This paper presents an investigation into the analysis of dynamic behaviour of a flexible robot manipulator using a symbolic manipulation approach. A constrained planar single-link flexible manipulator is considered. ...
This paper presents an investigation into the analysis of dynamic behaviour of a flexible robot manipulator using a symbolic manipulation approach. A constrained planar single-link flexible manipulator is considered. The finite element method is used for dynamic modelling of the system. A symbolic algorithm is developed using Macsyma. A general solution describing the dynamic behaviour of the manipulator is obtained. The effect of physical parameters of the manipulator on the characteristics of the system and the impact of their variation on the minimum-phase features of the system are studied and assessed.
The paper is concerned with the state estimator design problem for perturbed linear continuous-time systems with H/sub /spl infin// norm and variance constraints. The perturbation is assumed to be time-invariant and n...
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The paper is concerned with the state estimator design problem for perturbed linear continuous-time systems with H/sub /spl infin// norm and variance constraints. The perturbation is assumed to be time-invariant and norm-bounded and enters into both the state and measurement matrices. The problem we address is to design a linear state estimator such that, for all admissible measurable perturbations, the variance of the estimation error of each state is not more than the individual prespecified value, and the transfer function from disturbances to error state outputs satisfies the prespecified H/sub /spl infin// norm upper bound constraint, simultaneously. Existence conditions of the desired estimators are derived in terms of Riccati-type matrix inequalities, and the analytical expression of these estimators is also presented. A numerical example is provided to show the directness and effectiveness of the proposed design approach.
The paper deals with the adaptive control design of power turbogenerators operating in a complex power system. The designed control has to provide required steady-state and dynamic system properties under changing ope...
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The paper deals with the adaptive control design of power turbogenerators operating in a complex power system. The designed control has to provide required steady-state and dynamic system properties under changing operating conditions. The proposed control structure is a multiparameter one with self-tuning regulators on the subsystem level of the system. In the design, the standard pole placement method with recmsive parameter identification and heuristic automatic pole shift factor setting has been used which maintains the required oscillation level of the subsystems. The designed controllers have been verified via simulations using a nonlinear turbogenerator model in each subsystem. The power system parameter values have been obtained from the power system of Slovakia.
The paper summarizes current trends in building of a control Laboratory supporting controlengineering and control Theory courses. The emphasis is put on the laboratory equipment, the scale models, and the software en...
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The paper summarizes current trends in building of a control Laboratory supporting controlengineering and control Theory courses. The emphasis is put on the laboratory equipment, the scale models, and the software environment used for supporting the theoretical content of lectures and running the experiments in real-time. Classes of laboratory models are introduced considering the model complexity and common characteristics of a large variety of models developed over decades. Software tools supporting control experiments in real-time are summarized. The goal of the paper is to help those who intend to build a new control laboratory with practical experiments. Using experience of others saves time and money.
State estimation problem together with systems classification is solved. The novel idea is to represent all conditional probability density functions (c.p.d.f.) as a set of random samples. Usual approach is to represe...
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Following a polynomial approach to control design, the simultaneous stabilization by a controller of given fixed order of a family of SISO linear systems is interpreted as an NP-hard BMI feasibility problem. Upon form...
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State estimation problem together with systems classification is solved. The novel idea is to represent all conditional probability density functions (c.p.d.f.) as a set of random samples. Usual approach is to represe...
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State estimation problem together with systems classification is solved. The novel idea is to represent all conditional probability density functions (c.p.d.f.) as a set of random samples. Usual approach is to represent c.p.d.f. as a function over the state space. Using large number of samples an exact equivalent representation of c.p.d.f. is obtained. From this samples the estimates of moments like mean and covariances can be obtained. In [1] is described bootstrap filter for updating these samples for discrete time system. In this way any nonlinearity and nonnormality of noise can be handled. The contribution of this article is to use this approach to systems classification.
The role of data prefiltering in integrated process identification and model predictive control is presented in this paper. A multistep ahead prediction error method is derived. Using the multistep ahead prediction er...
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The role of data prefiltering in integrated process identification and model predictive control is presented in this paper. A multistep ahead prediction error method is derived. Using the multistep ahead prediction error method, process models that are more suitable for multistep ahead prediction can be identified. It is also found that the new identification method performed under closed-loop condition gives better models for the design of predictive control.
The role of structural invariants in the solutions of classical linear control problems when regular state feedback is used is enhanced. The structural modification that arise when these problems are extended to the c...
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In this note we consider the problem of H ∞ observer design for a class of uncertain linear discrete-time systems with delayed state and parameter uncertainties. The goal of this problem is to design a linear state o...
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In this note we consider the problem of H ∞ observer design for a class of uncertain linear discrete-time systems with delayed state and parameter uncertainties. The goal of this problem is to design a linear state observer such that, for the positive integer state time-delay and all admissible norm-bounded parameter uncertainties, the observation process remains robustly stable and the transfer function from exogenous disturbances to error state outputs meets the prespecified H ∞ norm upper bound constraint. The observer structure does not depend on the parameter uncertainties. A simple, effective algebraic methodology is developed to derive the conditions for the existence of the desired robust H ∞ observers, and the analytical expression of these observers is then characterized in terms of the matrix Riccati-like equations/inequalities. We provide a numerical example to demonstrate the validity and the applicability of the proposed approach.
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