Estimation for a Feedback System With a Desired Final State and Intermittent Stochastic Inputs
| Autor: | Peter J. Shea, Shida Ye, Chee-Yee Chong, Yaakov Bar-Shalom, Radu Visina |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | IEEE Transactions on Aerospace and Electronic Systems. 58:5351-5360 |
| ISSN: | 2371-9877 0018-9251 |
| DOI: | 10.1109/taes.2022.3170289 |
| Popis: | The system considered in this paper operates with a feedback that is characterized by a gain and a desired final state (DFS), which is the main parameter of interest in the present study. The system is, however, subjected intermittently to stochastic inputs according to a Markov process. Since the system operates in two modes | under the feedback to the DFS and under a stochastic input|the Interacting Multiple Model (IMM) estimator is used. Two approaches are considered: (i) the DFS is a discrete-valued random variable | one of a finite number of possible states | with an a priori probability mass function (pmf), and (ii) the DFS is a continuous-valued random variable with an a priori probability density function (pdf). For Approach (i), we use a multiple IMM estimator (MIMM) that features one IMM for each one of the possible DFS. The a posteriori probability of the model for each IMM, i.e., of each DFS, will be computed based on the likelihood function (LF) of the corresponding IMM. For Approach (ii), we design a single IMM to handle the unknown DFS to be estimated (mode M1), and the random inputs (mode M2). Simulation results explore several scenarios and investigate the degree of observability of this stochastic problem. |
| Databáze: | OpenAIRE |
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