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This article explores a nonlinear, adaptive controller aimed at increasing the stability margin of a direct-current (dc), small-scale, electrical network containing an unknown constant power load (CPL). Due to its negative incremental impedance, this load reduces the effective damping of the network, which may lead to voltage oscillations and even to voltage collapse. To overcome this drawback, we consider the incorporation of a controlled dc–dc power converter in parallel with the CPL. The design of the control law for the converter is particularly challenging due to the existence of unmeasured states and unknown parameters. We propose a standard input–output linearization stage, to which a suitably tailored adaptive observer is added. The good performance of the controller is validated through experiments on a small-scale network. [ABSTRACT FROM AUTHOR]

One of the most challenging problems in AC drives applications is the design of a simple plug‐in adaptation scheme to estimate the unknown rotor resistance and load torque for the industry‐standard indirect field oriented control. In this paper we give the first globally convergent solution to this problem for torque control of current‐fed induction motors that does not rely on any excitation assumption. Some results on speed regulation are also presented. [ABSTRACT FROM AUTHOR]

Summary: In this paper, we propose the first solution to the long‐standing problem of designing a globally convergent direct adaptive pole‐placement controller for linear, time‐invariant discrete‐time systems with arbitrary zeros that does not rely on persistency of excitation assumptions. As is well known, the main difficulty of this design is that it involves the estimation of parameters that enter nonlinearly in the regression model. This problem can be overcome introducing an overparameterized representation of the system, which imposes very strict persistency of excitation conditions to prove the parameter convergence. The latter is avoided here using a new version of the dynamic regressor extension and mixing parameter estimator recently proposed in the literature. The main feature of this estimator is that it generates, out of an m‐dimensional vector regression, m scalar regression models. This property allows us to estimate only the controller parameters of interest for the adaptive implementation, whose convergence is ensured under assumptions that are strictly weaker than the classical persistency of excitation requirement. Simulation results that illustrate the performance of the proposed scheme are also presented. [ABSTRACT FROM AUTHOR]

Abstract The problem of robust output regulation for MIMO linear time-invariant systems with harmonic exogenous inputs and parameter uncertainties is addressed. We discuss two methods to handle stability in the presence of plant uncertainties, that take full advantage of all controls and all available measurements. One method, appeals to a general notion of "robust" minimum-phase. The other method, that addresses the case of unstructured uncertainties, reposes on the solution of appropriate LMIs. In both cases, the critical issue is to show how adaptive tuning of the internal model can be implemented, so as to obtain a controller that guarantees asymptotic convergence of the regulated output to zero. A numerical example of vessel motion control is given to illustrate one of the proposed approaches. [ABSTRACT FROM AUTHOR]

Abstract In this paper we address the problem of state observation for sensorless control of magnetic levitation systems, that is, the regulation of the position of a levitated object measuring only the voltage and current of the electrical supply. Instrumental for the development of the theory is the use of parameter estimation-based observers, which combined with the dynamic regressor extension and mixing parameter estimation technique, allow the reconstruction of the magnetic flux. With the knowledge of the latter it is shown that the mechanical coordinates can be estimated with suitably tailored nonlinear observers. Replacing the observed states, in a certainty equivalent manner, with a full-state feedback stabilising law completes the sensorless controller design. In the interest of brevity the result is presented only for a two-degree-of-freedom system but the approach is applicable also for the more familiar case of one-degree-of-freedom. Simulation results are used to illustrate the transient performance and robustness of the proposed scheme. [ABSTRACT FROM AUTHOR]