Three‐Time‐Scale Singular Perturbation Stability Analysis of Three‐Phase Power Converters

This paper analyzes the stability of the well‐known three‐phase two‐level power converter. Focusing on the rectifier operating mode, the dynamics of the system, when the instantaneous power and dc‐link voltage controllers are included, are described by a set of complex equations that results in a nonlinear autonomous singularly perturbed system. Hence, the closed‐loop system can be studied under the assumption of separate time scales. The analysis proposed in this work follows a novel three‐time‐scale approach, where the fast time scale corresponds with the instantaneous power dynamics, the mid‐range time scale is related to the dc‐link voltage dynamics, and the slow time scale is associated with the dc‐link voltage regulator dynamics. In this way, the analysis leads to the decomposition of the closed‐loop system into three simpler subsystems: fast, medium, and slow subsystems. These subsystems approximate the closed‐loop system behavior over the three different time scales. Finally, since the equilibrium point of each subsystem is exponentially stable and some other conditions are satisfied, it is shown that the equilibrium point of the closed‐loop system also presents exponential stability. Experimental results for a synchronous three‐phase power rectifier prototype are included to corroborate the analysis carried out.     

Stability analysis and a hybrid controller design of grid‐connected offshore wind farm through a VSC‐HVDC transmission link

This paper proposes a hybrid controller which is a combination sliding mode control and PI control techniques for AC grid integrated offshore wind farm (OSWF) with voltage source converter ‐ high voltage direct current system. The controller must be capable of controlling AC voltage, DC‐link voltage, reactive power and effective power transfer. To examine the FRT capability, a symmetrical fault is applied at onshore AC grid side and compared the performances of the studied system based on the hybrid and PI controllers. The dynamic modelling and linearized system by state‐space modelling for the studied system are explained in detail. The small signal stability analysis and controller stability are observed with the help of the eigenvalue analysis. The analysis of the studied system with a hybrid and conventional controllers are conducted in the software environment of the MATLAB/SIMULINK . The effect of parameter uncertainty on total system stability is examined with the help of eigenmatrix of the studied system.     

Output‐Feedback Nonlinear Adaptive Control of Single‐Phase Half‐Bridge Ups Systems

We consider the problem of controlling single‐phase half‐bridge power converters in UPS systems operating in the presence of changing load. The control objective is twofold: (i) ensuring a satisfactory power factor correction (PFC) at the grid–UPS connection; (ii) guaranteeing a tight regulation of the DC bus voltage and the half‐bridge inverter output voltage despite changes in load. The considered control problem entails several difficulties including: (i) the high dimension and strong nonlinearity of the system; (ii) the numerous state variables that are inaccessible to measurements; (iii) the uncertainty that prevails on some system parameters. The problem is dealt with using a multi‐loop nonlinear adaptive control system that makes use of the backstepping design technique. The inner loop ensures the PFC objective and involves an adaptive observer estimating the grid voltage and impedance parameters. The intermediary loop regulates the inverter output voltage to its reference, which is a sinusoidal wave, and it also contains an observer estimating the current in the inverter coil. The outer loop regulates the DC bus voltage up to small size ripples. The controller performances are formally analyzed using system averaging theory.     

A family of virtual contraction based controllers for tracking of flexible‐joints port‐Hamiltonian robots: Theory and experiments

In this work, we present a constructive method to design a family of virtual contraction based controllers that solve the standard trajectory tracking problem of flexible‐joint robots in the port‐Hamiltonian framework. The proposed design method, called virtual contraction based control, combines the concepts of virtual control systems and contraction analysis. It is shown that under potential energy matching conditions, the closed‐loop virtual system is contractive and exponential convergence to a predefined trajectory is guaranteed. Moreover, the closed‐loop virtual system exhibits properties such as structure preservation, differential passivity, and the existence of (incrementally) passive maps. The method is later applied to a planar RR robot, and two nonlinear tracking control schemes in the developed controllers family are designed using different contraction analysis approaches. Experiments confirm the theoretical results for each controller.     

Predictive direct torque control with reduced ripples for induction motor drive based on T‐S fuzzy speed controller

Finite‐state model predictive control (FS‐MPC) has been widely used for controlling power converters and electric drives. Predictive torque control strategy (PTC) evaluates flux and torque in a cost function to generate an optimal inverter switching state in a sampling period. However, the existing PTC method relies on a traditional proportional‐integral (PI) controller in the external loop for speed regulation. Consequently, the torque reference may not be generated properly, especially when a sudden variation of load or inertia takes place. This paper proposes an enhanced predictive torque control scheme. A Takagi‐Sugeno fuzzy logic controller replaces PI in the external loop for speed regulation. Besides, the proposed controller generates a proper torque reference since it plays an important role in cost function design. This improvement ensures accurate tracking and robust control against different uncertainties. The effectiveness of the presented algorithms is investigated by simulation and experimental validation using MATLAB/Simulink with dSpace 1104 real‐time interface.     

A robust PI passivity‐based control of nonlinear systems and its application to temperature regulation

This paper deals with the problem of control of partially known nonlinear systems, which have an open‐loop stable equilibrium, but we would like to add a PI controller to regulate its behavior around another operating point. Our main contribution is the identification of a class of systems for which a globally stable PI can be designed knowing only the systems input matrix and measuring only the actuated coordinates. The construction of the PI is carried out invoking passivity theory. The difficulties encountered in the design of adaptive PI controllers with the existing theoretical tools are also discussed. As an illustration of the theory, we consider a class of thermal processes. Copyright © 2015 John Wiley & Sons, Ltd.     

Linear Model‐based Feedforward Control for Improving Tracking‐performance of Linear Motors

The main purpose of this article is to propose a linear model‐based approach for improving the tracking performance of linear motors. In particular, P‐ and PI‐controllers, augmented with a linear‐model‐based feedforward controller and disturbance observer (DOB), were utilized in this research. Experimental results show that the feedforward controller can substantially reduce the phase‐delay problem resulting from the limitation of closed‐loop bandwidth. In addition, the DOB can reject nonlinear behaviors to keep a motor‐system close to our nominal linear model. Compared with the results of using P‐ and PI‐controllers only, tracking errors were reduced from 4.44% to 0.67% of the desired trajectory. Therefore, the proposed method provides a solution for improving the tracking performance of linear motors.     

Model‐free adaptive formation control for unknown multiinput‐multioutput nonlinear heterogeneous discrete‐time multiagent systems with bounded disturbance

Based on the model‐free adaptive control, the distributed formation control problem is investigated for a class of unknown heterogeneous nonlinear discrete‐time multiagent systems with bounded disturbance. Two equivalent data models to the unknown multiagent systems are established through the dynamic linearization technique considering the circumstances with measurable and unmeasurable disturbances. Based on the obtained data models, two distributed controllers are designed with only using the input/output and disturbance data of the neighbor agents system. The tracking error of the closed‐loop system driven by the proposed controllers is shown to be bounded by the contraction mapping principle and inductive methods. An example illustrates the effectiveness of the proposed two distributed controllers.     

Fuzzy Sliding‐mode Strategy for Air–fuel Ratio Control of Lean‐burn Spark Ignition Engines

Minimization of emissions of carbon dioxide and harmful pollutants and maximization of fuel economy for lean‐burn spark ignition (SI) engines relies to a large extent on precise air–fuel ratio (AFR) control. However, the main challenge of AFR control is the large time‐varying delay in lean‐burn engines. Since the system is usually subject to external disturbances and uncertainties, a high level of robustness in AFR control design must be considered. We propose a fuzzy sliding‐mode control (FSMC) to track the desired AFR in the presence of periodic disturbances. The proposed method is model free and does not need any system characteristics. Based on the fuzzy system input–output data, two scaling factors are first employed to normalize the sliding surface and its derivative. According to the concept of the if‐then rule, an appropriate rule table for the logic system is designed. Then, based on Lyapunov stability criteria, the output scaling factor is determined such that the closed‐loop stability of the internal dynamics with uniformly ultimately bounded (UUB) performance is guaranteed. Finally, the feasibility and effectiveness of the proposed control scheme are evaluated under various operating conditions. The baseline controllers, namely, a PI controller with Smith predictor and sliding‐mode controller, are also used to compare with the proposed FSMC. It is shown that the proposed FSMC has superior regulation performance compared to the baseline controllers.     

Current‐mode control of DC–DC power converters: a backstepping approach

Current‐mode control is a robust industrial DC–DC power converter control scheme that has been successfully tested, is widely accepted, and is commonly implemented with conventional linear P and PI controllers. The need of more systematic designs with enhanced performance has motivated recent studies with linear and nonlinear advanced techniques, but the rigorous understanding and substantiation of the underlying key robust functioning capability are still lacking. In this paper, a constructive control approach is employed to study the current‐mode control problem of a class of DC–DC power converters, yielding a cascade control design methodology with: a robust convergence criterion coupled with a systematic and transparent construction‐tuning procedure, a rationale to explain the robust controller functioning, and a unified framework to interpret and compare the proposed controller with the existing conventional and advanced control designs. The implementation and functioning of the proposed control design is illustrated experimentally with a boost converter. Copyright © 2003 John Wiley & Sons, Ltd.     

Nonlinear fractional‐order power system stabilizer for multi‐machine power systems based on sliding mode technique

This paper presents two novel nonlinear fractional‐order sliding mode controllers for power angle response improvement of multi‐machine power systems. First, a nonlinear block control is used to handle nonlinearities of the interconnected power system. In the second step, a decentralized fractional‐order sliding mode controller with a nonlinear sliding manifold is designed. Practical stability is achieved under the assumption that the upper bound of the fractional derivative of perturbations and interactions are known. However, when an unknown transient perturbation occurs in the system, it makes the evaluation of perturbation and interconnection upper bound troublesome. In the next step, an adaptive‐fuzzy approximator is applied to fix the mentioned problem. The fuzzy approximator uses adjacent generators relative speed as own inputs, which is known as semi‐decentralized control strategy. For both cases, the stability of the closed‐loop system is analyzed by the fractional‐order stability theorems. Simulation results for a three‐machine power system with two types of faults are illustrated to show the performance of the proposed robust controllers versus the conventional sliding mode. Additionally, the fractional parameter effects on the system transient response and the excitation voltage amplitude and chattering are demonstrated in the absence of the fuzzy approximator. Finally, the suggested controller is combined with a simple voltage regulator in order to keep the system synchronism and restrain the terminal voltage variations at the same time. Copyright © 2014 John Wiley & Sons, Ltd.     

Gpc‐Based Self‐Tuning PI Controller for Speed Servo System of PMSLM

In this paper, a generalized predictive control (GPC)‐based two degrees of freedom (2 DOF) proportional integral (PI) controller is proposed for the speed servo system of a permanent magnet synchronous linear motor (PMSLM). In this new approach, based on a dynamic model of a servo system, a simplified and high‐performance GPC supplies a 2 DOF PI controller with suitable control parameters, according to the varied operating conditions. In previous studies, GPC‐based proportional integral derivative (PID) controllers have been designed using a step‐type or ramp‐type reference input. In our work, however, the speed command for PMSLM usually is required to be a trapezium‐type signal because of the limited travel range. Hence, control performance of a speed servo system using a GPC‐based 2 DOF PI controller is enhanced for tracking a trapezium‐type command. The validity and usefulness of the proposed controller are verified through simulation and experiments.     

Optimal fixed‐structure control for linear non‐negative dynamical systems

In this paper, we develop optimal output feedback controllers for set‐point regulation of linear non‐negative dynamical systems. Specifically, using a constrained fixed‐structure control framework we develop optimal output feedback control laws that guarantee that the trajectories of the closed‐loop system remain in the non‐negative orthant of the state space for non‐negative initial conditions. In addition, we characterize domains of attraction predicated on closed and open Lyapunov level surfaces contained in the non‐negative orthant for unconstrained optimal linear‐quadratic output feedback controllers. Output feedback controllers for compartmental systems with non‐negative inputs are also given. Copyright © 2004 John Wiley & Sons, Ltd.     

三电平SAPF双闭环控制系统的研究

提出了一种三电平并联型有源电力滤波器双闭环控制系统的设计方案。该系统采用ip-iq法提取谐波,利用瞬时无功功率理论检测三相电压与负载电流,用以计算补偿电流;其电压外环采用模糊PI控制器控制,电流内环采用内模控制器控制,并由三电平SVPWM调制器输出补偿电流。仿真实验结果验证了该系统具有良好的谐波补偿效果。     

Model predictive control for continuous lactide ring‐opening polymerization processes

Polylactic acid (PLA) is an attractive environment‐friendly thermoplastic that is bio‐sourced and biodegradable. PLA is industrially produced by the ring‐opening polymerization of lactide. This reaction is sensitive to drifts in the operating conditions and impurities in the raw materials that may affect the reaction rate as well as the polymer properties, which can be very costly in continuous processes. It is therefore crucial to employ a control strategy that allows recovering the nominal conditions and maintaining the desired properties and conversion level in case of drift. Three control strategies are discussed in this paper: proportional‐integral (PI) controller, dynamic optimization, and model predictive control (MPC). The proposed approaches are validated by simulation of a continuous PLA process constituted of three cascade reactors including one loop reactor in the middle. Besides the coupling of inputs and outputs, the process model is highly nonlinear, and the control is done only on the boundaries. The results show that the open‐loop optimization strategy provides better performance compared to the PI controller if the disturbance is assumed to be measured. The MPC also shows superior performances provided that the disturbance is first estimated. A polynomial model is developed to predict the nonmeasured disturbance based on the measured outputs.     

On input‐to‐state stability of rigid‐body attitude control with quaternion representation

The concept of input‐to‐state stability (ISS) is important in robust control, as the state of an ISS system subject to disturbances can be stably regulated to a small region around the origin. In this study, the ISS property of the rigid‐body attitude system with quaternion representation is thoroughly investigated. It has been known that the closed loop with continuous controllers is not ISS with respect to arbitrarily small external disturbances. To deal with this problem, hybrid proportional‐derivative controllers with hysteresis are proposed to render the attitude system ISS. The controller is far from new, but it is investigated in a new aspect. To illustrate the applications of the results about ISS, 2 new robust hybrid controllers are designed. In the case of large bounded time‐varying disturbances, the hybrid proportional‐derivative controller is designed to incorporate a saturated high‐gain feedback term, and arbitrarily small ultimate bounds of the state can be obtained; in the case of constant disturbances, a hybrid adaptive controller is proposed, which is robust against small estimate error of inertia matrix. Finally, simulations are conducted to illustrate the effectiveness of the proposed control strategies.     

Event‐Triggered Iterative Learning Control for Multi‐Agent Systems with Quantization

The emergence of networked control systems urges the digital control design to integrate communication constraints efficiently. In order to accommodate this requirement, this paper investigates the joint design of tracking problem for multi‐agent system (MAS) in the presence of resource‐limited communication channel and quantization. An event‐triggered robust learning control with quantization is firstly proposed and employed for MAS in this paper. The new event‐triggered distributed robust learning control system with the introduction of logarithmic quantization guarantees the asymptotic tracking property on the finite interval. Convergence analysis is given based on the Lyapunov direct method. Finally, numerical simulations are given to illustrate the efficacy of the event‐triggered approach compared with time‐triggered controllers.     

Fixed‐time attitude tracking control for spacecraft based on adding power integrator technique

In this article, the fixed‐time attitude tracking problem for rigid spacecraft is investigated based on the adding‐a‐power‐integrator control technique. First, a fixed‐time attitude tracking controller is designed to guarantee fixed‐time convergence of tracking errors. Then, by considering the presence of random disturbance and actuator faults, an adaptive fault‐tolerant attitude tracking controller is designed to guarantee tracking errors converge to a residual set of zero in a fixed time. The complete bounds on settling time are derived independently of initial conditions. The simulation results illustrate the highly precise and robust attitude control performance obtained by using the proposed controllers.     

Adaptive Continuous Neural Pitch Angle Control for Variable‐Speed Wind Turbines

As wind energy becomes one of the fastest growing renewable energy resources, the control of large‐scale wind turbines remains a challenging task due to its system model nonlinearities and high external uncertainties. In this paper, an adaptive neural pitch angle control strategy is proposed for the variable‐speed wind turbines (VSWT) operating in pitch control region. The control objective is to maintain the rotor speed and generator power at the prescribed reference values in the presence of external disturbance, without the need of the information of system parameters and aerodynamics. First, the order of the system dynamics is increased by defining a filtered regulation error. By this means, the non‐affine characteristics of the VSWT model is transformed into a simple affine control problem and thus the feedback linearization technique can be employed. The continuousness of control signal is also guaranteed to relax the requirement on the bandwidth of actuators, and the mechanical load on pitching systems is reduced. Subsequently, an online learning approximator (OLA) is utilized to estimate the unknown nonlinear aerodynamics of the wind turbine and extend the practicability of the proposed adaptive parameter‐free controller. In addition, a high‐gain observer is implemented to obtain an estimation of rotor acceleration, which rejects the need of additional sensors. Rigid theoretical analysis guarantees the tracking of rotor speed/generator power and the boundedness of all other signals of the closed‐loop system. Finally, the effectiveness of the proposed scheme is testified via the Wind Turbine Blockset simulation package in Matlab/Simulink environment. Moreover, comparison results reveal that the introduced solution is able to provide better regulation performance than the conventional PI counterpart.     

Data‐driven robust backstepping control of unmanned surface vehicles

In this article, a novel data‐driven robust backstepping control (DRBC) approach for tracking of unmanned surface vehicles (USVs) with uncertainties and unknown parametric dynamics has been developed. Main contributions are fourfold: (a) Unlike previous approaches, within the DRBC scheme, backstepping decoupled technique and data‐driven sliding‐mode control (DSMC) can be effectively cohered. (b) Using backstepping philosophy, a new data‐driven PI‐type sliding‐mode surface is devised, such that strong robustness with simple structure can be ensured. (c) Complex unknowns including couplings, uncertainties and parametric dynamics are sufficiently lumped, and are totally compensated by the extended state observer. (d) The entire DRBC scheme eventually achieves accurate tracking of USVs with strong couplings, uncertainties and unknown parametric dynamics. The efficacy and superiority of the proposed DRBC approach is validated on a prototype USV.