Presence Of Different Disturbances Research Articles

Output consensus design in clustered networks of heterogeneous linear MASs under disturbances

This paper focuses on the output consensus problem over a clustered network of heterogeneous agents. We are interested in the case where the communication topology is a fixed, directed graph within each cluster and a strongly connected, directed graph among clusters. Besides, each cluster has a leader that can instantly communicate with other leaders in different clusters. The heterogeneous agents’ goal is to achieve output consensus under the presence of different disturbances on agents. We propose a novel output consensus protocol. Each agent has an observer, allowing the reconstruction of the state and disturbances, and a virtual model, which considers both the continuous communication within the virtual clusters and discrete information across the inter-virtual cluster. We establish the equivalence between the output consensus over the clustered network and the virtual models’ consensus on the virtual clustered network. A sufficient condition for the consensus on virtual models based on matrices and graph theories is derived. Moreover, we provide a sufficient and necessary condition for the clustered network’s output consensus under different disturbances. Finally, we validate our theoretical results through an illustrative example.

Generalised model predictive controller design for A DC–DC non‐inverting buck–boost converter optimised with a novel identification technique

An on-line generalised model predictive control (GMPC) strategy is designed and optimised with a novel identification procedure in the presence of different disturbances. The principle of MPC is utilising a discrete-time model of a system to reach the control variables with a prediction over these values, which is followed by computing a cost function for the control aims. Non-inverting buck–boost converter is a non-minimum phase system based on its boost mode, which makes a challenging condition for designing a stable controller. The proposed control technique described in this paper removes the requirement for a system mathematical model adopting a black-box identification method which can decrease the computational burden. Numerous harmful disturbances can affect a DC–DC converter; thus, the GMPC scheme is used along with a novel improved exponential regressive least identification algorithm as an adaptive strategy for the controller to optimise the gains of the controller in an on-line way resulting in better disturbance rejection. A PID controller with particle swarm optimisation algorithm is designed for this converter to be compared with the GMPC controller. Finally, the efficiency of the GMPC is verified in various performances with experimental and simulation results.

Generalised predictive controller (GPC) design on single‐phase full‐bridge inverter with a novel identification method

The design of an on-line generalised predictive control (GPC) technique with a novel identification method is presented in this paper for a single-phase full-bridge inverter in the presence of different disturbances. The controller uses system discrete-time model to reach the control variables with a prediction over these values, followed by computing a cost function for control aims. However, in this controller, the need for the mathematical model of the system is removed since the black-box identification strategy is used. Moreover, GPC structure has many advantages including low computational complexity, systematic design procedure, and fixed switching frequency that makes it a good alternative for practical applications. Various disturbances can have a negative impact on a DC–AC inverter; thus, considering robust dynamics and ease of implantation, the GPC scheme is used along with an improved exponential regressive least square identification algorithm as an adaptive strategy in the controller. Moreover, the prediction horizons of this controller have been increased, resulting in its low steady-state error and better performance. Furthermore, harmonics in the sinusoidal signal can decrease the total efficiency of the system; thus, an LC filter is used to reduce the level of total harmonic distortion. However, the stability of the filter is the most challenging issue in designing a suitable controller. Finally, the strength of the current controller is verified using experimental and simulations results.

Adaptive neuro‐fuzzy inference systems (ANFIS) controller design on single‐phase full‐bridge inverter with a cascade fractional‐order PID voltage controller

AbstractAdaptive neuro‐fuzzy inference system (ANFIS) technique is a significant alternative of research which is structured with a combination of two soft‐computing strategies of fuzzy logic and artificial neural network. The design of ANFIS controller for a single‐phase full‐bridge inverter with pulse width modulation is demonstrated here in the presence of different disturbances. Moreover, an LC filter is designed to decrease the disturbing harmonics which the stability of the filter can be noted as an important issue. Based on the fuzzy C‐mean clustering method used for decreasing fuzzy rules, the computational burden has been improved resulting in faster dynamic performance. This method considers the system as a black‐box structure which omits the need for an exact model of system and can be an appropriate technique for ill‐defined systems. Additionally, to deal with the variations of supply DC voltage, a fractional‐order proportional‐integral‐derivative controller is designed which is tuned by particle swarm optimiser algorithm and can generate a sinusoidal reference for the system input. This double‐loop control technique is known as cascade control strategy. It can be seen that ANFIS scheme provides appropriate results with less computational burden and simple structure with optimised responses in challenging conditions. The capability of the proposed method is validated for different operating conditions through simulation and experimental results.

Optimised Time for Travelling Wave Fault Locators in the Presence of Different Disturbances Based on Real-World Fault Data

The real-world travelling wave fault data investigated in this paper indicate disturbances generate unpredictable, non-stationary and random waveforms which may cause maloperation of protection and control elements in a power system including travelling wave fault locators (TWFL). This type of fault locator is directly dependent on the detection of an accurate time of arrival (ToA) of travelling waves (TW) generated by a fault. This detection becomes complicated in the presence of disturbances when their ToAs are detected earlier than the fault TWs. Since travelling waves occur in the high-frequency bands (e.g. >50 kHz), in this paper a capacitor voltage transformer is employed to measure the TW voltage signals; this involves acquiring the current flowing to the ground and removing the low-frequency components (50/60 Hz). Disturbances create high magnitude pulses in the pre-fault section of a TW fault signal that last for a short time. Therefore, the time when a TWFL starts its computations requires to be optimised so that the effect of the disturbances is eliminated. The analysis techniques mentioned in this paper are based on real-world travelling wave fault data, and the solution uses statistical tools, such as cost function, mean and standard deviation, alongside Digital Signal Processing algorithms.

Interarea Power System Oscillations Damping via AI-based Referential Integrity Variable-Structure Control

Abstract The design of power system stabilizer (PSS) is load-dependent and needs continuous adjustment at each operating condition. This paper aims at introducing a robust non-fragile PSS for interconnected power systems. The proposed controller has the capability of adaptively tuning online its rule-base through a variable-structure direct adaptive control algorithm in order to rigorously attain the desired objectives. The PSS controller acts on damping the electromechanical modes of oscillations not only through a wide range of operating conditions but also in presence of different disturbances. Using MATLABTM-Simulink, simulation results significantly verify that the proposed controller provides favorable performance and efficiently contributes towards enhancing the system dynamic behavior when applied to the four machines two-area power system that mimics the typical system behavior in actual operation. The interaction between the variable-structure adaptive fuzzy-based power system stabilizer (VS-AFPSS) and the existed typical ones inside the interconnected power systems has been explicitly discussed. Compared to other conventional controllers, VS-AFPSS enables better damping characteristics to both local and inter-area oscillation modes considering different operating conditions and sever disturbances.

Studies on resilient control through multiagent consensus networks subject to disturbances.

Resiliency is one of the most critical objectives found in complex industrial applications today and designing control systems to provide resiliency is an open problem. This paper proposes resilient control design guidelines for industrial systems that can be modeled as networked multiagent consensus systems subject to disturbances or noise. We give a general analysis of multiagent consensus networks in the presence of different disturbances from the input-to-output stability point of view. Using a nonsingular linear transformation, some necessary and sufficient results are established for disturbed multiagent consensus networks by taking advantage of the input-to-state stability theory, based on which the disturbance rejection performance is analyzed in three cases separated by the spaces of disturbances and state disagreements between agents. It is shown that the linear matrix inequality technique can be adopted to determine the optimal disturbance rejection indexes for all the three cases. In addition, two illustrative numerical examples are given to demonstrate the derived consensus results for different types of directed graphs and subject to different classes of disturbances.

μ-Synthesis and Hardware-in-the-loop Simulation of Miniature Helicopter Control System

The aim of this paper is to describe in detail the μ-synthesis of a miniature helicopter integral attitude controller of high order and to present results from the hardware-in-the-loop simulation of this controller implementing Digital Signal Processor. The μ-controller designed allows to suppress efficiently wind disturbances in the presence of 25 % input multiplicative uncertainty. A simple position controller is added to ensure tracking of the desired trajectory in 3D space. The results from hardware-in-the-loop simulation are close to the results from double-precision simulation of helicopter control system in Simulink®. The software platform developed allows to implement easily different sensors, servoactuators and control laws and to investigate the closed-loop system behavior in presence of different disturbances and parameter variations.

Modelling and controlling of critical dimension in semiconductor manufacturing

As critical dimension (CD) in semiconductor device is always shrinking, it brings us many difficulties to control it. Since lithography and etch are all pivotal steps of CD, it is critical to identify, manage and minimise the major sources of variation of lithography and etch in the presence of different disturbances. Therefore, in this paper, two linear model predictive controllers (LMPCs) are formulated – the lithography CD controller and the etch CD controller on the basis of presenting a comprehensive study of the advantages and disadvantages of current methods of controlling of CD. The lithography CD controller manipulates multiple inputs – dose and focus, the etch CD controller manipulates etch time and Kalman filtering technologies are used to estimate state variables. The simulations of the two CD controllers designed are performed considering different types of disturbances and a comparison of performance of LMPCs and exponentially weighted moving average (EWMA) is presented. The results show that there is a significant reduction of the effect of the disturbances on CD and the two controllers are flexible and robust controllers with superior control ability to control CD.

On the design of adaptive autopilots for a launch vehicle

Three efficient and practical approaches for the design of an adaptive autopilot for a launch vehicle (LV) attitude control system during atmospheric flight are presented. The proposed adaptive control schemes are developed on the basis of different combinations of gain scheduling, decoupling, and the model reference adaptive technique. A new adaptation mechanism based on hyperstability theory is developed. Every scheme contains some degree of adaptation, corresponding to its complexity and cost of realization. A six-degree-of-freedom non-linear simulation was used to compare the adaptation characteristics of the proposed schemes in the presence of different disturbances during atmospheric flight of the vehicle.

Influence on Power Quality Measurement of the Simultaneous Presence of Different Disturbances

Influence on Power Quality Measurement of the Simultaneous Presence of Different Disturbances