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In this paper, sliding mode observers are designed in order to estimate actuator and sensor faults for linear fractional-order systems. The system is represented by a commensurate fractional-order state space model, in the presence of unknown sensor and actuator faults. The convergence of the designed observers is established. A numerical example is given to illustrate the effectiveness of the proposed...
In this paper, a new method with impulse spectrum is presented as a more general way for vibration control of the robotic arm of flexible multiple links. An impulse spectrum is directly responsible for basic processions. The multiple ODE of the arm is analyzed as an LTI system fit for superposition due to its dynamically relative constant. The study shows that the impulse spectrum proposed to suppress...
The method is proposed for state observer structural optimization, which is based on the procedure of similarity transformation for control object model. The transforming matrix in this case is formed by the variation of singular numbers of controllability and observability gramians. The method allows us to form the structure of state observer with optimal balance of controllability and observability,...
We propose an effective and efficient local decolorization method in this paper. It is an extension of the global decolorization method [6] which robustly reproduces visual appearance of a color image in the grayscale output. The improvement of the local extension is the effective preservation of the local color contrast which may diminish in the global method. Meanwhile the proposed local extension...
The FEAST algorithm is a subspace iteration method that uses a spectral projector as a rational filter in order to efficiently solve interior eigenvalue problems in parallel. Although the solutions from the FEAST algorithm converge rapidly in many cases, convergence can be slow in situations where the eigenvalues of a matrix are densely populated near the edges of the search interval of interest,...
In this paper, the control problem for a class of discrete-time Markovian jump linear system subject to totally and partially known transition probabilities with unknown Markov chain is investigated. The uncertainties are assumed norm-bounded. To solve this problem, an underlying Markovian jump linear system is reformulated as deterministic system associated with an indicator function. The solution...
This paper proposes a complete parametric approach for eigenstructure assignment in second-order system Mq̈+Dq̇+kq=cu using the displacement-plus-acceleration feedback controller. The expressions of closed-loop eigenvector matrix and feedback gains are in direct closed forms in terms of the closed-loop eigenvalues and a group parameter vectors, which represents the degree of design freedom. The main...
The tracking/rejection of periodic disturbances in linear systems is achievable via internal model principle-based techniques, such as repetitive control. However, when the frequency of the signal to track/reject is uncertain or time-varying, the performance of these controllers decays dramatically. This article discusses the basics of Model Reference Adaptive Control with Minimal Controller Synthesis,...
In this paper an useful application of a new right H-inverse to stabilization of perfect control for LTI MIMO discrete-time systems in state-space is shown. Following the recently introduced H-inverse, its intriguing property giving the stable perfect control is indicated here. Now, the SVD-based H-inverse with parameter and polynomial degrees of freedom clearly outperforms the classical minimum-norm...
This paper presents a new variable gain robust state observer for a class of uncertain linear systems. The robust state observer proposed in this paper is composed of fixed and variable gain matrices. In this paper, LMI-based sufficient conditions for the existence of the proposed robust state observer are given. Finally, a simple illustrative example is included.
We propose new asymptotic notions that capture the robustness of a large interconnected network as dimension of the network grows. Specifically, we address the question of how robustness of a network changes with the network dimension. Motivated by applications in transportation and economic networks, we study network topologies that are robust to scaling in network dimension, and investigate characteristics...
We develop an indirect adaptive model predictive control algorithm for uncertain linear systems subject to constraints. The system is modeled as a polytopic linear parameter varying system where the convex combination vector is constant but unknown. The terminal cost and set are constructed from a parameter-dependent Lyapunov function and the associated control law, and robust control invariant set...
This paper focuses on Norm-Optimal Iterative Learning Control (NO-ILC) framework for Single-Input-Single-Output (SISO) Linear Time Invariant (LTI) systems and considers the filter design problem in frequency domain. Modeling uncertainty, in general, degrades the performance of NO-ILC. Hence, ensuring Robust Monotonic Convergence (RMC) against modeling uncertainty is important, but the state-of-art...
This paper presents a convex-optimization-based technique to obtain PID parameters, used to control the infusion rate of the anesthetic drug propofol. Controller design is based on a set of identified patient models, relating propofol infusion to an EEG-based conciousness index. The main contribution lies in the method automatically taking inter-patient variability into account, i.e., it guarantees...
We revisit the issue of gain-scheduled versus robust control with a focus on matrix inequalities. It has been established that for uncertain continuous-time linear systems that depend affinely on the uncertainty, gain-scheduled stabilizability implies robust stabilizability. That is, as far as stabilizability is concerned, using a more complex gain-scheduled controller brings no advantage. In the...
The problem of robust fault detection (RFD) for discrete-time Markovian jump linear systems (MJLSs) with partly unknown transition probabilities is investigated in the paper. The RFD observer (RFDO) system and the dynamics of error generator are constructed. By introducing some free-weighting matrices, the proposed method leads to less conservatism compared with the existing ones. Moreover, the H∞...
Hysteresis nonlinearity, which is an inherent characteristic of piezoelectric actuators (PEAs), decreases the tracking precision and may even result in limit cycle oscillations. A tracking control based on H∞ robust disturbance observer (DOB) is presented for PEAs in this paper. Hammerstein system is applied to modeling dynamic hysteresis nonlinearity of PEA. Then, a control scheme that combines H...
A partial differential equation-based tracking controller is developed for a class of uncertain nonlinear systems with bounded external disturbances and time-varying input delay. A novel robust controller is designed such that the control input varies with both time and a spatial variable. The designed controller features gains to compensate for the delay and delay derivative independently and further...
A method is presented for synthesizing output estimators for a class of continuous time, uncertain, linear parameter-varying (LPV) systems. The uncertain system is described as an interconnection of a nominal LPV system and a block structured perturbation. The nominal LPV system is “gridded” over the space of parameters, with the state matrices being arbitrary functions of the parameters. The input/output...
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