This paper presents a model based on Hamilton's law of varying action for stochastic dynamic systems. In this model, the state variables are approximated as a linear sum of orthogonal polynomials. For deterministic systems, the coefficients of the polynomials are constant, but for stochastic systems
Hamilton’s law of varying action: Part II: Direct optimal control of linear systems
✍ Scribed by H. Öz; E. Adigüzel
- Publisher
- Elsevier Science
- Year
- 1995
- Tongue
- English
- Weight
- 589 KB
- Volume
- 179
- Category
- Article
- ISSN
- 0022-460X
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✦ Synopsis
A direct optimal procedure is developed for the control of linear, time varying, spatially discrete mechanical systems. An assumed-time-modes method in which the dependent variables of the dynamics problem are expanded in terms of admissible basis functions in time is extended to include a similar representation of the control inputs. This approach, together with direct use of Hamilton's law of varying action, allows explicit a priori integration in time of the energy related quantities leading to the algebraic equations of motion, thus the conventional first order differential state equations are obviated. Expansion coefficients for the dependent variables and those for input forces constitute the states and controls, respectively. A typical performance measure of linear quadratic regulator theory is considered for the optimal control problem and it is transformed into an algebraic objective function by using the assumed-time-modes expansions. The resulting algebraic optimality problem yields closed-form solutions for the optimal control gains directly. Some computational aspects of the proposed methodology are pointed out; numerical solutions for single-and multi-degrees-of-freedom problems are included.
📜 SIMILAR VOLUMES
Without consideration of force equilibrium and differential equations of motion, a general derivation of algebraic equations for dynamic systems is presented. This is achieved by an assumed-time-modes approach in conjunction with a direct application of Hamilton's law of varying action. By assumed-t
Operator techniques can be used to study linear time-varying control and dual-rate sampled-data control problems with an ~ optimality criterion.
State analysis and optimization of time-varying systems via Haar wavelets are proposed in this paper. Based upon some useful properties of Haar functions, a special product matrix and a related coefficient matrix are applied to solve the time-varying systems first. Then the backward integration is i