Quantized stabilization of stochastic systems with multiplicative noise under Markovian switching

Abstract

A problem of quantized state feedback quadratic mean-square stabilization of discrete-time stochastic processes under Markovian switching and multiplicative noise is considered. A static quantizer is used in the feedback channel and the jump Markovian switching is modeled by a discrete-time Markov chain. The control input is simultaneously applied to both the rate vector and the diffusion term. It is shown that the coarsest quantization density that permits quadratic mean-square stabilization of this system is achieved with the use of a logarithmic quantizer, and the coarsest quantization density is determined by an algebraic Riccati equation, which is also the solution to a special linear stochastic Markovian switching control system. Also, sufficient conditions for exponential mean-square stabilization of such systems are also explored. An example is given to demonstrate the obtained results.

Keywords:

• Logarithmic quantization
• stochastic systems
• Markovian switching systems
• discrete- time systems

Additional information

Funding

This work was supported in part by DOD Grant W911NF-08-0514 and NSF Grant CMMI-0927664.