The state dependent Riccati equation (SDRE) technique is a recently developed methodology for designing control laws and estimation algorithms for missile flight control. Although its potential is well recognized by control theory experts, the industry acceptance of the technique has been slow. The main reasons for this are: a) unlike linear control technology, the SDRE approach requires advanced numerical methods for its implementation, which are not currently available off-the-shelf, b) the perception that this technique may not be computationally feasible for real-time implementation on flight control processors.Both of these issues are addressed in this paper. A software package for real-time implementation of the SDRE technique was developed during the present research. The execution of this software at speeds up to 2 kHz sample rates on problems of the size commonly encountered in missile flight control applications was then demonstrated on commercial off-theshelf processors.
A human diver in the air is an example of a nonholonomic system with drift. In this paper, we present a dynamic model of the diver performing planar dives and examine a simple learning approach to the control problem. Finally, we present a proposal for a general, hierarchical, learning controller for systems with many degrees of freedom.
Abstract-This paper studies tracking of a reference path in a networked control system where the controller consists of a central decision maker and an on-site controller, which are connected through a discrete noiseless channel. The reference path is available noncausally to the central decision maker and the on-site controller has access to noisy observations from the plant and the reference information provided by the central decision maker. For a quadratic optimization objective, we provide the optimal control using dynamic programming and show that the optimal controller can be separated into a noncausal feedforward term (generated by the central decision maker) plus a feedback term (generated by the on-site controller) which has causal access to the controls applied without any loss of performance. We show that the feedforward control is the solution of a deterministic quadratic program, i.e., certainty equivalence holds. We later study the problem of transmission of the feedforward controls to the on-site controller over a discrete noiseless channel. We formulate and solve an optimization problem for the optimal time-varying and time invariant uniform quantization of the feedforward control signals sent by the central decision maker to the on-site controller over a communication network.
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