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This research investigates the position control of spherical charged particles suspended in a directly simulated homogeneous isotropic turbulence, which has the potential to improve the efficiency of the electrostatic precipitators (ESPs) in removing gaseous pollutants. To do this, the electric field used in ESPs is controlled by the sliding mode control method to steer the particles toward their desired positions. The particles are charged using the field charging method, which leads to electrical interactions between them. Employing the linked-list method reduces the computational cost related to these interaction forces. The dynamics of particles is simulated using the Maxey–Riley equation including the control force. Coupling the direct numerical simulation solver with the proposed control method and the linked-list scheme, along with solving the particle dynamics, complicates the problem from a control theory point of view. The robustness of the proposed model-free control method leads to overcoming disturbances and uncertainties in the simulation due to turbulence and repulsive electric forces. Hence, steering a large number of charged particles to places with more pollution concentration or increasing the duration of exposure of the particles to gaseous pollutants becomes possible. The findings of the present research are pertinent to improving the performance of air purification equipment. [ABSTRACT FROM AUTHOR]

This paper proposes a robust output feedback-based controller for a class of uncertain linear network-based control systems. This method ensures the stability, robustness and an output regulation against the modelling uncertainties and communication network negative effects. In this way, a switching sliding surface is proposed and designed using a switched quadratic Lyapunov functional, by solving a set of linear matrix inequalities. A method is then proposed to reach the quasi-sliding mode and stay thereafter. Simulation studies on four benchmark problems show the effectiveness of the proposed method with respect to the model uncertainties and also band-limited communication network deficiencies. [ABSTRACT FROM AUTHOR]

In this paper, the robust vibration control of a rotating carbon nanotube reinforced composite beam subjected to a temperature rise is studied. The governing mathematical partial differential equations are derived by Hamilton’s principle based on Euler–Bernoulli beam theory. The Galerkin method is then used to obtain the temporal ordinary differential equations and therefore to perform vibration analysis. For the purpose of vibration control, piezoelectric patches are used as sensors to measure the displacement of the beam and as actuators to implement control forces. A model-free adaptive fuzzy sliding mode controller is utilized to suppress the vibration of the rotating carbon nanotube reinforced composite beam. Since the plant’s state vector cannot be measured for control purposes and only the piezoelectric sensor’s output is available, a model-free adaptive fuzzy sliding mode observer is proposed here. Simulation studies demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper proposes a robust control strategy for robust tracking and model-following of a class of uncertain linear discrete-time systems. This method is based on the discrete-time sliding mode control and ensures stability, robustness and output tracking against the modelling uncertainties even for large sampling periods. In this way, two strategies are used: firstly, the well-known Lyapunov theory is used to achieve a set of linear matrix inequalities, which is then utilized to design the sliding surface; secondly, a control input is designed to reach the quasi-sliding mode. Simulation studies show the effectiveness of the proposed method in the presence of parameter uncertainties. [ABSTRACT FROM AUTHOR]

In this paper, active vibration control of carbon nanotube reinforced composite beams subjected to a temperature rise is studied. For this purpose, piezoelectric patches are used as sensors to measure the displacement of the beam and as actuators to implement control forces. The governing equation of motion of this beam is derived from the Euler–Bernoulli theory and Hamilton’s principle. Galerkin’s method is utilized to obtain the temporal ordinary differential equations. An optimal observer-based output feedback controller is designed by the linear quadratic regulator (LQR) methodology to ensure closed-loop stability. Simulation studies demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, the optimal vibration control of a rotating, pre-twisted, single-celled box thin-walled beam made of functionally graded material is discussed. This beam is under aerothermoelastic loading and warping restraint. A first-order shear deformation theory enabling satisfaction of traction-free boundary conditions is employed to achieve governing dynamical model. These equations include the effects of the presetting angle, the secondary warping, temperature gradient through the wall thickness of the beam, and also the rotational speed. Moreover, quasi-steady aerodynamic pressure loadings are determined using first-order piston theory, and steady beam surface temperature is obtained from gas dynamics theory. The extended Galerkin method is then used to transform the blade partial differential equations into a set of ordinary differential equations. Transversely isotropic sensor-actuator piezoelectric pairs that are surface embedded along the blade are also considered for the purpose of closed-loop control. An optimal observer-based output feedback control scheme is used to stabilize the closed-loop system. Simulation studies demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents a new method for control of linear networked systems by combining the predictive control and the variable sampling period approaches. In this way, event-driven sensors are implemented, i.e. by construction the sensors are triggered to sample the outputs of the plant, when new control input signals are received by the actuators. In light of this formulation, at each sampling instant, total control loop delay will be equal to the sampling period which is unknown. In order to deal with the network effects associated with a range of pre-specified time delays, appropriate step invariant discrete-time models of the networked plant are calculated offline. Based on these, some stabilizing control signals are constructed online. The control signals are then packed in the control-side packet, transmitted back to the plant side and received by a time delay compensator module. A less conservative class of Lyapunov functions, called switched quadratic Lyapunov, is used here for stability analysis and stabilizing controller design. Simulation studies on well-known benchmark problems demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper is concerned with the networked control of a class of uncertain nonlinear systems. In this way, Takagi–Sugeno (T-S) fuzzy modelling is used to extend the previously proposed variable selective control (VSC) methodology to nonlinear systems. This extension is based upon the decomposition of the nonlinear system to a set of fuzzy-blended locally linearised subsystems and further application of the VSC methodology to each subsystem. To increase the applicability of the T-S approach for uncertain nonlinear networked control systems, this study considers the asynchronous premise variables in the plant and the controller, and then introduces a robust stability analysis and control synthesis. The resulting optimal switching-fuzzy controller provides a minimum guaranteed cost on an H2performance index. Simulation studies on three nonlinear benchmark problems demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]