Robust control of a class of uncertain systems that have disturbances and uncertainties not satisfying “matching” condition is investigated in this paper via a disturbance observer based control (DOBC) approach. In the context of this paper, “matched” disturbances/uncertainties stand for the disturbances/uncertainties entering the system through the same channels as control inputs. By properly designing a disturbance compensation gain, a novel composite controller is proposed to counteract the “mismatched” lumped disturbances from the output channels. The proposed method significantly extends the applicability of the {DOBC} methods. Rigorous stability analysis of the closed-loop system with the proposed method is established under mild assumptions. The proposed method is applied to a nonlinear {MAGnetic} {LEViation} (MAGLEV) suspension system. Simulation shows that compared to the widely used integral control method, the proposed method provides significantly improved disturbance rejection and robustness against load variation
Abstract-The output voltage regulation problem of a PWMbased DC-DC buck converter under various sources of uncertainties and disturbances is investigated in this paper via an optimized active disturbance rejection control (ADRC) approach. Aiming to practical implementation, a new reduced-order generalized proportional integral (GPI) observer is first designed to estimate the lumped (possibly time-varying) disturbances within the DC-DC circuit. By integrating the disturbance estimation information raised by the reduced-order GPI observer (GPIO) into the output prediction, an optimized ADRC method is developed to achieve optimized tracking performance even in the presence of disturbances and uncertainties. It is shown that the proposed controller will guarantee the rigorous stability of closed-loop system, for any bounded uncertainties of the circuit, by appropriately choosing the observer gains and the bandwidth factor. Experimental results illustrate that the proposed control solution is characterised by improved robustness performance against various disturbances and uncertainties compared to traditional ADRC and integral MPC approaches.
(Review Version)For any given system the number and location of sensors can affect the closed-loop performance as well as the reliability of the system. Hence one problem in control system design is the selection of the sensors in some optimum sense that considers both the system performance and reliability. Although some methods have been proposed that deal with some of the aforementioned aspects, in this work, a design framework dealing with both control and reliability aspects is presented. The proposed framework is able to identify the best sensor set for which optimum performance is achieved even under single or multiple sensor failures with minimum sensor redundancy. The proposed systematic framework combines linear quadratic gaussian control, fault tolerant control and multiobjective optimisation. The efficacy of the proposed framework is shown via appropriate simulations on an electro-magnetic suspension system.
Abstract-This paper demonstrates the enhancement of inter-area mode damping by multiple flexible ac transmission systems (FACTS) devices. Power system damping control design is formulated as an output disturbance rejection problem. A decentralized damping control design based on the mixed-sensitivity formulation in the linear matrix inequality (LMI) framework is carried out. A systematic procedure for selecting the weights for shaping the open loop plant for control design is suggested. A 16-machine, five-area study system reinforced with a controllable series capacitor (CSC), a static var compensator (SVC), and a controllable phase shifter (CPS) at different locations is considered. The controllers designed for these devices are found to effectively damp out inter-area oscillations. The damping performance of the controllers is examined in the frequency and time domains for various operating scenarios. The controllers are found to be robust in the face of varying power-flow patterns, nature of loads, tie-line strengths, and system nonlinearities, including device saturations.
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