The paper deals with the robust synthesis and analysis of control systems with a hybrid structure which consists of a sampled continuous process and a discrete control algorithm. A method for the design of digital con...
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The paper deals with the robust synthesis and analysis of control systems with a hybrid structure which consists of a sampled continuous process and a discrete control algorithm. A method for the design of digital controllers for processes with uncertain physical plant parameters is presented. The Robust Pole Region Assignment and the Algebraic Approach to the Output Feedback Based Pole Placement in the discrete domain are applied. The paper proposes also a new robust stability/performance criterion for hybrid systems with interval parametric uncertainties. An application example is included.
The paper describes the development and application of several techniques for knowledge extraction from trained ANN models, such as the identification of redundant inputs and hidden neurons, derivation of causal relat...
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The paper describes the development and application of several techniques for knowledge extraction from trained ANN models, such as the identification of redundant inputs and hidden neurons, derivation of causal relationships between inputs and outputs, and analysis of the hidden neuron behavior in classification ANNs. An example of the application of these techniques is given of the faulty LED display benchmark. References of the application of these techniques are given of diverse large scale ANN models of industrial processes.
A procedure for the postoptimal analysis of dynamic positioning control system of floating vessels is proposed. The control system design is based on the optimal constrained covariance control (OC 3 ). Using the OC 3 ...
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A procedure for the postoptimal analysis of dynamic positioning control system of floating vessels is proposed. The control system design is based on the optimal constrained covariance control (OC 3 ). Using the OC 3 technique, the disadvantages of the classical LQG optimal control technique are avoided. The presented numerical example illustrates the properties of the new approach.
Predictive control algorithms are promising also in the case of nonlinear systems. Two versions of extended horizon predictive control algorithms are given here for the nonlinear simple Hammerstein model. A quadratic ...
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Predictive control algorithms are promising also in the case of nonlinear systems. Two versions of extended horizon predictive control algorithms are given here for the nonlinear simple Hammerstein model. A quadratic cost function is minimized, which considers the quadratic deviation of the reference signal and the output signal predicted in a future point and also the squares of the control increments. The system model is transformed to a predictive incremental form. Two versions of suboptimal extended horizon control algorithms are given with different assumptions for the control signal during the control horizon. Robustness properties of these algorithms are considered in case of plant-model mismatch through some simulation examples.
Autonomous systems of electric power supply consisting of one common primary source of electric power supply and a set of multiple modular switched-controlled secondary sources of electric power supply (DC-to-DC power...
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Autonomous systems of electric power supply consisting of one common primary source of electric power supply and a set of multiple modular switched-controlled secondary sources of electric power supply (DC-to-DC power converters) are considered. The problem of the stabilization of the voltages transformed by the multiple modular switched-controlled secondary sources of electric supply is formulated and solved in conventional and dynamic local sliding surfaces. The robust decoupled linear desired behavior of the stabilization errors of the transformed voltages is guaranteed in local sliding modes. The desired quality of the voltage stabilization is achieved in dynamic sliding surfaces without measurement or estimation of disturbances (load currents).
A new method for nonlinear model predictive control with guaranteed stability is proposed as an extension to the stability constrained model predictive control (SCMPC) for linear time-invariant systems. The method app...
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ISBN:
(纸本)0780341872
A new method for nonlinear model predictive control with guaranteed stability is proposed as an extension to the stability constrained model predictive control (SCMPC) for linear time-invariant systems. The method applies to a class of nonlinear systems that can be transformed to a controllable companion form and depends on the existence of a nonlinear deadbeat control (although this is not necessarily the control that is used). Asymptotic stability is proved for the case when all state variables are measurable.
A third-order proportional process model with parameter uncertainty is controlled by different simple controllers. First the robustness of four different PID-control designs is investigated. Then internal model contro...
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A third-order proportional process model with parameter uncertainty is controlled by different simple controllers. First the robustness of four different PID-control designs is investigated. Then internal model control (IMC) is designed in the time domain for the exact process model and for its approximating model with a first-order lag and a delay time. Finally, the PID-control of the nominal model is extended by an IMC-like feedback, which makes the control especially robust.
This article presents an extension to stability-constrained model predictive control (SCMPC) incorporating state estimation. It is proved that asymptotic stability of the closed loop system is guaranteed for SCMPC whe...
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This article presents an extension to stability-constrained model predictive control (SCMPC) incorporating state estimation. It is proved that asymptotic stability of the closed loop system is guaranteed for SCMPC when a stable state estimator is used rather than direct measurement of the full state variables. The results are illustrated with experimental results from a real-time implementation of SCMPC with state estimation for control of a plasma enhanced chemical vapor deposition (PECVD) system.
The passivity property of dissipative mechanical structures has long been exploited in designing passive controllers that provide robust stability even in the presence of unmodeled dynamics of the system. For an input...
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The passivity property of dissipative mechanical structures has long been exploited in designing passive controllers that provide robust stability even in the presence of unmodeled dynamics of the system. For an input/output map of a flexible structure to be passive, collocation of the actuators and sensors is required and also the sensors should measure the velocity of the system. The so-called smart structures frequently have more sensors than actuators. Therefore, the passive controller can at best utilize only a subset of the sensors. In this paper we consider the design of a squaring down matrix which would render a system passive subject to some additional performance considerations. The problem of obtaining the synthesized passive output is cast as a set of linear matrix inequalities (LMIs) which can be efficiently solved by the LMI Toolbox in Matlab. We apply this procedure with the assumption that the sensors provide both displacement and velocity information which is generally not true. We show that the passive controllers can be implemented without the use of velocity information. By using synthesized passive outputs in addition to naturally occurring passive outputs, we obtain better system performance. We present experimental results involving a single flexible beam with torque input and hub angular position and strain gage outputs.
A new matrix rule-based model of discrete-part discrete event systems is given that, together with the well-known Petri net marking transition equation, yields a complete matrix-based dynamical description of these sy...
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A new matrix rule-based model of discrete-part discrete event systems is given that, together with the well-known Petri net marking transition equation, yields a complete matrix-based dynamical description of these systems. In this application to deadlock analysis, the exact relations between circular blockings and deadlocks are given for a large class of reentrant flow lines. Explicit matrix equations are given for online dynamic deadlock analysis in terms of circular blockings, and certain 'critical siphons' and 'critical subsystems'. This allows efficient dispatching with deadlock avoidance using a generalized kanban scheme. For the class of flow lines considered, the existence of matrix formulae shows that deadlock analysis is not NP-complete, but of polynomial complexity.
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