Adjoint-Based Optimization Procedure for Active Vibration Control of Nonlinear Mechanical Systems

Author(s):  
Carmine M. Pappalardo ◽  
Domenico Guida

In this paper, a new computational algorithm for the numerical solution of the adjoint equations for the nonlinear optimal control problem is introduced. To this end, the main features of the optimal control theory are briefly reviewed and effectively employed to derive the adjoint equations for the active control of a mechanical system forced by external excitations. A general nonlinear formulation of the cost functional is assumed, and a feedforward (open-loop) control scheme is considered in the analytical structure of the control architecture. By doing so, the adjoint equations resulting from the optimal control theory enter into the formulation of a nonlinear differential-algebraic two-point boundary value problem, which mathematically describes the solution of the motion control problem under consideration. For the numerical solution of the problem at hand, an adjoint-based control optimization computational procedure is developed in this work to effectively and efficiently compute a nonlinear optimal control policy. A numerical example is provided in the paper to show the principal analytical aspects of the adjoint method. In particular, the feasibility and the effectiveness of the proposed adjoint-based numerical procedure are demonstrated for the reduction of the mechanical vibrations of a nonlinear two degrees-of-freedom dynamical system.

1995 ◽  
Vol 05 (02) ◽  
pp. 573-583 ◽  
Author(s):  
M. PASKOTA ◽  
A.I. MEES ◽  
K.L. TEO

In this paper, we consider the directing of orbits of discrete chaotic dynamical systems towards desired targets. Our aim is to significantly reduce the time needed to reach a target region by applying only small, bounded perturbations. We derive an open-loop control from methods of optimal control theory, and we discuss the effects of random dynamical noise on the open-loop control.


1988 ◽  
Vol 110 (2) ◽  
pp. 120-125 ◽  
Author(s):  
A. Akers ◽  
S. J. Lin

Optimal control theory is applied to the design of a pressure regulator for an axial piston pump and single-stage electrohydraulic valve combination. The control valve has been modeled and an optimal control law has been formulated. The time response curves due to a step input inflow rate and in current input to the servovalve have been obtained for the open loop and for the optimal control system. Comparison of the results has been made with previous work in which the supply valve to the swashplate actuators was not modeled. It is shown that controlled system modeling of the servovalve significantly improves system performance in terms of response frequency and pressure peaks.


2012 ◽  
Author(s):  
Leonard David Berkovitz ◽  
Negash G. Medhin

2009 ◽  
Vol 06 (07) ◽  
pp. 1221-1233 ◽  
Author(s):  
MARÍA BARBERO-LIÑÁN ◽  
MIGUEL C. MUÑOZ-LECANDA

A geometric method is described to characterize the different kinds of extremals in optimal control theory. This comes from the use of a presymplectic constraint algorithm starting from the necessary conditions given by Pontryagin's Maximum Principle. The algorithm must be run twice so as to obtain suitable sets that once projected must be compared. Apart from the design of this general algorithm useful for any optimal control problem, it is shown how to classify the set of extremals and, in particular, how to characterize the strict abnormality. An example of strict abnormal extremal for a particular control-affine system is also given.


2018 ◽  
Author(s):  
E.H. Bussell ◽  
C.E. Dangerfield ◽  
C.A. Gilligan ◽  
N.J. Cunniffe

SummaryMathematical models provide a rational basis to inform how, where and when to control disease. Assuming an accurate spatially-explicit simulation model can be fitted to spread data, it is straightforward to use it to test the performance of a range of management strategies. However, the typical complexity of simulation models and the vast set of possible controls mean that only a small subset of all possible strategies can ever be tested. An alternative approach – optimal control theory – allows the very best control to be identified unambiguously. However, the complexity of the underpinning mathematics means that disease models used to identify this optimum must be very simple. We highlight two frameworks for bridging the gap between detailed epidemic simulations and optimal control theory: open-loop and model predictive control. Both these frameworks approximate a simulation model with a simpler model more amenable to mathematical analysis. Using an illustrative example model we show the benefits of using feedback control, in which the approximation and control are updated as the epidemic progresses. Our work illustrates a new methodology to allow the insights of optimal control theory to inform practical disease management strategies, with the potential for application to diseases of plants, animals and humans.


1990 ◽  
Vol 112 (3) ◽  
pp. 475-481 ◽  
Author(s):  
S. J. Lin ◽  
A. Akers

This work presents a study of the applicability of optimal control theory to the design of a pressure regulator by use of an axial piston pump with a two-stage electrohydraulic servovalve. The control valve has been modeled and an optimal control law has been formulated. The time response curves due to a step input in flow rate to the pump have been obtained for the open loop and the for the optimal control system. An examination of the results has shown that the performance, in terms of pressure peaks and frequency during recovery to the flow disturbance, is significantly improved over that obtained when a single-stage valve is used.


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