A key difficulty of the explicit approach to self-tuning control—both theoretically and computationally—is the need to solve a polynomial identity to generate the required controller coefficients. For systems with uncorrelated output noise, however, the identity has a simple solution, and in this paper the implications of this phenomenon are discussed in relation to self-tuning regulation. A suitable explicit algorithm is introduced, and it is shown that, under certain conditions, global stability and system identifiability can be established without recourse to sophisticated estimator management techniques
Convergence properties of a self-tuning regulator incorporating an input mean-square constraint are ...
A simple parameter adaptive controller design methodology is introduced in which steady-state servo ...
Convergence properties of a self-tuning regulator incorporating an input mean-square constraint are ...
A key difficulty of the explicit approach to self-tuning control—both theoretically and computationa...
The explicit self-tuning control of linear systems with constant but unknown parameters is analysed....
The explicit self-tuning control of linear systems with constant but unknown parameters is analysed....
This paper solves the exact pole assignment problem for the single-input stochastic systems with unk...
The behaviour of n-input n-output systems with white noise is considered. An adaptive controller tha...
Abstract—The key issue for adaptive pole-placement control of linear time-invariant systems is the p...
The key issue for adaptive pole-placement control of linear time-invariant systems is the possible s...
In a major breakthrough, Guo and Chen [1] have recently shown how to establish the self--optimality ...
A new self-tuning implicit pole-assignment algorithm is presented which, through the use of a pole c...
This paper solves the exact pole assignment problem for the single-input stochastic systems with unk...
Parameter estimation of linear Discrete-time systems by linear programming using two error criteria,...
A computationally efficient pole-zero placement algorithm for explicit adaptive control of discrete-...
Convergence properties of a self-tuning regulator incorporating an input mean-square constraint are ...
A simple parameter adaptive controller design methodology is introduced in which steady-state servo ...
Convergence properties of a self-tuning regulator incorporating an input mean-square constraint are ...
A key difficulty of the explicit approach to self-tuning control—both theoretically and computationa...
The explicit self-tuning control of linear systems with constant but unknown parameters is analysed....
The explicit self-tuning control of linear systems with constant but unknown parameters is analysed....
This paper solves the exact pole assignment problem for the single-input stochastic systems with unk...
The behaviour of n-input n-output systems with white noise is considered. An adaptive controller tha...
Abstract—The key issue for adaptive pole-placement control of linear time-invariant systems is the p...
The key issue for adaptive pole-placement control of linear time-invariant systems is the possible s...
In a major breakthrough, Guo and Chen [1] have recently shown how to establish the self--optimality ...
A new self-tuning implicit pole-assignment algorithm is presented which, through the use of a pole c...
This paper solves the exact pole assignment problem for the single-input stochastic systems with unk...
Parameter estimation of linear Discrete-time systems by linear programming using two error criteria,...
A computationally efficient pole-zero placement algorithm for explicit adaptive control of discrete-...
Convergence properties of a self-tuning regulator incorporating an input mean-square constraint are ...
A simple parameter adaptive controller design methodology is introduced in which steady-state servo ...
Convergence properties of a self-tuning regulator incorporating an input mean-square constraint are ...