Sharif Digital Repository

In this work, design of an observer-based nonlinear controller for a class of single input-single output (SISO) systems in the general strict feedback form subject to input saturation based on the back-stepping technique has been addressed. A full order adaptive observer is constructed to estimate the unknown states and system parameters simultaneously. The proposed control scheme is singularity free and can handle the input nonlinearity. Asymptotical stability of the closed-loop system in the presence of observer dynamics and input saturation has been established by the Lyapunov stability theorem. The effectiveness of the proposed controller is illustrated by applying the proposed scheme to... 

Application of fractional order PID (FOPID) controller to an automatic voltage regulator (AVR) is presented and studied in this paper. An FOPID is a PID whose derivative and integral orders are fractional numbers rather than integers. Design stage of such a controller consists of determining five parameters. This paper employs particle swarm optimization (PSO) algorithm to carry out the aforementioned design procedure. PSO is an advanced search procedure that has proved to have very high efficiency. A novel cost function is defined to facilitate the control strategy over both the time-domain and the frequency-domain specifications. Comparisons are made with a PID controller and it is shown... 

In this paper, We propose concurrent learning adaptive controller, which uses recorded and current data concurrently for adaptation, to model reference adaptive control (MRAC) of uncertain switched systems. In standard MRAC architecture for switched systems, the adaptive update laws are derived based on the gradient descent scheme, but here we developed two novel parameter estimation schemes by using modification terms in adaptation laws in which recorded data is used simultaneously with current data and a triggering time is considered in which a sufficient condition on the linear independence of the recorded data is obtained to guarantee the exponential convergence of tracking error and... 

This article presents a robust adaptive fractional order proportional integral derivative controller for a class of uncertain fractional order nonlinear systems using fractional order sliding mode control. The goal is to achieve closed-loop control system robustness against the system uncertainty and external disturbance. The fractional order proportional integral derivative controller gains are adjustable and will be updated using the gradient method from a proper sliding surface. A supervisory controller is used to guarantee the stability of the closed-loop fractional order proportional integral derivative control system. Finally, fractional order Duffing–Holmes system is used to verify... 

In this Letter, we propose a fractional-order controller to stabilize the unstable fixed points of an unstable open-loop system. Also, we show that this controller has strong ability to eliminate chaotic oscillations or reduce them to regular oscillations in the chaotic systems. This controller has simple structure and is designed very easily. To determine the control parameters, one needs only a little knowledge about the plant and therefore, the proposed controller is a suitable choice in the control of uncertain chaotic systems. © 2007 Elsevier B.V. All rights reserved  

Robust stability analysis of multiorder fractional linear time-invariant systems is studied in this paper. In the present study, first, conservative stability boundaries with respect to the eigenvalues of a dynamic matrix for this kind of systems are found by using Young and Jensen inequalities. Then, considering uncertainty on the dynamic matrix, fractional orders, and fractional derivative coefficients, some sufficient conditions are derived for the stability analysis of uncertain multiorder fractional systems. Numerical examples are presented to confirm the obtained analytical results. Copyright © 2017 John Wiley & Sons, Ltd  

In this paper, a robust multivariable Model based Predictive Control (MPC) is proposed for the solution of load frequency control (LFC) in a multi-area power system. The proposed control scheme is designed to consider multivariable nature of LFC, system uncertainty and generation rate constraint, simultaneously. A constrained MPC is employed to calculate optimal control input including generation rate constraints. Economic allocation of generation is further ensured by modification of the predictive control objective function. To achieve robustness against system uncertainty and variation of parameters, a linear matrix inequality (LMI) based approach is employed. To validate the... 

A bilateral impedance controller is presented to enable robot-assisted surgery of a beating heart. For this purpose, two desired impedance models are designed and realized for the master and slave robots interacting with the operator (surgeon) and the environment (heart tissue), respectively. The impedance models are designed such that (a) the slave robot complies with the oscillatory motion of the beating heart and (b) the surgeon perceives the non-oscillatory portion of the slave/heart contact force at the master robot implying arrested-heart surgery. These performance goals are achieved via appropriate adjustment of the impedance model parameters without any measurement or estimation of... 

This paper presents a hierarchical Bayesian modeling framework for the uncertainty quantification in modal identification of linear dynamical systems using multiple vibration data sets. This novel framework integrates the state-of-the-art Bayesian formulations into a hierarchical setting aiming to capture both the identification precision and the variability prompted due to modeling errors. Such developments have been absent from the modal identification literature, sustained as a long-standing problem at the research spotlight. Central to this framework is a Gaussian hyper probability model, whose mean and covariance matrix are unknown, encapsulating the uncertainty of the modal parameters.... 

Different real-world processes can be described by a linear model parameterised with respect to the processoperating point, as an uncertain parameter. The family of transport processes with long memory is a kind of these processeswhich are characterised by the parameterised time-fractional diffusion equations. This study proposes a generalised isodamping feature for achieving the phase margin invariance regardless of the uncertain parameter variations in control of timefractional diffusion processes. Also, the study suggests an analytical method to tune stabilising fractional-order proportional-integral/proportional-derivative controllers for adjusting a desired value for the phase margin at... 

Stabilizing unstable periodic orbits of a deterministic chaotic system which is perturbed by a stochastic process is studied in this paper. The stochastic chaos is modeled by exciting a deterministic chaotic system with a white noise obtained from derivative of a Wiener process which eventually generates an Ito differential equation. It is also assumed that the chaotic system being studied has some model uncertainties which are not random. The sliding mode controller with some modifications is used for stochastic chaos suppression. It is shown that the system states converge to the desired orbit in such a way that the error covariance converges to an arbitrarily small bound around zero. As... 

Increasing the social welfare and achieving real competitive markets are the main purposes of consumers participation in electricity markets. Hence, Demand Response Programs (DRPs) have been designed to consider the consumers participation. One of these programs named Emergency Demand Response Program (EDRP) is based on consumers' responses to high electricity prices and to the incentives that are paid by Independent System Operators (ISOs) in the critical hours. In this paper, a model has been proposed for EDRP participation in the Stochastic Security Constrained Unit Commitment (SCUC) program. Both the spinning reserve and the demand side reserve, which is modeled as EDRP, are taken into... 

Million miles of gravity-fed drinking water and sewage pipelines around the world, especially in rural and urban areas in mountain ranges, have introduced a new renewable energy sources (RES), i.e., in-pipe hydropower systems (IHS). Output power of this technology, similar to other types of RES, suffers from intermittency, while it is still more predictable in comparison to other technologies of RESs. Besides, energy storage systems (ESS) are introduced as a pivotal technology for dealing with the intermittent and non-dispatchable characteristics of IHS through spatio-temporal arbitrage. This paper aims to develop a stochastic mixed-integer linear programming (MILP) formulation that... 

In this paper, a novel decentralized adaptive control scheme for multiagent formation control is proposed based on an integration of artificial potential functions with robust control techniques. Fully actuated mobile agents with partially unknown models are considered, where an adaptive fuzzy logic system is used to approximate the unknown system dynamics. The robust performance criterion is used to attenuate the adaptive fuzzy approximation error and external disturbances to a prescribed level. The advantages of the proposed controller can be listed as robustness to input nonlinearity, external disturbances, and model uncertainties, and applicability on a large diversity of autonomous... 

In this paper, an adaptive control scheme for multi-agent formation control is proposed. This control method is based on artificial potential functions integrated with adaptive fuzzy sliding mode control technique. We consider fully actuated mobile agents with completely unknown dynamics. An adaptive fuzzy logic system is used to approximate the unknown system dynamics. Sliding Mode Control (SMC) theory is used to force agents' motion to obey the dynamics defined by the simple inter-agent artificial potential functions. Stability proof is given using Lyapunov functions, which shows the robustness of controller with respect to disturbances and system uncertainties. Simulation results are... 

Deregulation in power systems has created new uncertainties and increased the previous ones. The presence of these uncertainties causes the transmission network to remain monopoly and the private investors not being interested in investing in this section. This paper presents a new merchant-based transmission expansion planning (TEP) formulation from the viewpoint of private investors. The information-gap decision theory (IGDT) is used to model the inherent uncertainties associated with the estimated investment cost of candidate lines and the forecasted system load and NSGAII is utilized to solve the multi-objective optimization problem. This algorithm helps private investors to select the... 

This paper describes the design and implementation of a H∞-based robust controller for a commercial 2MW variable-speed variable-pitch wind turbine. The single controller is able to deliver specification performance for the entire full load region. Various aspects of modeling and design procedures including reduced order model validation, torsional mode damping of drivetrain and uncertainty estimation are explained in detail. To make the design more reliable and industrially attractive, simple routines for the derivation of required weighting functions are introduced. To investigate the benefits of the suggested design, its closed-loop performance is compared with the wind turbine's baseline... 

The widespread presence of contingent generation, when coupled with the resulting volatility of the chronological net-load (i.e., the difference between stochastic generation and uncertain load) in today's modern electricity markets, engender the significant operational risks of an uncertain sufficiency of flexible energy capacity. In this article, we address several operational flexibility concerns that originate from the increase in generation variability captured within a security-constrained unit commitment (SCUC) formulation in smart grids. To quantitatively assess the power grid operational flexibility capacity, we first introduce two reference operation strategies based on a two-stage...