A generic two degree of freedom controller introduced for linear plants is extended for nonlinear processes. The nonlinear controller consists of two parts: the first depending on the design parameters and the invaria...
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A generic two degree of freedom controller introduced for linear plants is extended for nonlinear processes. The nonlinear controller consists of two parts: the first depending on the design parameters and the invariant part of the process, the second only on the model of the plant. A simple iterative controller refinement scheme is constructed. The efficiency of this scheme is presented by simulation examples.
The authors created a Web-based integrated education support system that unified the data in the administrative system and the education system in a university. The purpose of the system was to make the administrative...
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Limits of optimality in a generic two-degree of freedom control system is investigated. New relationships are introduced for the decomposition to identification and optimization errors in inverse stable and inverse un...
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(纸本)0889865027
Limits of optimality in a generic two-degree of freedom control system is investigated. New relationships are introduced for the decomposition to identification and optimization errors in inverse stable and inverse unstable processes. In the inverse stable case these errors has a random, in the inverse unstable case systematic and random parts.
Some new structural properties of the classical SF/SFO schemes are analyzed by TFR equivalent forms of LTI systems. The location of poles and zeros of the closed-loop system can only be partly designed by SFO. A two-s...
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Some new structural properties of the classical SF/SFO schemes are analyzed by TFR equivalent forms of LTI systems. The location of poles and zeros of the closed-loop system can only be partly designed by SFO. A two-step procedure is suggested to reach full zero/pole placement for SISO systems applying a TDOF scheme.
Error properties of a generic two-degree of freedom control system is investigated. It is shown that there is a considerable difference between inverse stable and inverse unstable processes. New direct relationships a...
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Error properties of a generic two-degree of freedom control system is investigated. It is shown that there is a considerable difference between inverse stable and inverse unstable processes. New direct relationships are introduced for identification and optimization errors. For inverse unstable case these errors consist of systematic and random parts. The new results help to construct new algorithms for simultaneous robust identification and control
It is shown that for open-loop stable plants the task of an MPC can be solved by identifying the plant model only instead of the redundant prediction model. Interesting structural considerations can be derived from co...
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It is shown that for open-loop stable plants the task of an MPC can be solved by identifying the plant model only instead of the redundant prediction model. Interesting structural considerations can be derived from comparison of the topologies and structural forms of regulators obtained by pole-placement design, the GTDOF scheme and the MPC . A new simple method is also introduced for adaptive and combined iterative identification and control for time-delay plants.
Some shortcomings of current statistical model for maneuvering target are discussed. The applicable bound of modified Rayleigh distribution was derived. Based on the result, a new current statistical model description...
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Some shortcomings of current statistical model for maneuvering target are discussed. The applicable bound of modified Rayleigh distribution was derived. Based on the result, a new current statistical model description was proposed. computer simulation by MATLAB shows that the tracking accuracy of the new method is preferred to the old one.
We will argue in this paper that the nature and magnitude of model uncertainty dictate the appropriateness of the control system design methodology. To obtain these arguments, we will pursue optimality of the control ...
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We will argue in this paper that the nature and magnitude of model uncertainty dictate the appropriateness of the control system design methodology. To obtain these arguments, we will pursue optimality of the control ...
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We will argue in this paper that the nature and magnitude of model uncertainty dictate the appropriateness of the control system design methodology. To obtain these arguments, we will pursue optimality of the control system design. Note this is a philosophical paper , in which we present our arguments in qualitative terms . We will identify the circumstances under which several control system design methodologies are appropriate. The design methodologies that will be considered are (1) optimal control and optimal feedback design, (2) model predictive control (receding horizon control), (3) active and passive adaptive control and (4) robust control. Robust control strategies are conservative and limit the possible improvements that can be obtained over say classical PID control. However, it will turn out that for certain types of control problems, improvements in performance are indeed limited. Roughly speaking, the area where we may expect (significant) improvement from advanced (optimal) control system design is very much limited by the uncertainty of the systems model. Miracles are not to be expected from advanced control. What can be expected is reflected in an active adaptive optimal control scheme introduced and discussed in this paper.
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