Antonio T. Alexandridis

NN-Based Adaptive Tracking Control of Uncertain Nonlinear Systems Disturbed by Unknown Covariance Noise

A class of uncertain nonlinear systems that are additionally driven by unknown covariance noise is considered. Based on the backstepping technique, adaptive neural control schemes are developed to solve the output tracking control problem of such systems. As it is proven by stability analysis, the proposed controller guarantees that all the error variables are bounded with desired probability in a compact set while the tracking error is mean-square semiglobally uniformly ultimately bounded (M-SGUUB). The tracking performance and the effectiveness of the proposed design are evaluated by simulation results.

Stability and convergence analysis for a class of nonlinear passive systems

A systematic and general method that proves state boundedness and convergence to nonzero equilibrium for a class of nonlinear passive systems with constant external inputs is developed. First, making use of the method of linear-time-varying approximations, the boundedness of the nonlinear system states is proven. Next, taking advantage of the passivity property, it is proven that a suitable switching storage function can be always obtained to show convergence to the nonzero equilibrium by using LaSalles Invariance Principle. Numerical and simulation results illustrate the proposed theoretical analysis.

Generalized Nonlinear Stabilizing Controllers for Hamiltonian-Passive Systems With Switching Devices

A generalized nonlinear control scheme suitable to regulate any state variable at any desired reference value, for a class of nonlinear Hamiltonian-passive systems that includes switching power devices, is presented. The proposed controller acts as a special nonlinear oscillator, uses as feedback only the state variable that has to be regulated, renders the Hamiltonian-passive structure of the entire system, and regulates the nonlinear system to any nonzero desired equilibrium independently from its parameters and characteristics. Particularly, it is proven that under some common assumptions, the system states consisting of the controller states plus the original system states, are bounded for constant or piecewise constant external inputs. Under the same assumptions, it is established and proven that for these systems there exists a general, bounded, differentiable, nonincreasing storage function. Thus, LaSalles invariance principle can be directly applied to prove convergence to the desired equilibrium. Although this storage function can be really constructed as a suitably switching function, its explicit derivation is not necessary for the controller design; it is only needed to guess that such a storage function exists. This constitutes the main contribution of this brief since, in order to implement the proposed controller, one has simply to check whether some initial assumptions are satisfied. The simulation and experimental results conducted for the case of a dc-dc boost converter system with resistance-inductance load verify the proposed design approach.

Direct Power Control of DFIG Wind Systems Based on Nonlinear Modeling and Analysis

A complete new modeling approach for doubly fed induction generator (DFIG) wind energy systems is provided in this paper. The model incorporates all the system component dynamics, i.e., the ones of the induction generator and the ac/dc/ac frequency converter, and is developed on state space with the state vector including directly as states the stator-circuit and grid-side converter active and reactive powers. This innovation, combined with a voltage-oriented model deployment, permits the design and application of simple feedback PI direct power controls (DPCs). Hence, the proposed design approach becomes independent from the flux measurement or estimation under the cost of requiring a rigorous stability analysis, caused by the fact of not using field-oriented vector control techniques. Using recent advanced nonlinear methods, this analysis is completely performed on the entire closed-loop nonlinear system to conclude input-to-state stability and convergence to the desired equilibrium. Thus, a fully analyzed design approach for DPC is provided with guaranteed stability, further evaluated through extensive simulation results on a commercial 2-MW DFIG wind system.

Adaptive Neural Tracking for a Class of SISO Uncertain and Stochastic Nonlinear Systems

Adaptive neural control schemes based on the backstepping technique are developed to solve the tracking control problem of a combined stochastic and uncertain nonlinear system. As shown by an extensive stability analysis the proposed control scheme ensures that all the error variables are bounded in probability while the mean square tracking error becomes semiglobally uniformly ultimately bounded in an arbitrarily small area around the origin. The effectiveness of the design approach is illustrated by simulation results.

Modular Control Design and Stability Analysis of Isolated PV-Source/Battery-Storage Distributed Generation Systems

A distributed generation (DG) system with a photovoltaic (PV) source supported by energy storage devices and feeding dc- and ac-loads in islanded-mode operation, is considered and analyzed. As all the DG parts are interfaced through power electronic dc/dc or dc/ac converters, a control strategy is introduced which is applied directly on each individual duty-ratio converter input. The aim of the control design is to drive the PV-array energy production at the maximum power and to ensure instantaneous power balance in the limits of the storage capacity. In this scheme, critical quality demands are fulfilled, such as operation with constant ac- and dc-voltages at the load sides, independently from the power consumed. The particular controllers are implemented by applying the standard local cascaded structure with the inner-loops being fast nonlinear proportional-integral current-mode controllers. To avoid adverse impacts on the system performance, caused by contradictory actions between the individual controllers, the complete accurate DG model is considered as an isolated microgrid with the fast inner-loop controllers incorporated. Adopting a common modular inner-loop nonlinear controller form, a rigorous novel stability analysis is developed by constructing the appropriate Lyapunov function in a new sequential manner. Finally, the stability and convergence to the equilibrium are verified by simulation and experimental results.

Full-Scale Modeling, Control, and Analysis of Grid-Connected Wind Turbine Induction Generators With Back-to-Back AC/DC/AC Converters

A model-based dynamic analysis of a variable-speed wind generator system consisting of an induction generator connected to the grid through a full power frequency converter is conducted. To this end, a nonlinear modeling of the entire system is used in a manner that permits a novel controller design with common structure for both the generator- and grid-side converters. The proposed controller, acting directly on the duty-ratio inputs of the converters, ensures the boundedness of the duty-ratio signals in the permitted range although its structure is independent from the system parameters and open to different control objectives. Therefore, maximum power point tracking and power factor correction are easily implemented. Furthermore, the controller is proven to guarantee stability of the whole system under field- or near-field-oriented conditions without needing any flux measurement or estimation. Hence, the main contribution established by this approach is that a rigorous stability analysis taking into account the generator, converters, dc link, and controller dynamics is presented on the basis of a complete system modeling and controller design approach. The theoretical analysis and controller effectiveness are confirmed via extended simulation results for a commercial size 2-MW induction generator operating under varied wind speed conditions and are further validated on a similar system with real-time results.

Bounded Nonlinear Stabilizing Speed Regulators for VSI-Fed Induction Motors in Field-Oriented Operation

A new nonlinear controller design is developed for speed regulation of voltage source inverter (VSI)-driven induction motors. The proposed controller directly provides the duty-ratio input of the VSI in the permitted range to ensure linear modulation, is fully independent from the system parameters and suitably regulates the motor speed and the stator flux to the desired values. Considering the complete nonlinear model of the converter-motor system and applying advanced nonlinear methods, boundedness of the full system states is proven. Furthermore, exploiting the Hamiltonian-passive structure of the system, state convergence to the equilibrium is shown using LaSalles Invariance Principle. Though the controller design is developed in the frame of the field-oriented control methodology, stability holds true even without accurate field orientation guaranteeing an effective performance in cases where parameter variations occur. Extensive simulation results on an industrial size system are conducted to evaluate the proposed controller performance, under rapid changes of the reference speed or load torque as well as system parameter variations. In addition, a lab size induction motor system is experimentally tested. In all cases, the system response shows fast convergence to the equilibriums after limited transients, thus verifying the theoretical results.

Advanced Integrated Modeling and Analysis for Adjustable Speed Drives of Induction Motors Operating With Minimum Losses

The nonlinear induction motor model is appropriately integrated by incorporating the dynamics of the power electronic converter in a manner that permits the design of stable field-oriented control (FOC) operating with minimum losses. As already proven, the challenging issue of operating the induction machine with minimum copper losses requires a varying rotor flux opposed to the standard FOC technique, which keeps the rotor field magnitude constant and tracks the electric torque to the desired level. To this end, exploiting the Hamiltonian structure of the developed motor/converter model, an innovated nonlinear controller is proposed that guarantees the technical limits of the converter (linear modulation) and simultaneously operates under FOC at steady state to achieve accurate speed regulation with varying rotor flux according to the minimal losses requirements. Under these circumstances, the conventional FOC stability analysis does not hold anymore, and therefore for the first time, a new rigorous analysis is provided that proves stability and convergence to the desired equilibrium for the complete closed-loop motor converter system. Finally, the theoretical contribution is examined in comparison to the traditional FOC operation by simulations obtained for an industrial size induction motor, while it is further evaluated by real-time results of a motor with similar parameters.

Enhanced Control Design of Simple DC-DC Boost Converter-driven DC Motors: Analysis and Implementation

Abstract The DC-DC boost converter is one of the simplest power electronic devices that has not been yet exploited in a wide range of industrial applications due to control design difficulties caused by its model inherent special structure. Such an industrial application is the DC motor speed regulation that is studied in the present work. Particularly, in this article, a novel, non-linear control scheme for the duty ratio input of the converter is proposed, which is extensively analyzed and experimentally tested. The proposed design, though non-linear, results in a very simple scheme, ensures that the duty ratio takes values exclusively in the permitted range [0,1), achieves precise speed regulation even in cases of high unknown load disturbances, and does not depend on system parameters and states. Simultaneously, the design is formulated in a manner that provides a closed-loop passive system, which, as proven in the article, satisfies all these assumptions and properties that make possible the application of a new advanced non-linear method that strongly connects passivity with stability. Thus, the boundedness of all the closed-loop states and the stability and convergence to the desired steady-state equilibrium are directly concluded. The theoretical analysis is verified through extended simulation and experimental results.