when dealing with uncertainty. type-ii fuzzy logic controllers are however newer and more promising approaches that have been recently applied to various fields due to their significant contribution especially when the noise (as an important instance of uncertainty) emerges. during the design of type- i fuz...
15 صفحه اولStabilization of Markov jump linear systems using quantized state feedback
This paper addresses the stabilization problem for single-input Markov jump linear systems via modedependent quantized state feedback. Given a measure of quantization coarseness, a mode-dependent logarithmic quantizer and amode-dependent linear state feedback law can achieve optimal coarseness for mean square quadratic stabilization of a Markov jump linear system, similar to existing results fo...
متن کاملCommunication-Limited Stabilisability of Jump Markov Linear Systems
This paper investigates the control of fully observed, scalar jump Markov linear systems in which feedback is transmitted at finite data rates over noiseless digital channels. In particular, the objective is to find the infimum data rate, over all causal coding and control laws, at which such a system may be asymptotically stabilised in mth absolute output moment. The control problem is first s...
متن کاملRobust H2 control of continuous-time Markov jump linear systems
This paper is concerned with the problem of designing robust H2 state-feedback controllers for continuous-time Markov jump linear systems subject to polytopic-type parameter uncertainty. Based on the parameter-dependent Lyapunov function approach, a new method for designing robust H2 controllers is presented in terms of solutions to a set of linear matrix inequalities. A numerical example is gi...
متن کاملParticle filters for state estimation of jump Markov linear systems
Jump Markov linear systems (JMLS) are linear systems whose parameters evolve with time according to a finite state Markov chain. In this paper, our aim is to recursively compute optimal state estimates for this class of systems. We present efficient simulation-based algorithms called particle filters to solve the optimal filtering problem as well as the optimal fixed-lag smoothing problem. Our ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IFAC Proceedings Volumes
سال: 2011
ISSN: 1474-6670
DOI: 10.3182/20110828-6-it-1002.02150