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This paper addresses a non-interacting torque control strategy to decouple the d- and q-axis dynamics of a permanent magnet synchronous machine (PMSM). The maximum torque per ampere (MTPA) method is used to determine the reference currents for the desired torque. To realize the noninteracting control, knowledge concerning the inductances L_d and L_q of the electrical machine is necessary. These two inductances are estimated by two extended Kalman filters (EKFs), which use a univariate polynomial as a model to describe the saturation effects of the PMSM. The Kalman filters (KF) are realized within a noninteracting control system to improve the observability of the inductance. Despite the non-perfect decoupling, thanks to the structural stochastic nature of the KFs, noninteracting cancellation errors are represented with its process noise and the inductances are estimated sufficiently well. In this sense, we can speak about KFs for and within noninteracting control. Estimating inductances is fundamental for optimal torque control, which is a viable approach to reducing mechanical vibration and disturbance. Moreover, the control strategy of model-based techniques must be adaptively tuned to work properly. Starting from the existing literature, a viable control structure is proposed in which the stability of the control loop using a Proportional Integral (PI) controller is shown for the resulting time-varying system. In fact, the model is represented as a time-varying system because of the presence of the variable inductances L_d and L_q and because of the presence of the velocity of the rotor which is not considered as a state. In this paper, a forward Euler discretization is used to realize the observer in the discrete experimental setup. Measures realized with hardware in the loop (HIL) show interesting results in the context of inductance estimation, due to the advantage of the reduction of the dimensions of the two decoupled EKFs resulting from the noninteraction control. Using the HIL simulator, the proposed torque control strategy is investigated, showing promising results in terms of increasing observability due to decoupling. This and the usage of univariate polynomials in EKF calculations lead to significant reduction of measurement points, reduction of oscillations and ripples, deviation between desired and achieved torque and reduction of disturbances. Moreover, the proposed control strategy using a very limited calculation load, at the same time, maintains the ripples inside the technical limits of the obtained torque. Both effects are due to the decoupled EKFs with simplified and reduced order of the models using univariate polynomials, which require significantly fewer measuring points in the run-up to the creation of the model of the inductances L_d and L_q.

Favorable neighboring interactions and economical transmission costs are the foundations of formation-containment control (FCC), while the complex marine environments hamper its expansion on networked unmanned surface vehicles (USVs). In this context, this paper investigates an intermittent dynamic event-triggered control scheme for USVs experiencing communication interruptions to achieve FCC. Specifically, the control architecture consists of two synchronously working sub-layers. In the first layer, an intermittent communications-based formation tracking controller is initially developed to endow USVs with higher endurance against communication interruptions, such that the leader USVs can form a desired formation pattern while following a virtual leader. Meanwhile, a dynamic event-triggered mechanism (DETM) is incorporated into the intermittent controller to reduce the update frequency of control signals with computable minimum inter-event time (MIET). Similarly, an intermittent DETM-based controller is proposed for followers to achieve containment missions in the second layer. Moreover, the global information is unnecessary with time-varying control gains. Finally, the simulations are provided to verify the effectiveness and superiority of the proposed control scheme.

A degradation modeling method of marine gas turbines for the overhaul cycle is proposed to address the problem of insufficient data sets for fault diagnosis and trend prediction algorithm validation. First, a nonlinear model of the marine three-shaft gas turbine gas path was established. The degradation path and component degradation models were subsequently obtained. The distribution of the washing cycle and degradation factors in the overhaul cycle were solved using an optimization algorithm, and degradation data in the washing cycle were obtained. The model's feasibility is validated with a segment of actual degradation data. The change rule of the gas turbine operating data during the overhaul cycle was also obtained. The degradation data of marine gas turbines under different boundary conditions are simulated using the established degradation model. This model provides data sets essential for validating fault diagnosis and trend prediction algorithms. Furthermore, it provides a reference for modeling the degradation of other mechanical equipment.

This paper presents an active disturbance rejection control (ADRC) approach for three-phase four-legs voltage source inverters (FL-VSIs) in a standalone renewable energy resources (RES)-based islanded microgrid. The key purpose of the proposed approach is to improve the control robustness against load-side disturbances, power supply parameters uncertainties, and faulty operating conditions. Indeed, a notable benefit of ADRC is its ability to operate effectively without the need for precise knowledge of disturbance characteristics or accurate modeling and FL-VSI parameters. As compared with conventional PI controllers, this advanced control strategy allows improving the voltage waveforms quality and conforming to existing power quality standards and metrics while using only output voltage sensors. Extensive simulations on Matlab/Simulink software have been conducted to assess the effectiveness of the proposed approach.

This paper presents the first study of the global stabilization of subfully actuated systems (sub-FAS) by hybrid impulsive control method. Since sub-FAS contain singular sets, controllers designed by the conventional high-order fully actuated (HOFA) system approach may not be feasible for all initial conditions in the state space. Different from existing studies that constrain initial conditions to achieve substabilization, we devise a hybrid controller via the HOFA system approach and state-dependent impulsive control method, addressing the global stabilization problem without constraints on the initial states. By transforming sub-FAS into hybrid systems through the hybrid controller, we obtain some criteria for global stabilization of the sub-FAS. It is noted that both stabilizing and destabilizing impulses are used to overcome the singular sets in the sub-FAS. Finally, two examples illustrate the proposed approach.

Due to the energy storage and release capability introduced by stiffness adjustment, a variable stiffness actuator is essential to achieve human-like energy efficiency for robots. However, it is not trivial to control the strongly coupled and nonlinear system, especially with highly dynamic stiffness variation. In this work, decoupled and robust command filtered backstepping tracking controllers for position and stiffness are proposed. Furthermore, a disturbance observer is introduced to estimate the lumped disturbances caused by directly decoupled dynamics and unmodeling errors. Since the input control torques can be easily saturated due to limited deformation of elastic elements, anti-windup compensation is introduced into the tracking control laws to reduce its negative influence. Thus, by combining the command filtered backstepping controller, disturbance observers, and anti-windup compensation, the stability proof of the proposed composite controller is provided. The tracking control performance is validated through simulations of multi-DoF variable stiffness actuated robots.

In DC microgrids, the cascade operation of the DC-DC converters leads to a constant power load fed by the boost converter, resulting in unstable behavior in addition to the non-minimum phase dynamics. An enhanced load disturbance rejection control scheme based on partial pole placement and an approximate model matching technique is proposed. This approach is inspired by the well-known direct synthesis method to achieve optimal load disturbance rejection performance. The effectiveness of the proposed control scheme has been validated through hardware implementation, demonstrating its capability in setpoint tracking and load disturbance rejection under variations in load power and input voltage. The robust stability of the suggested scheme has been investigated through the Kharitonov theorem and Monte-Carlo simulation, considering different performance matrices. The suitability of the presented scheme has been established by analyzing the comparative performance of recently reported works. The proposed controller reduces peak overshoot and settling time by ∼50%, handles system uncertainties up to 75%, and outperforms FOPID controllers tuned with particle swarm optimization, queen bee genetic algorithm, and chaos game optimization methods.

The coupled relationship between inputs and outputs in multiple-input multiple-output (MIMO) systems, as well as the multiplicative uncertainties caused by multiplicative faults, increases the complexity of fault diagnosis (FD) and fault-tolerant control (FTC). Research has indicated that coprime factor uncertainties are suitable for modeling multiplicative uncertainties. This paper presents an FD and FTC strategy for MIMO systems based on the ν-gap metric technique within the coprime factorization framework. In the offline phase, the ν-gap metric-based hierarchical clustering method is designed to classify fault samples. Next, core systems and boundary systems are calculated for each fault category, and corresponding residual compensation controllers are designed. In the online phase, by computing the relevant ν-gap metric values, the fault severity of the real-time system is determined, and the core system with similar dynamic behaviors is identified. This FD result drives the switching of residual compensation controller, achieving FTC and ensuring system stability and robustness. This strategy eliminates the need for online solving of fault-tolerant controller, saving computational resources. Finally, the ν-gap metric-based FD and FTC strategy is validated with simulations on a three-phase voltage source inverter system.

The topside separation system plays a pivotal role in the treatment of produced water within offshore oil and gas production operations. Due to high-humidity and salt-infested marine environments, topside separation systems are susceptible to dynamic model variations and valve faults. In this work, fault-tolerant control (FTC) of topside separation systems subject to structural uncertainties and slugging disturbances is studied. The system is configured as a cascade structure, comprising a water level control subsystem and a pressure-drop-ratio (PDR) control subsystem. A fault-tolerant H_∞ control framework is developed to cope with actuator faults and slugging disturbances. To enhance control performance in the presence of actuator faults and model uncertainties while reducing sensitivity to slugging disturbances, the fault-tolerant H_∞ control problem for the topside separation system is established as the two-player differential game problem. In addition, a Nash equilibrium solution for the fault-tolerant H_∞ control problem is achieved through the solution of the game algebraic Riccati equation (GARE). A model-free approach is presented to implement the proposed fault-tolerant H_∞ control method using off-policy reinforcement learning (RL). Simulation studies demonstrate the effectiveness of the solution.

This paper aims to study the remote state estimation of networked nonlinear systems subject to aperiodic sampled delayed measurement. A novel sampled-data non-affine nonlinear observer (SNNO) is designed to address this issue. The designed observer is composed of two parts: the first part is a continuous-time observer, and the second part is an auxiliary variable design that provides continuous compensation of output estimation errors for the first part's state observer. The design of this auxiliary variable provides a new compensation scheme for sampled delayed measurement. The input-to-state stability of the SNNO with respect to the system and output disturbance is proved by means of trajectory-based stability theory. The new theoretical tool reveals the relationship between the convergence rate of the proposed SNNO and the sampling and delay periods. Simulations and comparative analyses with other sampled-data observers are given.