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This study introduces a proposed control method for microgrids (MGs) in islanded (off-grid) mode. The proposed control method is developed by modifying the droop control method using H-infinity controller. In this control method, the droop control loop, current and voltage control loops are adjusted to respond to system load variation. The proposed method is an adaptive control one as it regulates the system voltage and frequency to their nominal values after system load variations. Also, it is a repetitive control method as it depends on the internal model principle that provides good performance for voltage and current error tracking. To prove the applicability and effectiveness of the proposed method, it is applied to a test system using MATLAB/Simulink under three different loading conditions. The results are compared with those of droop control and they prove the effectiveness of the proposed method in adjusting MGs under the off-grid mode of operation. Also, a system stability analysis is performed based on root locus and system step response. Robustness analysis is performed to prove the ability of the proposed controller to restore the system performance after the fault clearance.

In this study, a DC micro-grid consisting of multiple paralleled energy resources interfaced by both bidirectional AC/DC and DC/DC boost converters and loaded by a constant power load (CPL) is investigated. By considering the generic dq transformation of the AC/DC converters' dynamics and the accurate nonlinear model of the DC/DC converters, two novel control schemes are presented for each converter-interfaced unit to guarantee load voltage regulation, power sharing and closed-loop system stability. This novel framework incorporates the widely adopted droop control and using input-to-state stability theory, it is proven that each converter guarantees a desired current limitation without the need for cascaded control and saturation blocks. Sufficient conditions to ensure closed-loop system stability are analytically obtained and tested for different operation scenarios. The system stability is further analysed from a graphical perspective, providing valuable insights of the CPL's influence onto the system performance and stability. The proposed control performance and the theoretical analysis are first validated by simulating a three-phase AC/DC converter in parallel with a bidirectional DC/DC boost converter feeding a CPL in comparison with the cascaded PI control technique. Finally, experimental results are also provided to demonstrate the effectiveness of the proposed control approach on a real testbed.

The design of output constrained control system for unmanned aerial vehicles deployed in confined areas is an important issue in practice and not taken into account in many autopilot systems. In this study, the authors address a neural networks-based adaptive trajectory tracking control algorithm for multi-rotors systems in the presence of various uncertainties in their dynamics. Given any sufficient smooth and bounded reference trajectory input, the proposed algorithm achieves that (i) the system output (Euclidean position) tracking error converges to a neighbourhood of zero and furthermore (ii) the system output remains uniformly in a prescribed set. Instead of element-wise estimation, a norm estimation approach of unknown weight vectors is incorporated into the control system design to relieve the onboard computation burden. The convergence property of the closed-loop system subject to output constraint is analysed via a symmetric barrier Lyapunov function augmented with several quadratic terms. Simulation results are demonstrated on a quadrotor model to validate the effectiveness of the proposed algorithm.

This study is concerned with the event-triggered control for networked control systems via dynamic output feedback controllers (DOFCs). The output measurement signals of the physical plant are sampled periodically. An output-based discrete event-triggering mechanism is introduced to choose those only necessary sampled-data packets to be transmitted through a communication network for controller design. Under this event-triggering mechanism, the resultant closed-loop system is first modelled as a linear system with an interval time-varying delay. Then a novel stability criterion is established by employing the Lyapunov–Krasovskii functional approach. Based on this stability criterion, a new sufficient condition is derived to co-design both the desired DOFCs and the event-triggering parameters. Finally, a satellite control system is taken to show the effectiveness of the proposed method.

An input constrained adaptive tracking controller is designed for flapping micro aerial vehicles, wherein the moving averaging filter is adopted to estimate the averaged states of the system. Specifically, in the outer loop controller, an observer is constructed to estimate the disturbances within the system. Moreover, the constrained thrust is designed to keep the frequency in a proper region so as to meet the requirement of average estimation. Then, a tracking differentiator is used to provide trackable trajectories for the inner loop. Subsequently, a new quaternion-based hybrid attitude tracking controller is designed which successfully deals with high-frequency noises and avoids possible chattering. As supported by mathematical analysis, the proposed control strategy guarantees the uniform ultimate boundedness of the closed-loop system, and it keeps the control torques within the permitted range to meet the application requirement. At last, numerical simulations are carried out to support the validity of the proposed controller, whose results are satisfactory even when the thrust and torques are saturated.

Microgrid (MG) technology evolves as a promising solution to deal with the intermittent renewable generations and frequently changing load demand. This paper proposes a fully distributed and bounded secondary control algorithm with flexible convergence time for voltage and frequency restoration. It also enables accurate active power sharing for an islanded MG, compared with the well-known consensus-based distributed control approach. The proposed control scheme achieves accelerated fixed-time convergence. The upper bound on the convergence is established by using the Lyapunov stability theory. The bounded, distributed control approach restores the voltage and frequency in fixed-time while sharing the active power precisely. Further, the proposed controller is adaptive to the communication topology change and supports the plug and play feature of MG. Extensive simulations have been pursued using MATLAB/SimPowerSyetem toolbox considering frequent load perturbation and communication topology change. The obtained results are analysed to verify the performance of the proposed control algorithm. It is observed that the proposed bounded input controller converges faster than the conventional method.

Stability of a standalone hybrid power system (HPS) in a smart grid is always a challenging task. Further, the operational stability of the power system depends on the associated communication infrastructure. Therefore, it is always crucial to pick up a controller that can assure system's stability along with performance, despite disturbances like (load and input wind variations) with communication delays. Present study focuses on reactive power management and voltage stability issues of an isolated HPS. The stability aspects of HPS are improved through reactive power compensation, by custom power devices like static var compensator. The control aspects of SVC as well as the whole hybrid system are taken care by H∞ linear matrix inequalities approach. Further, H-infinity control, Lyapunov stability along with linear matrix inequalities techniques estimate the delay boundary of controllers. The iterative performance of the proportional–integral–derivative controllers, and robust H∞ damping controller of the HPS, are designed through LMI approach. Later experimental study of the HPS is done, with a prototype model in dSPACE real-time control environment. In this case, dSPACE 1104 is added for data acquisition and control. Adaptability and robustness of the proposed controllers are verified under fluctuating loads and uncertain wind power input.

Among all converters, one of the most prominent technologies employed in multi-infeed ac/dc (MIACDC) smart grids is the modular multilevel converters (MMCs). The core part of the MIACDC grids is their dc-voltage power port. All MMC's components in a dc-voltage power port – which are capable of significantly impacting on the dynamics – are mathematically modelled in the space-phasor representation using the rotating dq-frame. Afterwards, the effects of each submodule capacitors and arm inductors on the dc-voltage power port's dynamics are investigated and analysed, separately. This paper mathematically shows that the former is affecting the low-frequency range of the bandwidth, and the latter is impacting on the high-frequency one. Moreover, this paper demonstrates that a robust, optimal controller synthesized by the µ-analysis is a good candidate to induce both robust stability and performance in an MMC-based dc-voltage power port. In order to illustrate the contributions of this article, detailed mathematical analyses; comparative results simulated by the switching model of MMC; and experimental results produced by a test rig, which is able to examine the transient performance of an MMC-based dc-voltage power port, are provided. For comparison, the results of the PI-Lead controller and those of another controller optimally synthesized have been provided.

Networked control systems (NCS) have become an emerging and important research area given the rapidly developing network communication technology. Numerous studies in this area concentrate on the stability of control systems, while little has been done on its performance analysis, especially the index of an optimal control system. We fill this gap here by analysing the optimal tracking performance for an NCS that has quantitative control inputs over feedback channels. We design a dual‐degree‐of‐freedom controller along with an optimal control system, by applying the Youla parameterization method based on the time domain and coprime decompositions. The proposed methodology is assessed by numerical simulations. The system's tracking performance is found to be deteriorated by the unstable poles and non‐minimum phase zeros of the controlled object, as well as by quantization signal errors. These findings are beneficial for analysing and designing practical control systems. This paper focuses on the performance analysis of networked control systems, specifically addressing the optimal tracking performance with quantitative control inputs over feedback channels. A dual‐degree‐of‐freedom controller is designed using the Youla parameterization method, and the system's performance is assessed through numerical simulations. The findings highlight the impact of unstable poles, non‐minimum phase zeros, and quantization errors on tracking performance, offering insights for practical control system design.