Presence Of Deterministic Disturbances Research Articles

Predefined-Time Control of Full-Scale 4D Model of Permanent-Magnet Synchronous Motor with Deterministic Disturbances and Stochastic Noises

This paper presents a predefined-time convergent robust control algorithm that allows the control designer to set the convergence time in advance, independently of initial conditions, deterministic disturbances, and stochastic noises. The control law is consequently designed and verified by simulations for a full-scale 4-degrees-of-freedom (4D) permanent-magnet synchronous motor (PMSM) system in cases of a disturbance-free system with completely measurable states, a disturbance-free system with incompletely measurable states, a system with incompletely measurable states in the presence of deterministic disturbances, and a system with incompletely measurable states in the presence of both deterministic disturbances and stochastic noises. Numerical simulations are provided for the full-scale 4D PMSM system in order to validate the obtained theoretical results in each of the considered cases. To the best of our knowledge, this is the first attempt to design a predefined-time convergent control law for multi-dimensional systems with incompletely measurable states in the presence of both deterministic disturbances and stochastic noises.

Consensus Disturbance Rejection for Linear Multiagent Systems With Directed Switching Communication Topologies

This paper addresses the consensus disturbance rejection problem for multiple-input multiple-output linear multiagent systems (MASs) with directed fixed as well as switching communication topologies in the presence of deterministic disturbances. Based on the relative output information among neighboring agents, a controller, which incorporates the consensus error estimator, the state estimator with static coupling strength and the disturbance observer, is given such that consensus tracking could be achieved in the considered MASs under directed switching communication topologies provided that the control parameters are suitably chosen and the average dwell time is larger than a positive threshold, while the disturbances are fully rejected by the designed disturbance observer. Furthermore, by designing a state estimator with adaptive coupling law, a controller is given such that consensus disturbance rejection of MASs with directed fixed topology could be achieved in a fully distributed manner. The obtained theoretical results are finally validated by performing simulations on the unmanned aerial vehicles.

Disturbance Modeling and State Estimation for Predictive Control with Different State-Space Process Models

AbstractThe paper is concerned with disturbance modeling and observer design for Model Predictive Control (MPC) with different formulations of state-space process models. Systematic discussion is given, presenting the ways the deterministic disturbances most important in process control applications should be treated in the MPC algorithm, to obtain disturbance attenuation and offset-free control. The closely related problem of observer design and understanding is explained. It is shown that a simple approach with a process state observer only, in the presence of deterministic disturbances, can work better than the conventional approach of extended process-disturbance state estimation. The observer design is also considered for the case of extended velocity form state-space modeling including integrators. A simplified approach with reduced order observer is given. The results are illustrated on a 2×2 example process problem.

Identification from Step Response in the Presence of Deterministic Disturbance

Over the last few years many important issues in continuous-time identification from step response have been addressed. Methods for simultaneous estimation of the delay and algorithms to deal with transient initial conditions have been proposed. However, the issue of disturbance has not been addressed in the context of a single step input. In this article, we present a new approach for identification from step response in the presence of deterministic disturbances. Two types of disturbances are considered. Type one assumes that the disturbance affects the output throughout the test period. In the second type, we consider a disturbance that enters into the process at an unknown time during the test. For both cases the efficacy of the proposed procedure is demonstrated using a simulation example. An experimental study is also presented for the second type of disturbance.

Robust design of adaptive control system in the presence of deterministic disturbance

In this paper, we propose robust design of Immersion and Invariance (I&I) - model reference adaptive control system (MRACS) for an SISO linear time-invariant system with arbitrary relative degree in the presence of deterministic disturbance. In this method, we introduce fixed compensator and prove uniformly asymptotic stability of the tracking error and the boundedness of all signals in the closed system.

間接法MRACSのロバスト構成法-確定外乱の考慮

間接法MRACSのロバスト構成法-確定外乱の考慮

Analysis on the Fundamental Properties of Active Magnetic Bearing Control Systems by a Transfer Function Approach.

The fundamental properties of active magnetic bearing controllers are investigated from the standpoint of output regulation in the presence of deterministic disturbances. A transfer function approach is used in the analysis. The variable to be regulated is selected from rotor displacement, coil current and bearing force. The treated disturbance is stepwise or harmonic; the latter is caused by rotor unbalance. The essential properties of the controller achieving output regulation for step disturbances are derived. Those for unbalance disturbance are also shown by using complex-variable representation, which makes the procedure of analysis similar to that for constant disturbances. The derived controllers for unbalance compensation are converted into two types of real-variable representation: state equation and convolution integral. It clarifies the equivalence between the independently developed unbalance compensation controllers. It is also shown that the obtained results can be utilized in designing controllers.

Transfer function characterization of output regulation control in active magnetic bearings

ABSTRACT The problems of output regulation in the presence of deterministic disturbances are discussed for active magnetic bearings. The treated disturbances are constant and harmonic: the latter is generated by rotor unbalance. A transfer function approach is used in the analysis. The general structures of controllers achieving displacement or current regulation for constant disturbances and achieving displacement, current or force regulation for unbalance disturbances are derived. The controllers for unbalance compensation are converted into two types of real-variable representation: state equation and convolution integral. It clarifies the equivalence between the independently developed unbalance compensators.

A Transfer Function Approach to Active Magnetic Bearing Control Systems.

The fundamental properties of active magnetic bearing controllers are investigated from the standpoint of output regulation in the presence of deterministic disturbances. A transfer function approach is used in the analysis. The variable to be regulated is selected from rotor displacement, coil current and bearing force. The treated disturbance is constant or harmonic ; the latter is caused by rotor unbalance. The essential properties of the controller achieving output regulation for constant disturbances are derived. Those for unbalance disturbance are also shown by using complexvariable representation, which makes the procedure of analysis similar to that for constant disturbances. The derived controllers for unbalance compensation are converted into two types of realvariable representation : state equation and convolution integral. It clarifies the equivalence between the independently developed unbalance compensation controllers. It is also shown that the obtained results can be utilized in designing controllers.

Adaptive Control with Improved Asymptotic Performance in the Presence of Deterministic Disturbances

The problem of adaptive control of linear systems subjected to both small parameter and bounded additive deterministic disturbances is considered. The controlled systems are not identifiable in view of poor a priori information about disturbances. It is supposed that for system with known parameters a certain regulator is given that ensures a desired non-adaptive asymptotic control performance. It is proven that this nonadaptive parameter-dependent control performance is achievable under adaptive control in spite of non-identifiability of the system. The solution is based on control-oriented estimation algorithm and uses set estimates of unknown parameters.

A New Disturbance Compensating Method in Model Reference Adaptive Control System

This paper proposes a design method of MRACS (Model Reference Adaptive Control System) for unknown plants in the presence of deterministic disturbance or periodic disturbance, so that the output error will converge to zero as time tends to infinity.In the traditional adaptive control systems dealing with disturbance, the disturbance was usually restricted to be deterministic. To remove the effect of disterbance, the general way was to use extended system including a disturbance model, or to use integral compensators. Here, a new disturbance compensating method is proposed, in which disturbance compensating signals are introduced into MRACS, and are combined adaptively to cancel the effect of disturbance. In this proposed method, because the filter signals of input and output are composed in the same way as the disturbance free cases, the MRACS has a simple constructure. Even for the periodic disturbance with unknown shape, if the period is known, by using Fourier series, the proposed method is also possible to remove the effect of this sort of disturbance. Furthermore, being used, disturbance compensating signals in MRACS, it is possible to take the initial responses of filters into account, and the characteristics of parameter convergence can be improved. The effectiveness of this proposed method is illustrated by some computer simulations.

Practical Aspects of PID Auto-Tuners Based on Relay Feedback

The performance of an automatic PID controller tuning method based on relay feedback is studied in the presence of deterministic disturbances. It is found that the occurence of any static load disturbance could cause significant errors in the estimates of the ultimate gain and period. However, the resultant asymmetry of the relay switching intervals can be used as an error indicator, or used to compute a self-corrective bias to restore accuracy of the estimates. This corrective bias is found to be functional even in the presence of moderate nonlinearity. A reliable self-biasing auto-tuner is thus resultant. The effect of a less common sinusoidal load could be more serious since it may not be detectable and hence more prior knowledge about its presence is required.

Quadratic and higher-order feedback gains for control of nonlinear systems

The problem of controlling a nonlinear system optimally in the presence of deterministic disturbances is treated. In particular, optimal feedback control in the vicinity of an optimal nominal trajectory is sought. The control law is to preserve the optimality of the nominal path and provide terminal control to the nominal end point defined by hard constraints on functions of the terminal state. A method of obtaining approximations of any order to such a nonlinear optimal feedback control law is presented. Linear differential equations for the linear and quadratic feedback gains are explicitly given. The equations for the linear gains are homogeneous, whereas those for higher-order gains are nonhomogeneous. The forcing terms are functions of the gains of the next lower order. Closed-form expressions for the linear and quadratic gains for a simple intercept problem and their simulations are presented. The addition of quadratic gains to the linear control approximation generally results in improved control.