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When multiple parameters jump simultaneously, a multiple models adaptive decoupling controller using dimension-by-dimension technology is presented to solve the problems such as too many models, long computing time and so on. To find the optimal parameter, it adopts one-dimension optimization method in series instead of multiple-dimension optimization method in parallel. At any time only one parameter...
Based on a new concept: virtual equivalent system, this paper presents a criterion on the stability and convergence of multivariable stochastic self-tuning control systems. With the aid of presented criterion we can not only analyze and evaluate the performances of various stochastic self-tuning control systems, but also get some guidelines for designing new stochastic self-tuning control systems...
This paper presents an adaptive fuzzy-neural controller for multivariable system which incorporates the advantage of fuzzy logic and neural network. Inverted pendulum is well known as a multivariable and nonlinear system. And it is very difficult to design and realize a single stage fuzzy controller for the problem of multivariable system as inverted pendulum. After the description of the research...
In this paper, an adaptive fuzzy control approach for complex task involving robot/environment interaction is presented. The approach implementation is based on fuzzy logic controller (FLC) design and optimization methodology which operates in two stages. In the first stage, the FLC parameters are trained and optimized offline using a method based on Solis' and Wetts' algorithm so that the constraints...
This paper develops a representation of multi-model based controllers using graph theory and artificial intelligence techniques. These techniques are neural networks and genetic algorithms. Thus, graph theory is used to describe in a formal and concise way the switching mechanism between the various plant parameterizations of the switched system. Moreover, the interpretation of multimodel controllers...
The paper deals with continuous-time adaptive control of a nonlinear process. A nonlinear model of the process is approximated by a continuous-time external linear model. The parameters of the CT external linear model are estimated via parameters of a corresponding delta model. The control system configuration with two feedback controllers is considered. The controller design is based on the polynomial...
The paper deals with the control of multivariable systems with the same number of inputs as the number of outputs using a decentralized approach. The controlled system is divided into single input-single output (SISO) subsystems and adaptive controllers are used to control each subsystem. This paper is focused to the usage of self-tuning controllers (STC) which are a subset of adaptive controllers...
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