12,123 research outputs found
Sparse Wide-Area Control of Power Systems using Data-driven Reinforcement Learning
In this paper we present an online wide-area oscillation damping control
(WAC) design for uncertain models of power systems using ideas from
reinforcement learning. We assume that the exact small-signal model of the
power system at the onset of a contingency is not known to the operator and use
the nominal model and online measurements of the generator states and control
inputs to rapidly converge to a state-feedback controller that minimizes a
given quadratic energy cost. However, unlike conventional linear quadratic
regulators (LQR), we intend our controller to be sparse, so its implementation
reduces the communication costs. We, therefore, employ the gradient support
pursuit (GraSP) optimization algorithm to impose sparsity constraints on the
control gain matrix during learning. The sparse controller is thereafter
implemented using distributed communication. Using the IEEE 39-bus power system
model with 1149 unknown parameters, it is demonstrated that the proposed
learning method provides reliable LQR performance while the controller matched
to the nominal model becomes unstable for severely uncertain systems.Comment: Submitted to IEEE ACC 2019. 8 pages, 4 figure
A novel technique for load frequency control of multi-area power systems
In this paper, an adaptive type-2 fuzzy controller is proposed to control the load frequency of a two-area power system based on descending gradient training and error back-propagation. The dynamics of the system are completely uncertain. The multilayer perceptron (MLP) artificial neural network structure is used to extract Jacobian and estimate the system model, and then, the estimated model is applied to the controller, online. A proportional–derivative (PD) controller is added to the type-2 fuzzy controller, which increases the stability and robustness of the system against disturbances. The adaptation, being real-time and independency of the system parameters are new features of the proposed controller. Carrying out simulations on New England 39-bus power system, the performance of the proposed controller is compared with the conventional PI, PID and internal model control based on PID (IMC-PID) controllers. Simulation results indicate that our proposed controller method outperforms the conventional controllers in terms of transient response and stability
Adaptive Backstepping Controller Design for Stochastic Jump Systems
In this technical note, we improve the results in a paper by Shi et al., in which problems of stochastic stability and sliding mode control for a class of linear continuous-time systems with stochastic jumps were considered. However, the system considered is switching stochastically between different subsystems, the dynamics of the jump system can not stay on each sliding surface of subsystems forever, therefore, it is difficult to determine whether the closed-loop system is stochastically stable. In this technical note, the backstepping techniques are adopted to overcome the problem in a paper by Shi et al.. The resulting closed-loop system is bounded in probability. It has been shown that the adaptive control problem for the Markovian jump systems is solvable if a set of coupled linear matrix inequalities (LMIs) have solutions. A numerical example is given to show the potential of the proposed techniques
Mathematical control of complex systems
Copyright © 2013 ZidongWang et al.This is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
Effect of reconstituted method on shear strength properties of peat
Peat is an organic soil contains more than 75% organic content. Shear strength of the
soil is one of the most important parameters in engineering design, especially during
the pre-construction and post-construction periods, since used to evaluate the
foundation and slope stability of soil. Peat normally known as a soil that has very
low shear strength and to determine and understand the shear strength of the peat is
difficult in geotechnical engineering because of a few factors such as the origin of
the soil, water content, organic matter and the degree of humification. The aim of this
study was to determine the effective undrained shear strength properties of
reconstituted peat. All the reconstituted peat samples were of the size that passing
opening sieve 0.425mm, 1.000mm, 2.360mm and 3.350mm and were preconsolidated
at pressures of 50 kPa, 80 kPa and 100 kPa. The relationship deviator
stress- strain, σdmax and excess pore water pressure, Δu, shows that in both of
reconstituted and undisturbed peat gradually increased when confining pressure, σ’
and pre- consolidation pressure, σc increased. As a conclusion, the undrained shear
strength properties result obtained shows that the RS3.350 has higher strength than
RS0.425, RS1.000 and RS2.360. However, the entire reconstituted peat sample
shows the increment value of the shear strength with the increment of peat size and
pre- consolidation pressure. For comparison purposes, the undrained shear strength
properties result obtained shows that the reconstituted peat has higher strength than
undisturbed peat. The factors that contributed to the higher shear strength properties
in this study are segregation of peat size, pre- consolidation pressure, initial void
ratio and also the physical properties such as initial water content, fiber content and
liquid limit
Active actuator fault-tolerant control of a wind turbine benchmark model
This paper describes the design of an active fault-tolerant control scheme that is applied to the actuator of a
wind turbine benchmark. The methodology is based on adaptive filters obtained via the nonlinear geometric
approach, which allows to obtain interesting decoupling property with respect to uncertainty affecting the
wind turbine system. The controller accommodation scheme exploits the on-line estimate of the actuator
fault signal generated by the adaptive filters. The nonlinearity of the wind turbine model is described by the
mapping to the power conversion ratio from tip-speed ratio and blade pitch angles. This mapping represents
the aerodynamic uncertainty, and usually is not known in analytical form, but in general represented by
approximated two-dimensional maps (i.e. look-up tables). Therefore, this paper suggests a scheme to
estimate this power conversion ratio in an analytical form by means of a two-dimensional polynomial, which
is subsequently used for designing the active fault-tolerant control scheme. The wind turbine power generating
unit of a grid is considered as a benchmark to show the design procedure, including the aspects of
the nonlinear disturbance decoupling method, as well as the viability of the proposed approach. Extensive
simulations of the benchmark process are practical tools for assessing experimentally the features of the
developed actuator fault-tolerant control scheme, in the presence of modelling and measurement errors.
Comparisons with different fault-tolerant schemes serve to highlight the advantages and drawbacks of the
proposed methodology
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