Design of Practical Control Algorithms for Nonlinear Stochastic Systems.
Abstract
This interim report summarizes a continuation of the investigation into the use of digital nonlinear filters in conjunction with deterministic control algorithms. The problem of stabilization and control of nonlinear stochastic systems observed by noisy measurement data arises in many Air Force systems. Inherent in this problem is the problem of processing noise contaminated measurement data to obtain accurate estimates of the state of the system. If it is possible to estimate the state of the system accurately, then well-known classical deterministic control techniques may often be used to give adequate system performance. This approach will greatly reduce the complexity of the control algorithm over that required by a truly optimal stochastic control policy. On the other hand, the use of recently developed filtering techniques in place of the simpler linearized or extended Kalman filter can greatly increase the accuracy of the state estimates and, thereby, improve system performance and alleviate divergence problems. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 31, 1978
- Accession Number
- ADA053611
Entities
People
- Daniel L. Alspach