Output Disturbances Research Articles

Extended Kalman Filter Based Linear Quadratic Regulator Control for Optical Wireless Communication Alignment

High-precision positioning of two underwater mobile robots based on laser beams alignment has been investigated in this work. Usually, the control problem addressed in laser beams aims to maintain the position of the receiver robot aligned with the transmitter robot despite the effects of noise and active disturbances. In this paper, a new state space model is proposed. The latter is more precise than the usual used two state space model [1]. Furthermore, an estimation based control strategy using Extended Kalman Filter Estimator (EKF) and Linear Quadratic Regulator (LQR) is proposed to achieve the control objectives. LQR controller is well known as optimal control design with better tuning flexibility along with intrinsic robustness properties such as noise and output disturbance rejections. The achieved performance of the proposed controller is compared to the conventional proportional (P), Proportional-Integral-Derivative (PID) and Proportional-Integral (PI) controller to analyze the improvements and stability. In addition, an investigation of a sensitivity analysis is conducted to show robustness with different process noise variances of LQR controller.

Fault Estimation Based on an Adaptive Observer for a Class of Uncertain Nonlinear Descriptor Systems

First, an $${{H}_{\infty }}$$ adaptive observer is designed for a class of uncertain nonlinear descriptor systems. This observer can simultaneously estimate the actuator faults, sensor faults, and system states in the presence of uncertainty and output disturbance. Various types of faults, such as abrupt faults and incipient faults, can be estimated using the observer. Then, the observer is designed without requiring some conditions to be satisfied. The observer stability is analyzed using the Lyapunov stability theory. Then, the sufficient conditions for the existence of the observer are converted into linear matrix inequalities (LMIs). The proposed method does not need the Lipschitz constant in the LMI formulation. Therefore, the proposed method can be applied to systems with unknown or large Lipschitz constants. Additionally, unlike the conventional adaptive estimator, the proposed estimator has both proportional and integral components to enhance the accuracy and rapidity of the estimation. Two simulation examples are provided to illustrate the effectiveness of the proposed method for descriptor systems and normal state-space systems.

Characteristics of harmonic distortion and disturbance in frequency 9-150 kHz of the grid-connected rooftop photovoltaic system for various types non-linear household loads

The usage of Photovoltaic (PV) energy system as a solar power plant has been growing rapidly in the world, because it is clean without emitting greenhouse gasses. The rapid development of power electronics technology has an impact in the development of PV system and the usage of non-linear household appliances that use inverter technology. In PV system, an inverter is used to convert direct current (DC) power from sunlight to alternating current (AC). Inverters usually have a switching rate higher than 1 kHz, which may cause waveform distortions and disturbances in AC power output, such as harmonics and disturbance in the frequency range 9-150 kHz. These disturbances may affect the performance of equipment, as well as neighbor equipment connected to the same network. This research is focused on analyzing the effect of current flowing in the non-linear household loads (induction cooker and compact fluorescent lamp) to the harmonics distortion (THDi, TDDi and harmonic voltage distortion) and disturbance in frequency 9-150 kHz on the Grid-connected Rooftop PV System by conducting laboratory measurement using a computer-based oscilloscope and power quality analyzer. The results show that the variation of current flowing in the equipment affects the harmonics distortion and disturbance in frequency 9-150 kHz.

Event-Triggered Tracking Control With Filtered Outputs and Impulsive Observers.

This article studies an event-triggered tracking control problem for linear systems subject to output feedback and disturbances, where a new configuration incorporating filtered outputs and impulsive observers is proposed. The transmissions in the sensor-to-controller and controller-to-actuator channels are scheduled by dynamic event-triggered control (ETC) mechanisms to save communication resources. To eliminate the effects of the derivatives of output noises on the tracking and transmission performance, a low-pass filter is introduced to preprocess the raw output signals. Both the filter state and raw output will be transmitted to the controller node while the latter is only utilized by an impulsive observer at some discrete instants. Then, it is proved that the proposed dynamic ETC schemes can solve the practical tracking control problem with fixed reference points and avoid Zeno behavior in both channels. Meanwhile, when some user-specified parameters in the event-triggering conditions are small enough, the tracking control problem can be solved asymptotically for disturbance-free systems. In addition, to further improve the transient performance, reduced-order impulsive observers and optimization of impulsive gain matrices are studied. Finally, simulation results are provided to illustrate the efficiency and feasibility of the obtained results.

Okun's law: Copula-based evidence from G7 countries

In this paper we present evidence on the association between unemployment and output in the G7 economies, which has direct implications for the validity of Okun's law. Specifically, we investigate dependence and asymmetry between the residuals of the output and unemployment first difference equations using the copula methodology. We find that dependence between GDP and unemployment disturbances is strong only in USA and France followed by Canada, the UK and Germany. There is no dependence in Italy and Japan. This enhances the validity of Okun's law in the former countries without invalidating it in Italy and Japan, since there is still a negative relationship given by the systematic part of the output-unemployment difference equations estimates. Also, there is asymmetry in the former five countries. Output disturbances are associated with unemployment ones only during recessions, while they are completely disentangled throughout contractions in the US, France, Canada, the UK and Germany. These findings imply that USA and France, and less so Canada, Great Britain and Germany provide the most favorable environment for counter-cyclical economic policies. In these economies, policy makers should react more than output-unemployment dynamic equations dictate in case of output slumps. However, during recoveries in these countries and in Italy as well as Japan during the whole business cycle, authorities ought to base stabilization policies solely on the systematic part of the relation between output and unemployment changes.Our results provide guidance to policy makers in addition to what is suggested by traditional empirical approaches, which focus on the estimation of the deterministic part of the output-unemployment relationship.

Robust Optimal PID type ILC for Linear Batch Process

The proportional-integral-derivative (PID) controller is standard technique for controlling the industrial batch process. However, the parameter tuning and updating of PID controller has been a challenging topic for control engineers especially for the real system having initial state error, state and output disturbances. In this paper, a kind of robust optimal iterative learning control (ILC) scheme is suggested to update the PID gains for the linear system with initial state error, state and output disturbances. The quadratic performance criteria is considered, which constitute of the error and input slew rate, and the robust BIBO stability is investigated theoretically for the proposed PID type ILC scheme. In addition, the bound of the tracking error has been calculated by using Lyapunov composite energy function. Simulation examples are also given to demonstrate the effectiveness of the proposed scheme in term of its ability to deal with linear as well as nonlinear system

Attractive ellipsoid design for robust sliding‐mode observation error in stochastic nonlinear discrete‐time systems

SummaryIn this paper the observation process of stochastic discrete‐time nonlinear system is analyzed. The system to be observed is assumed to be uncertain, but fulfilling the global "quasi‐Lipschitz" condition and is subjected to stochastic input and output disturbances of a white noise type. The combination of a traditional Luenberger residual term with a discontinuous one is considered. The designing of the best observer gain matrices is realized by using the Robust Attractive Ellipsoid Method for the analysis of the averaged observation error. The construction of this attractive ellipsoid is based on the numerical solution of some matrix optimization problem under specific constraints of Bilinear and Linear Matrix Inequalities (BMI's and LMI's) type applied to improve the attractiveness zone estimation. Two numerical xamples illustrate the effectiveness of the suggested approach.

Modification of Fluid Balance Chart for Nurses to Monitor Fluid Volume Disturbance in Patients Undergoing Hematopoietic Stem Cell Transplantation

Background: Hematopoietic stem cell transplantation involves the intravenous infusion of autologous or allogeneic stem cells to reestablish hematopoietic function in patients whose bone marrow or immune system is damaged. This study aimed to modify the fluid balance chart for nurses to monitor fluid volume disturbance in patients undergoing hematopoietic stem cell transplantation. Design: A prospective, single - centered research design was utilized in this study. Setting: The study was conducted at the Bone marrow transplantation unit at South – Egypt Cancer Institution. Subject: A purposive sample of 25 adult conscious patients undergoing stem cell transplant, from both sexes and age range between (20 – 65years).Tools: three tools were used; a structured interview questionnaire, modified fluid balance chart, and a fluid volume disturbance monitoring sheet. Results: There was a statistically significant difference between the modified and routine fluid charts regarding the mean amount of daily fluid balance (10750.00 ± 409 ml) and (8333. 63 ± 388 ml) respectively with (P.value = 0.001). Conclusion: modification of fluid balance chart has a great effect on accurate monitoring of the fluid intake, output, and fluid volume disturbances.

Adaptive output‐feedback control for damped wave equations with unknown damping coefficient and corrupted boundary measurement

SummaryAdaptive output‐feedback control is investigated for a class of uncertain damped wave equations. The remarkable features of the system in question are as follows: (i) Unknown damping is allowed at the boundary; (ii) The boundary measurement is corrupted by an unknown harmonic disturbance. These features make the control problem essentially different from those in the related literature. To solve the problem, a novel adaptive output‐feedback control scheme is established for the system. Specifically, an ingenious observer is first introduced to reconstruct the unmeasured system state in the space domain. Based on this, a certain compensation mechanism is designed for the unknown damping coefficient and output disturbance by adaptive technique based on projection operator. Then, an output‐feedback controller is successfully designed by the backstepping method for ODEs, which guarantees that all states of the resulting closed‐loop system are bounded, and the original system state ultimately converges to an arbitrarily prescribed small neighborhood of the origin. Finally, a simulation example is provided to illustrate the effectiveness of the proposed method.

Reduced-Order Observer Based-Fault Estimation for Markovian Jump Systems With Time-Varying Generally Uncertain Transition Rates

This paper addresses such problem for simultaneous estimations of the actuator fault, output disturbance and sensor fault for a type of Markovian jump systems, which takes on time-varying generally uncertain transition rates. In order to perform estimations for faults, a new reduced-order observer is proposed, of which the gain matrix is designed to fully decouple the unknown input for the system. As for the solution to time-varying generally uncertain transition rates, an offline quantization mechanism is developed, which can help to prove, to a large extent, the observer error system to be stable. The proposed method is able to guarantee the exact estimations of the states and faults in spite of the existence of external disturbances and the time-varying stochastic switching. Furthermore, a numerical example is brought to testify the correctness of the designed fault estimation method.

Improved control strategy for Cuk converter assisted wind‐driven SEIG for DC nanogrid

In this study, the current mode control strategy for a Cuk converter assisted self-excited induction generator-based wind energy conversion system (WECS) for DC nanogrid is proposed. The sliding mode controller (SMC) is a non-linear controller and, is preferred because of good static and dynamic response for input -output disturbance rejections. However, the knowledge of all the state variables is required, which increases the number of sensors and control complexity. To reduce the number of sensors, reduced-order SMC (ROSMC) can be implemented. Conventionally design of the voltage loop in ROSMC does not consider the uncertainty of the control parameter. However, the accuracy of the control signal generated by the ROSMC also depends on how accurately the reference current is generated. Therefore, a genetic algorithm tuned PI controller is proposed to generate the ripple-free reference current. Artificial intelligence assisted ROSMC (AIROSMC) is proposed because of its advantages over SMC, which are a reduced number of sensors, improved dynamic response and easy implementation. The extensive simulation study is carried in MATLAB\Simulink for comparative analysis of fixed frequency SMC, two variable SMC, ROSMC, and AIROSMC. The harmonic spectrum analysis is carried out to justify the selection of DBR instead of the controlled rectifier.

An internal model control design method for failure-tolerant control with multiple objectives

The selection of control structure is a critical step in the design of a control system since it can largely affect the achievable control performance. This paper presents a general internal model control (IMC) structure with multiple degrees-of-freedom for the design of control systems with multiple objectives (i.e., reference tracking and load and output disturbance rejection), so that controllers are designed independently of each other. The optimal performance of controllers is shown to remain intact when a controller is taken off-line, for example, due to actuator and/or sensor failures. This feature circumvents the need to redesign the remaining on-line controllers for optimal failure-tolerant control. The proposed control approach is used to derive IMC control structures for multi-loop cascade and coordinated control systems. The performance of the control approach is demonstrated on a simulated thin-film drying process in continuous pharmaceutical manufacturing for several multi-loop control structures and a variety of control-loop component failures.

High precision position control of electro-hydrostatic actuators in the presence of parametric uncertainties and uncertain nonlinearities

Characterized by high power-to-weight ratio, modularity and energy efficiency, electro-hydrostatic actuators (EHAs) have been successfully applied to aircrafts and submarines, where high precision and repeatability are in high demand. The position tracking performance, however, can be inevitably affected by parametric uncertainties and uncertain nonlinearities. Model inaccuracy or system variations normally require a large loop gain to achieve robust performance, which leads to over-design. Leakage in the fluid power system decreases steady-state accuracy, and friction in the actuator degrades the transient performance or even causes stick-slip motion at low speeds. Furthermore, the system may exhibit limit cycle (or hunting) due to Stribeck friction and integral action. This paper proposes a robust high precision position control strategy incorporating leakage and friction compensation for EHAs. Quantitative feedback theory (QFT) is applied to design a robust controller that satisfies the prescribed performance specifications without over-design, considering model inaccuracy and system variations. The internal leakage is subsequently compensated based on experimental data instead of incorporating an integrator in the controller; hence, limit cycle is avoided, and response speed is improved. Friction in the actuator is identified based on the LuGre friction model and compensated through an observer in the loop. Friction variation and load fluctuation are considered to be output disturbances to be suppressed by the QFT controller. The QFT controller with leakage and friction compensation scheme is verified through experiments on a typical EHA. Both the steady-state and transient position tracking performances are greatly improved.

Model Reference Robust Adaptive Control of Control Element Drive Mechanism in a Nuclear Power Plant

In the nuclear power plant, the control element drive mechanism (CEDM: A type of solenoid actuators) is used to insert nuclear fuel rods into the core to regulate the neutron absorption within the reactor. The control environment is full of uncertainty and disturbance, and the CEDM is supposed to cope with the varying conditions in the reactor. In this paper, a model reference adaptive control (MRAC) of CEDM is investigated. The existing MRAC scheme that assumes the known system order is first extended to the system with unknown high-frequency gain and output disturbance, and then the extended version is applied to the control problem of CEDM. A simplified relationship between the input voltage and the magnetic force of the CEDM is established based on Kirchhoff’s voltage law and the magnetic co-energy theory. The system order of the plant is identified by the prediction error method using experimental input/output data: A 3rd order linear model with three poles and two zeros turns out to be the best model for control. Based on this model, a 3rd order reference model is selected, and an adaptive control law with s-modified adaptation laws is designed under output disturbance. The performance of the proposed control law is compared with a well-tuned PI controller and the conventional MRAC. The superiority of the proposed method is also demonstrated in an abnormal condition. Simulation and experiment results are provided.

Uncertainty and Disturbance Estimator-Based Robust Tracking Control for Dual-Active- Bridge Converters

External disturbances, system uncertainties, and various load characteristics, e.g., deadtime effect, computation time delay, circuit parameter uncertainty, and the constant power load (CPL), can lead to tracking errors that even result in instability in the output voltage of dual-active-bridge (DAB) converters. To address those challenges and improve the output performance, an uncertainty and disturbance estimator (UDE)-based robust voltage control scheme is proposed in this article. First, a generic dynamic model for DAB converters is proposed based on the converter output current to simplify the controller design, which integrates the DAB circuit model with the phase-shift control scheme. Then, the UDE-based voltage controller is presented based on the proposed model, and the stability performance is discussed in detail. With the CPLs, the output impedance of the UDE-controlled DAB converter is also modeled for the first time to show the stability boundary. Based on the derived stability criteria, the design of the UDE controller is summarized. A series of comparative experiment studies has been conducted, and the results prove that the proposed scheme can notably improve the voltage tracking performance and extend the stability boundary of the DAB converters when feeding CPLs even under significant parameter uncertainties.

A Modified Functional Observer-Based EID Estimator for Unknown Continuous-Time Singular Systems

This paper presents the design of a linear quadratic analog tracker (LQAT) based on the observer–Kalman-filter identification (OKID) method and the design of a modified functional observer-based equivalent input disturbance (EID) estimator for unknown square–non-square singular analog systems with unknown input and output disturbances. First, an equivalent mathematical model of the singular analog system is presented to simulate the time response of continuous-time linear singular analog systems to arbitrary inputs via the model conversion method. Then, for the unknown singular analog system, it constructs a linear quadratic analog tracker with state feedback and feed-forward gains based on the off-line OKID method. Furthermore, it extends the design methodology of the EID estimator for strictly proper regular systems with unknown matched–mismatched input and output disturbances to proper regular systems. It is important to mention that the newly developed modified functional observer for proper systems is used to estimate the unknown EID of singular analog systems and that the constraints on the dimensions of unknown disturbances can be eliminated by using the newly proposed EID estimation method. The contributions of this paper can be listed as follows: (1) based on both the OKID method and the discrete-to-continuous model conversion, the simulation of the time responses of the continuous-time linear singular models (which are not feasible using existing MATLAB toolboxes) become feasible; (2) for effective control of the unknown singular analog system, an off-line OKID method is proposed to design an LQAT with state feedback and feed-forward gains; and (3) based on the newly developed modified functional observer for the reduced-order proper regular system, the original EID estimator in the literature is newly extended to estimate the EID from the unknown strictly proper singular analog system, without the original dimensional constraints of the disturbances. It is important to mention that the disturbances of interest can be unknown matched–mismatched input and output disturbances.

Extended state observer-based adaptive dynamic sliding mode control for power level of nuclear power plant

It is well known that nuclear energy is a clean, safe, and reliable energy resource. Nuclear power plant is one of the prominent applications of nuclear energy. In this paper, aiming at improving the control performance for power level of nuclear power plant, an extended state observer-based adaptive dynamic sliding mode control (ESO-ADSMC) scheme is proposed. The mathematical model of nuclear reactor is firstly constructed based on point-reactor kinetics equations. Then, an extended state observer is designed to estimate both unmeasured states and output disturbances in real time, and the asymptotic convergence of the observer error state space is analyzed according to Routh-Hurwitz and Lyapunov stability theory. Subsequently, an adaptive dynamic sliding mode control approach is proposed for power level control of nuclear power plants in the presence of output disturbances, which is a combination of sliding mode control and backstepping control to enhance disturbance rejection ability. In addition, the chattering phenomenon is eliminated due to the discontinuous sign function contained in the first derivative of actual control input. Finally, simulation studies are carried out to demonstrate the feasibility and effectiveness of the proposed control strategy compared with backstepping control method in terms of the accuracy and rapidity of the response of power level, and robustness against output disturbances.

Predictor‐based adaptive feedback control for a class of systems with time delay and its application to an aircraft skin inspection robot

This study presents a predictor-based adaptive feedback control for a class of systems with a known input time delay, an arbitrary large unknown output time delay, unmeasurable states, unmodelled dynamics and disturbances. First, a predictor is employed to cope with the input time delay, and an input delay-free system was established. Then, to overcome the arbitrarily large unknown output time delay and unmeasurable states, an augmented descriptor observer is developed for the new delay-free system. Finally, an adaptive neural network is constructed to estimate the lumped unknown term by backstepping control and obtain the preliminary estimated model, which can compensate the unknown dynamic disturbances and the unmodelled dynamics in the backstepping iteration to achieve the desired tracking performance. In addition, to demonstrate the efficiency of the proposed scheme, the control of pressure difference is also implemented in the adsorption system of an aircraft skin inspection robot, and the simulation results verify the feasibility and effectiveness of the proposed control scheme.

Sensor Fault Reconstruction based on Adaptive Sliding Mode Observer for Forklift Fault-Tolerant Control System

For the problem of multiple sensor fault detection and reconstruction in the forklift fault-tolerant control system, a sliding mode observer (SMO) with adaptive regulation law is proposed. Based on the three-degree-of-freedom (3-DOF) model of forklift, a linear state equation with output disturbance is designed as its equivalent sensor fault model. The sensor fault is converted into an actuator fault by defining an auxiliary state variable as an output signal filter. Then the SMO-based method of sensor fault detection and reconstruction is given. Without knowing the upper bound of an unknown fault, an adaptive sliding mode observer (ASMO) can also be effective through the adaptive algorithm. Finally, experimental results further verify the effectiveness of the method, and provide a foundation for forklift fault-tolerant control.

Estimating the Flexibility Index of the Heat Exchanger Network by using the Confidence Level

This paper presents a new technique to estimate the heat exchanger network flexibility index by using a statistical method. This method identifies the true value under uncertainty. The flexibility of the heat exchanger network (HEN) is one of factors which affect the operability of the system. This method was applied by the following a sequential procedure. First, the disturbance propagation of HEN was studied by generating the linear model which presents the relationship between the output disturbance of the target temperature and the disturbance in the operation condition in input such as the supply temperature and the flow rate of the heat capacity. The matlab application was used to generate this equation. Second, the stream with low sensitivity to this disturbance was selected. Third, the confidence level for the lower disturbance this stream was calculated. This method was applied on three published cases and their results were compared with the results of the new method. The new method provides a simple way to calculate the flexibility index for large heat exchanger networks..