Numerical methods of optimal control theory using variations in the state space

Cybernetics ◽  
1968 ◽  
Vol 2 (3) ◽  
pp. 1-23 ◽  
Author(s):  
N. N. Moiseev
Keyword(s):  
Optimal Control ◽  
Numerical Methods ◽  
Control Theory ◽  
State Space ◽  
Optimal Control Theory ◽  
The State

Observer Design for Active Suspension Control for Passenger Cars

2006 ◽  
Author(s):  
Federico Cheli ◽  
Ferruccio Resta ◽  
Edoardo Sabbioni
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
State Space ◽  
Optimal Control Theory ◽  
State Vector ◽  
The State ◽  
Observer Design ◽  
Passenger Cars ◽  
Suspension Control ◽  
System States

An observer for controlled suspension is presented in this paper based on acceleration measurements. The proposed observer allows to estimate the system states and can be profitably used in a state-derivative feed-back control. This kind of control, designed in the reciprocal-state-space framework (RSS), is based on the optimal control theory and consists in minimizing the derivative of the state vector instead of the state vector itself.

Dispersion of nanoparticles with optimal control theory based on destabilization

2014 ◽  
Vol 2 ◽  
pp. 86-86
Author(s):  
Miki U. Kobayashi ◽  
Nobuaki Aoki ◽  
Noriyoshi Manabe ◽  
Tadafumi Adschiri
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
Optimal Control Theory ◽  
Dispersion Of Nanoparticles

scholarly journals Recoil control of deepwater drilling riser system based on optimal control theory

2020 ◽  
pp. 108473
Author(s):  
Xiuquan Liu ◽  
Zhaowei Liu ◽  
Xianglei Wang ◽  
Nan Zhang ◽  
Na Qiu ◽  
...  
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
Optimal Control Theory ◽  
Deepwater Drilling

scholarly journals Optimal Control for a COVID-19 Model Accounting for Symptomatic and Asymptomatic

2020 ◽  
Vol 8 (1) ◽  
pp. 168-179
Author(s):  
Jead M. Macalisang ◽  
Mark L. Caay ◽  
Jayrold P. Arcede ◽  
Randy L. Caga-anan
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
Medical Care ◽  
Optimal Control Theory ◽  
Comparable Result ◽  
Type Model ◽  
Hospital Beds ◽  
Transmission Reduction ◽  
Bed Capacity ◽  
The Government

AbstractBuilding on an SEIR-type model of COVID-19 where the infecteds are further divided into symptomatic and asymptomatic, a system incorporating the various possible interventions is formulated. Interventions, also referred to as controls, include transmission reduction (e.g., lockdown, social distancing, barrier gestures); testing/isolation on the exposed, symptomatic and asymptomatic compartments; and medical controls such as enhancing patients’ medical care and increasing bed capacity. By considering the government’s capacity, the best strategies for implementing the controls were obtained using optimal control theory. Results show that, if all the controls are to be used, the more able the government is, the more it should implement transmission reduction, testing, and enhancing patients’ medical care without increasing hospital beds. However, if the government finds it very difficult to implement the controls for economic reasons, the best approach is to increase the hospital beds. Moreover, among the testing/isolation controls, testing/isolation in the exposed compartment is the least needed when there is significant transmission reduction control. Surprisingly, when there is no transmission reduction control, testing/isolation in the exposed should be optimal. Testing/isolation in the exposed could seemingly replace the transmission reduction control to yield a comparable result to that when the transmission reduction control is being implemented.

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