“…a proof. see Ilchmann and Owens [7]. This shows that condition (6) is an extension of the well-known minimumphase dehnition for single-input, single-output systems given usually in the frequency domain.…”
mentioning
confidence: 79%
“…), i(') e I2Q, o). Therefore (see, e.g., Ilchmann and Owens [7]), lim,--y(l) : lin1,-z(r) : 0. Since the system becomes constant after finite time, asymptotic decay of r(r) implies exponential decay, which proves part (i).…”
mentioning
confidence: 90%
“…Although this inequality has been implicitly used in earlier works [8,19], or in a more general framework, including nonlinear disturbances [7] and Zo-functions [5] forp > 1, we would like to give a straightforward proof in the present simple situation. The inequality is a basic tool for the proof of stability of the universal adaptive stabilizer presented in section 4.…”
“…a proof. see Ilchmann and Owens [7]. This shows that condition (6) is an extension of the well-known minimumphase dehnition for single-input, single-output systems given usually in the frequency domain.…”
mentioning
confidence: 79%
“…), i(') e I2Q, o). Therefore (see, e.g., Ilchmann and Owens [7]), lim,--y(l) : lin1,-z(r) : 0. Since the system becomes constant after finite time, asymptotic decay of r(r) implies exponential decay, which proves part (i).…”
mentioning
confidence: 90%
“…Although this inequality has been implicitly used in earlier works [8,19], or in a more general framework, including nonlinear disturbances [7] and Zo-functions [5] forp > 1, we would like to give a straightforward proof in the present simple situation. The inequality is a basic tool for the proof of stability of the universal adaptive stabilizer presented in section 4.…”
“…Finally, from (13) and the fact that w i ∈ L ∞ and w L ∞ ∈ , it follows that f i ∈ L ∞ . Finally, from (13) and the fact that w i ∈ L ∞ and w L ∞ ∈ , it follows that f i ∈ L ∞ .…”
Section: Appendix a (Proof Of Lemma 1)mentioning
confidence: 93%
“…These assumptions were then proved to be very restrictive and unnecessary for the convergence and stability proofs of adaptive control systems. Also, some researches which relaxed one or several of the aforementioned assumptions have been presented, [3,5,7,8,[10][11][12][13]. Adaptive control algorithms which ensured the robustness of the systems in the presence of disturbances have been designed [2].…”
This paper presents an indirect adaptive control scheme for nominally stabilizable non-necessarily inversely stable continuous-time systems with unmodelled dynamics. The control objective is the adaptive stabilization of the closed-loop system with the achievement of a bounded tracking-error between the system output and a reference signal given by a stable filter. The adaptive control scheme includes several estimation algorithms and a supervisor which selects the appropriate estimator at every certain time and keeping it operating for at least a minimum period of residence time. This selection is based on a performance criterion related to a measure of the estimation errors obtained with each estimator. In this way, the performance of the output signal is improved with regard to the performance achieved with a unique estimation algorithm. All the estimators are either of the least-squares type or gradient type. However, any well-posed estimation algorithm is potentially valid for application. These estimators include relative dead-zones for robustness purposes and parameter 'a posteriori' modifications to ensure the controllability of the estimated models of the plant, which is crucial for proving the stabilizability of the plant via adaptive pole-placement designs.
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