The advanced control system for control of nonlinear, slowly time variant and delayed processes is described in the paper. The proposed control system performs automatic tuning of fuzzy gain-scheduling controller para...
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The advanced control system for control of nonlinear, slowly time variant and delayed processes is described in the paper. The proposed control system performs automatic tuning of fuzzy gain-scheduling controller parameters. The parameters are tuned according to a non-linear process model, which is identified by performing simple experiments on the actual process. The proposed control system (ASPECT) is implemented as a software product and currently runs on several PLC platforms.
Nonlinear passivity-based control (PBC) algorithms for power converters have proven to be an interesting alternative for other, mostly linear, control techniques. The control objective is usually achieved through an e...
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Nonlinear passivity-based control (PBC) algorithms for power converters have proven to be an interesting alternative for other, mostly linear, control techniques. The control objective is usually achieved through an energy reshaping process and by injecting damping to modify the dissipation structure of the system. However, a key question that arises during the implementation of the controller is how to tune the various parameters. From previous work we know that a PBC controller forces the closed-loop dynamics to behave as if there are artificial resistors connected to the real circuit elements. This has led to conservative tuning rules stemming from characteristic impedance matching conditions. In this paper an alternative solution is provided that uses the classical Brayton-Moser equations (1964). The criteria derived from these equations result in fairly sharp and less conservative tuning rules to guarantee stability and non-oscillatory responses. Both criteria are compared and tested using the elementary single-switch boost converter.
This paper demonstrates the use of noncausal operators in iterative learning control (ILC). First, it is shown that for a particular class of plants (having unstable zeros), perfect tracking can only be achieved by us...
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This paper demonstrates the use of noncausal operators in iterative learning control (ILC). First, it is shown that for a particular class of plants (having unstable zeros), perfect tracking can only be achieved by using noncausal operators. Then it is shown that with any converging algorithm (both causal and noncausal) we can associate a particular feedback controller. For causal algorithms this controller can be shown to be internally stabilizing. In the noncausal case, however, the associated controller is found to be generally destabilizing which implies that the existing notion of an equivalent controller for causal ILC does not extend to noncausal ILC.
Skillful motor control of human is achieved by the appropriate motor commands generating from the central nerve system. Internal model in the cerebellum may have great contribution for realizing accurate motor control...
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In this paper, the problems of isomorphic decomposition and controllability of a class of nonlinear systems possessing symmetries, on the basis of quotient systems, is studied. The isomorphic decomposition formations ...
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In this paper, the problems of isomorphic decomposition and controllability of a class of nonlinear systems possessing symmetries, on the basis of quotient systems, is studied. The isomorphic decomposition formations of these systems are derived. Finally, it is shown that controllability of the original systems can be determined by that of the subsystems, which are obtained through isomorphic decomposition. The corresponding sufficient and necessary conditions are given. Two new theoretical results have been proved.
In this paper, the problem of system decomposition of complex linear dynamical systems, by exploiting the similarity property, is studied. System decompositions were sought in terms of similarity hierarchical structur...
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In this paper, the problem of system decomposition of complex linear dynamical systems, by exploiting the similarity property, is studied. System decompositions were sought in terms of similarity hierarchical structures. Three new theoretical results were proved. A method for constructing the transformation has been derived. The conditions for such decomposition of complex linear systems are given.
Skillful motor control of human is achieved by the appropriate motor commands generating from the central nerve system. Internal model in the cerebellum may have great contribution for realizing accurate motor control...
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Skillful motor control of human is achieved by the appropriate motor commands generating from the central nerve system. Internal model in the cerebellum may have great contribution for realizing accurate motor control. In this paper, the model for human motor control on manual tracking to moving visual target was constructed based on the experimental data of the visual tracking test for three groups; normal healthy adults, patients with cerebellar ataxia and patients with Parkinson disease. Relationship between the model parameters and movement disorders were investigated. Furthermore, the compensation method for improving the motor function of patients were also considered.
The paper compares a new population based method called PLA (population learning algorithm) with the evolutionary computation approach. The paper introduces a concept of the population learning algorithm, compares its...
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