Fast Output Sampling Research Articles

FAULT TOLERANT CONTROL OF FLEXIBLE SMART STRUCTURES USING ROBUST DECENTRALIZED FAST OUTPUT SAMPLING FEEDBACK TECHNIQUE

ABSTRACTThis paper presents the modeling, design and simulation of a Robust Decentralized Fast Output Sampling (RDFOS) feedback controller for the vibration control of a smart structure (flexible cantilever beam) when there is actuator failure. The beam is divided into 8 finite elements and the sensors / actuators are placed at finite element positions 2, 4, 6, and 8 as collocated pairs. The smart structure is modeled using the concepts of piezoelectric theory, Euler‐Bernoulli beam theory, Finite Element Method (FEM) techniques and the state space techniques. Four multi‐variable state‐space models of the smart structure plant are obtained when there is a failure of one of the four actuators to function. The effect of failure of one of the piezo actuators to function during the vibration of the beam is observed. The tip displacements, open and closed loop responses with and without the controller are observed. For all of these models, a common stabilizing state feedback gain F is obtained. A robust decentralized fast output sampling feedback gain L which realizes this state feedback gain is obtained using the LMI approach. In this designed control law, the control inputs to each actuator of the multi‐model representation of the smart structure is a function of the output of that corresponding sensor only and the gain matrix has got all off‐diagonal terms zero and this makes the control design a robust decentralized one. Then, the performance of the designed smart system is evaluated for Active Vibration Control (AVC). The robust decentralized FOS controller obtained by the designed method requires only constant gains and hence may be easier to implement in real time.

Control of Piezo Actuated Structures using Interval Method

A Fast output sampling feedback controller is designed and implemented for vibration control of piezoelectric actuated beam structure using an interval method. Uncertainties which are assumed in the model, are identified through on line recursive least square parameter estimation. The control and identification process is done by using Simulink modeling software and a dSPACE DS 1104 controller board.

Mathematical Modeling of SISO based Timoshenko Structures – A Case Study

This paper features the mathematical modeling of a single input single output based Timoshenko smart beam. Further, this mathematical model is used to design a multirate output feedback based discrete sliding mode controller using Bartoszewicz law to suppress the flexural vibrations. The first 2 dominant vibratory modes is retained. Here, an application of the discrete sliding mode control in smart systems is presented. The algorithm uses a fast output sampling based sliding mode control strategy that would avoid the use of switching in the control input and hence avoids chattering. This method does not need the measurement of the system states for feedback as it makes use of only the output samples for designing the controller. Thus, this methodology is more practical and easy to implement.

DESIGN OF FAST OUTPUT SAMPLING FEEDBACK CONTROL FOR SMART STRUCTURE MODEL

In this paper, the problem of modelling and output feedback control design for a smart structural system using piezoelectric material as a sensor/actuator is addressed. The model for a smart cantilever beam is developed by the finite element method. State space models for a smart cantilever beam with a single sensor/actuator for three different sensor/actuator locations are obtained. The fast output sampling feedback control is designed to control the first two vibration modes for each sensor/actuator location and its performance is evaluated.

Output Feedback Sliding-Mode Control for Uncertain Systems Using Fast Output Sampling Technique

This paper presents a method for achieving quasi-sliding mode for uncertain systems using a fast output sampling control strategy that avoids switching of control and, hence, avoids chattering. This method does not need the system states for feedback as it makes use of only the output samples for designing the controller. Thus, this methodology is more practical and easy to implement. The design technique is illustrated through two numerical examples

Modeling and fast output sampling feedback control of a smart Timoshenko cantilever beam

This paper features about the modeling and design of a fast output sampling feedback controller for a smart Timoshenko beam system for a SISO case by considering the first 3 vibratory modes. The beam structure is modeled in state space form using FEM technique and the Timoshenko beam theory by dividing the beam into 4 finite elements and placing the piezoelectric sensor/actuator at one location as a collocated pair, i.e., as surface mounted sensor/actuator, say, at FE position 2. State space models are developed for various aspect ratios by considering the shear effects and the axial displacements. The effects of changing the aspect ratio on the master structure is observed and the performance of the designed FOS controller on the beam system is evaluated for vibration control.

Robust decentralized fast-output sampling technique based power system stabilizer for a multi-machine power system

Power-system stabilizers (PSSs) are added to excitation systems to enhance the damping during low-frequency oscillations. In this paper, the design of robust decentralized PSS for four machines with a 10-bus system using fast-output sampling feedback is proposed. The nonlinear model of a multimachine system is linearized at different operating points, and 16 linear state space models are obtained. For all of these plants, a common stabilizing state feedback gain, F, is obtained. A robust decentralized fast-output sampling feedback gain which realizes this state feedback gain is obtained using LMI approach. This method does not require all the states of the system for feedback and is easily implementable. This robust decentralized fast-output sampling control is applied to a nonlinear plant model of several machines at different operating (equilibrium) points. This method yields encouraging results for the design of power-system stabilizers.

Analysis of a multirate sampled-data implementation of a continuous-time, sliding-mode observer/controller pair

An approach for closed-loop stability analysis of sampled-data implementations of control systems with Lipschitz-continuous non-linear elements is applied to a sliding-mode-based observer/controller pair. The stability analysis involves the evaluation of a finite horizon integral obtained from an L2 -type analysis. This results in stability constraints involving matrix inequalities. The conditions raised can be satisfied for sufficiently fast sampling. The technique allows for incorporation of multiple sampling frequencies. Two sampling frequencies have been considered for the sliding-mode controller, a fast output sampling frequency and a slower controller sampling frequency. A numerical example illustrates some characteristics of the approach.

A Minor Correction to “A New Algorithm for Discrete-Time Sliding Mode Control Using Fast Output Sampling Feedback”

The purpose of this letter is to show that the recently proposed fast output sampling sliding-mode control method in an earlier paper by the authors needs a small correction in the expression for the control law. The results or the corrected algorithm is illustrated by the same example considered in the earlier paper.

Fault-tolerant spatial control of a large pressurised heavy water reactor by fast output sampling technique

A method is presented to design a spatial control system of a large pressurised heavy water reactor (PHWR) with the constraint that the closed loop system be stable even if one sensor or actuator has failed. Linear state models are obtained corresponding to the normal operating condition and different failure modes of the reactor. Each model is found to possess the two time scale property. Using similarity transformation each two time scale model is converted into a block diagonal form by which two subsystems, namely a fast subsystem and a slow subsystem, are easily obtained. State feedback is designed separately for the slow and the fast subsystems for each model. Then a composite state feedback gain is obtained from the state feedback gains computed for the slow and fast subsystems separately for each model. The composite state feedback so designed assigns the poles at arbitrary locations for the respective models. These composite state feedback gains are realised simultaneously by fast output sampling gains. Thus the states of the system are not needed for feedback purposes. An LMI formulation is used to overcome the undesired effects of poor error dynamics and noise sensitivity which are encountered if state feedback is realised exactly.

Spatial control of a large pressurized heavy water reactor by fast output sampling technique

In this paper a method is presented to design a controller for discrete two time scale system based on fast output sampling technique. Using similarity transformation the two time scale system is converted into a block diagonal form which is then partitioned into two subsystems, namely, a fast subsystem and a slow subsystem. Now state feedback controls are designed separately for the slow subsystem and the fast subsystem. Then a composite state feedback control is obtained from the state feedback controls designed for subsystems to assign the eigenvalues of the entire system at arbitrary locations. This composite state feedback gain is realized by using fast output sampling feedback gain. Thus the states of the system are not needed for feedback. But in practice there are two problems in realizing the state feedback gain exactly viz. poor error dynamics and noise sensitivity. So a linear matrix inequality formulation is used to overcome these undesired effects. The method has been applied to a large pressurized heavy water reactor (PHWR) for control of xenon induced spatial oscillations. A particular grouping of the state variables has been considered to decompose the system into the slow subsystem and the fast subsystem. Then fast output sampling fedback gains have been calculated. The efficacy of the control has been demonstrated by simulation of transient behavior of the nonlinear model of the PHWR.

Design of power system stabilizer for single machine system using robust fast output sampling feedback technique

Power system stabilizers (PSS) are added to excitation systems to enhance the damping during low frequency oscillations. In this paper, the design of PSS for single machine connected to an infinite bus using fast output sampling feedback is proposed. The non-linear model of a machine is linearized at different operating points and 16 linear plant models are obtained. For all of these plants a single stabilizing state feedback gain, F is obtained. A robust fast output sampling feedback gain which realizes this state feedback gain is obtained using linear matrix inequalities approach. This method does not require state of the system for feedback and is easily implementable. This robust fast output sampling control is applied to non-linear plant model of one machine at different operating (equilibrium) points. This method gives very good results for the design of PSS.

Variable structure model following controller using non-dynamic multirate output feedback

The paper presents a new algorithm for a variable structure model following controller (VSMFC) design for discrete time systems using a fast output sampling technique. The reaching law approach is used to guarantee the sliding mode motion. This methodology is easy to implement since the method is based on output feedback. It is shown that the proposed fast output sampling variable structure model following controller (FOS VSMFC) gives the same results as obtained by state feedback VSMFC. To demonstrate the design technique a VSMFC is designed for the tip position control of a single flexible link. The simulation results show the effectiveness of the proposed method.

Algorithm on robust sliding mode control for discrete-time system using fast output sampling feedback

A robust fast output sampling sliding mode control (FOSSMC) method for discrete-time systems with uncertainty is presented. Recently a FOSSMC was designed for a constant discrete-time system, however, this control law does not ensure the robustness of the system to parameter uncertainty and external disturbances. The authors present a FOSSMC that for known parameter variations and external disturbances does guarantee the robustness of the sliding mode motion.

A new algorithm for discrete-time sliding-mode control using fast output sampling feedback

This paper presents a new approach for sliding-mode control (SMC) of discrete-time systems using the reaching law approach together with the fast output sampling (FOS) feedback technique. This method does not need the system states for feedback as it makes use of only the output samples for designing the controller. Thus, this methodology is more practical and easy to implement. A numerical example demonstrates the design technique. Simulation results show that the proposed FOS SMC technique produces the same results as obtained by state feedback SMC technique.

Timely robust fault detection for multirate linear systems

This paper presents a fault detection and isolation scheme for multirate systems with a fast input sampling rate and slower output sampling rates. We design a separate observer for each set of simultaneous measurements with the observer operating at their sampling rate. We use an unknown input observer design to allow state estimation in the presence of disturbances and modelling errors. The observer allows us to estimate the system state and obtain a residual vector to be used in fault detection. Furthermore, we are able to use single-rate methodologies for fault diagnosis. We provide necessary and sufficient conditions for the existence of the observer and the detection of the fault vector. An example is given to illustrate the new fault detection approach and another to demonstrate fault isolation.

OUTPUT FEEDBACK SLIDING MODE CONTROL FOR MIMO DISCRETE TIME SYSTEMS

In this paper we present a new algorithm for discrete sliding mode control of linear multivariable systems using fast output sampling feedback. Here we make use of a single switching surface regardless of the number of inputs. The main contribution of this work is that instead of using the system states, the output samples are used for designing the controller. Numerical example demonstrates the design technique.

Fast Output Sampling Regulators with Integral Action

Fast output sampling controllers have been proposed as an alternative to observer-based state feedback control, and have been demonstrated to be useful for robust controller design. Here it is shown how integral action can be incorporated into the design. An LMI-based design procedure that has been proposed recently to trade fast decay of estimation errors against low noise-sensitivity, can be used at the same time to eliminate the estimation error resulting from an additional integrator loop. The proposed design method is illustrated by a practical application: a multivariable regulator for a turbogenerator is designed and experimental results are shown.

Robust control of a laboratory aircraft model via fast output sampling

A new multimodel approach to robust controller design is illustrated by a practical application: for a laboratory aircraft model, a robust controller is designed for acceptable performance, in normal operating conditions and under propeller failure, simultaneously. Based on a linear model for each operating mode, linear matrix inequality (LMI) formulation of the problem and convex programming are used to search for a state feedback controller that achieves the objective. This state feedback design is then realized simultaneously in both operating modes by a controller that is based on fast output sampling. Robust performance is demonstrated by experimental results.

Robust Control of an Aircraft Model

AbstractA new multimodel approach to robust controller design is illustrated by a practical application; for a laboratory aircraft model, a robust controller is designed simultaneously for normal operating conditions and for propeller failure. Based on a linear model for each operating mode, an LMI formulation of the problem and convex programming are used to search for a state feedback controller which achieves the objective. This state feedback design is then realized simultaneously in both operating modes by a controller which is based on fast output sampling. Robust performance is demonstrated by experimental results.