Sharif Digital Repository

This paper presents a multi-model robust control (MMRC) design for an offshore variable speed wind turbine with tension leg platform. The proposed control scheme covers the model uncertainty in the above rated wind speed, and it provides a reliable control for power regulation while minimizing the mechanical loads on the wind turbine structure. For this purpose, the above rated wind speed region is divided into several wind speed groups, and a set of linearized models are obtained from the Fatigue, Aerodynamics, Structures, and Turbulence (FAST) simulator for various mean wind speeds of each group. Using Weibull wind speed distribution, a nominal model with additive uncertainty is generated... 

In this article, a novel cooperative secondary voltage/frequency control considering time-varying delays and noises in fading channels is presented for an autonomous alternating current (AC) voltage sourced-based converter (VSC)-based microgrid (MG), including inverter-interfaced distributed generations (DGs). Fading phenomenon makes complex random fluctuations on the voltage and frequency of every DG received from its neighbor DGs. In multi-agent cooperative systems, in addition to the total additive noise and time-variant delay, a multiplicative complex random variable is considered to model the main received signal and its replicas due to multipath propagation. The proposed... 

This paper proposes a novel decentralized control approach for islanded direct-current (DC) microgrids (MGs) based on model predictive control (MPC) to regulate the distributed generation unit (DGU) output voltages, i.e. the voltages of the point of common coupling (PCC). A local controller is designed for each DGU, in the presence of uncertainties, disturbances, and unmodeled dynamics. First, a discrete-time state-space model of an MG is derived. Afterward, an MPC algorithm is designed to perform the PCC voltage control. The proposed MPC scheme ensures that the PCC voltages remain within an acceptable range. Several simulation studies have been conducted to illustrate the effectiveness of... 

This paper proposes a novel distributed noise-resilient secondary control for voltage and frequency restoration of islanded microgrid inverter-based distributed generations (DGs) with an additive type of noise. The existing distributed methods commonly are designed as secondary control system systems that operate on the assumption of ideal communication networks among DGs. However, the channels are prone to stochastic noise, whereas each DG obtains noisy measurements of the states of its neighbors via environmental noises. The existing distributed noise-resilient methods, ignore a complete model of the system. In contrast, this paper proposes consensus protocols that take into account both... 

This paper presents a two-level optimal control for the binary distillation column. From the control point of view, the binary distillation column is a high-order system consisting of several interconnected subsystems (trays) that aim to maximize output purity. Controlling the system in a hierarchical manner not only decreases complexity and solution time but also can improve the control structure's reliability. In this study, the distillation column is decomposed into NT second-order subsystems, each representing one stage (one tray). Accordingly, the cost function is decomposed, and thus, the overall problem is converted into NT lower-order subproblems where each tray has its own... 

This paper presents a new nonlinear current control strategy based on backstepping control and high-order sliding mode differentiator in order to employ distributed generation (DG) unit interfacing converters to actively compensate harmonics/interharmonics of local loads. The converter-based DG unit is connected to a weak grid (with uncertain impedance) and local load (that can be parametrically uncertain and topologically unknown) through an LCL filter. The proposed strategy robustly regulates the inverter output currents and delivers pure sinusoidal, three-phase balanced currents to the grid. The new controller demonstrates the robust performance and robust stability of the DG unit system... 

This paper presents a new nonlinear voltage control strategy based on backstepping control and a high-order sliding mode differentiator for an islanded microgrid. The microgrid consists of multiple distributed generation (DG) units with an arbitrary configuration that can be parametrically uncertain or topologically unknown. The proposed controller robustly regulates the microgrid voltages in the presence of parametric uncertainties, unmodeled dynamics, load imbalances, and nonlinear loads with harmonic/interharmonic currents. In contrast to existing methods, the controller does not need to know the frequency of harmonic and interharmonic current of microgrid loads that lead to the reduction... 

In this paper, a new fuzzy based Model Coordination (F-MC) strategy is proposed for hierarchical control of large-scale systems (LSS). To solve the overall problem with a two-level optimal control strategy, we first decompose the system into several sub-systems at the first level. Then, at the second level, a fuzzy coordinator will be used to predict the interaction between subsystems. The proposed fuzzy based coordination approach is applicable to all types of LSS. Although in this paper, an optimal control of a 2DOF robot manipulator, as a LSS, will be considered. The obtained results are compared with the centralized optimization  

In large-scale power systems, classical centralized control approaches may fail due to geographically distribution of information and decentralized controllers result in sub-optimal solution for load-frequency control (LFC) problems. In this paper, a two-level structure is presented to obtain optimal solution for LFC problems and also reduce the computational complexity of centralized controllers. In this approach, an interconnected multi-area power system is decomposed into several sub-systems (areas) at the first-level. Then an optimization problem in each area is solved separately, with respect to its local information and interaction signals coming from other areas. At the second-level,... 

This paper is concerned with the disturbance attenuation problem of fuzzy large-scale systems which consist of N interconnected subsystems which are represented by Takagi-Sugeno fuzzy models. Using Lyapunov function and linear matrix inequalities (LMIs), a criterion is proposed to have a prescribed level of disturbance attenuation. A numerical example is given to illustrate the control design procedure and its effectiveness  

This study presents a motion planning algorithm to generate a feasible periodic solution for a hybrid system describing running by a three-dimensional (3-D), three-link, three-actuator, monopedal robot. In order to obtain a symmetric running gait along a straight line, the hybrid system consists of two stance phases and two flight phases. The motion planning algorithm is developed on the basis of a finite-dimensional optimisation problem with equality and inequality constraints. By extending the concept of hybrid zero dynamics to running, the authors propose a time-invariant control scheme that is employed at two levels to locally exponentially stabilise the generated periodic solution for... 

The main objective of this paper is to investigate the stability and stabilization problem of fuzzy large-scale systems in which the system is composed of a number of Takagi-Sugeno fuzzy subsystems with interconnection. Instead of fuzzy parallel distributed compensation (PDC) design, nonlinear state feedback controllers are used in stabilization of the overall large-scale system. Based on Lyapunov stability theory, linear matrix inequalities (LMIs) conditions are derived for asymptotic and exponential stability. Two numerical examples are given to confirm the analytical results and illustrate the effectiveness of the proposed strategy  

A repeated inflation-unemployment game within the linear-quadratic frame-work of Barro and Gordon is studied assuming that the government would like to cheat optimally and the finite heterogeneous population of private agents attempts to learn the government's targets using a reinforcement learning algorithm. Private agents are heterogeneous in their initial expectations of inflation rate but are assumed to utilize an identical anticipatory reinforcement learning process, namely Q-learning. In our heterogeneous setting, the only way for the private agents to achieve a zero value for their loss function, is for all of them to correctly anticipate the Nash equilibrium. It is of particular... 

The purpose of this paper is to deal with a novel intelligent predictive control scheme using the multiple models strategy with its application to an industrial tubular heat exchanger system. The main idea of the strategy proposed here is to represent the operating environments of the system, which have a wide range of variation in the span of time by several local explicit linear models. In line with this strategy, the well-known linear generalized predictive control (LGPC) schemes are initially designed corresponding to each one of the linear models of the system. After that, the best model of the system and the LGPC control action are precisely identified, at each instant of time, by an... 

A repeated inflation-unemployment game within the linear-quadratic framework of Barro and Gordon is studied assuming that the government would like to cheat optimally and the finite heterogeneous population of private agents attempts to learn the government's targets using a reinforcement learning algorithm. Private agents are heterogeneous in their initial expectations of inflation rate but are assumed to utilize an identical anticipatory reinforcement learning process, namely Q-learning. In our heterogeneous setting, the only way for the private agents to achieve a zero value for their loss function, is for all of them to correctly anticipate the Nash equilibrium. It is of particular... 

This paper deals with the problem of multi-agent learning of a population of players, engaged in a repeated normal-form game. Assuming boundedly-rational agents, we propose a model of social learning based on trial and error, called "social reinforcement learning". This extension of well-known Q-learning algorithm, allows players within a population to communicate and share their experiences with each other. To illustrate the effectiveness of the proposed learning algorithm, a number of simulations on the benchmark game of "Battle of Sexes" has been carried out. Results show that supplementing communication to the classical form of Q-learning, significantly improves convergence speed towards... 

This work deals with the problem of controlling the outlet temperature of a tubular heat exchanger system by means of flow pressure. The usual industrial case is to try to control the outlet temperature by either the temperature or the flow of the fluid, which flows through the shell tube. But, in some situations, this is not possible, due to the fact that the whole of system coefficients variation cannot quite be covered by control action. In this case, the system behavior must precisely be modeled and appropriate control action needs to be obtained based on novel techniques. A new multiple models control strategy using the well-known linear generalized predictive control (LGPC) scheme has... 

In traditional game theory, the players play with policy of maximizing their payoffs. In real world, there are many situations where payoffs have uncertainty and are fuzzy in nature. In this paper, a new method for finding pure strategy Nash equilibriums, to realistically analyze the games with fuzzy payoffs is investigated. Using ranking fuzzy numbers, a fuzzy preference relation is constructed over payoffs. The priorities of payoffs are considered as the degree of being Nash equilibriums  

Presented is a novel approach for designing continuous-time update laws to update the parameters of stabilising controllers during continuous phases of bipedal walking such that (i) a general cost function, such as the energy of the control input over single support, can be minimised in an online manner, and (ii) the exponential stability of the corresponding limit cycle for the closed-loop impulsive system is not affected. Formally, a class of update laws with a radial basis step length is developed to minimise a cost function in terms of the stabilising controller parameters and initial states of the mechanical system  

The purpose of the paper presented here is to control the fluid temperature that flows in the inner tube of a tubular heat exchanger system by means of the fluid flow pressure. This system in its present form has a specified range of the coefficients' variation, while the temperature of the outlet fluid could generally be controlled by either the temperature or the flow of the inlet fluid flowing in the shell tube. The control realization for the system presented is often complicated, because the variation of the system coefficients and the reference signal must be thoroughly covered by the control action. In such a case, the system behaviour must first be represented by the multiple...