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Disturbance observer-based anti-disturbance control for a class of stochastic systems
2015 34th Chinese Control Conference (CCC), 2015This paper proposes a disturbance observer-based anti-disturbance control strategy for a class of stochastic systems subject to two kinds of disturbances. One represents the stochastic disturbance with partially-known information. The other is an independent Wiener process.
Wei Xinjiang +3 more
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Dead time and processes with stochastic disturbances
15th Annual Conference of IEEE Industrial Electronics Society, 2003To control processes with unknown or variable dead time, it is important to estimate the dead time in real time. In the present work, adaptive control systems with reference models, where the estimation of the dead time in the batch processing model is considered, are studied.
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Stability analysis of TâS fuzzy coupled oscillator systems influenced by stochastic disturbance
Neural computing & applications (Print), 2020Jiayi Liu +5 more
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Stability of Structures under Stochastic Disturbances
1971This paper examines certain problems in the stability of elastic structures when the external loads fluctuate in a stochastic manner. The study is important for two reasons. First, there exist many examples of loads such as those generated by jet and rocket engines, earthquakes, wind gusts, etc., that cannot be adequately described by deterministic ...
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On the convergence of tracking differentiator with multiple stochastic disturbances
Science China Information Sciences, 2023Zehao Wu +3 more
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Minimum Variance Controllers for Stochastic Disturbances
1981In the design of minimum variance controllers the variance of the controlled variable $${\mathop{\rm var}} \left[ {y\left( k \right)} \right] = E\left\{ {{y^2}\left( k \right)} \right\}$$ is minimized. This criterion was used in [12.4] by assuming a noise filter given by (12.2.31) but with C(z â1) = A(z â1). The manipulated variable u(k) was not
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Parameter-optimized Controllers for Stochastic Disturbances
1981The parameter-optimized control algorithms given in chapter 5 can be modified to include stochastic disturbance signals n(k) by using the quadratic performance criterion $$S_{eu}^2 = \sum\limits_{k = 1}^M {\left[ {{e^2}\left( k \right) + rK_p^2\Delta {u^2}\left( k \right)} \right]} $$ (13.1) if the disturbance signals are known.
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Environment Systems and Decisions, 2018
H. Klammler, P. Rao, K. Hatfield
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H. Klammler, P. Rao, K. Hatfield
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