Nonlinear adaptive feedback linearisation-based backstepping controller design for islanded DC microgrid

A robust nonlinear adaptive controller design for unmanned autonomous vehicles (UAVs) for controlling the hovering flight is presented. The controller is premeditated recursively based on the control Lyapunov theory where the mass of the UAV in the model is considered as anonymous parameter. To illustrate the forcefulness property of the designed controller, the effects of external disturbances are also considered in the UAV dynamical model throughout the devise of the controller. The unknown parameter (mass) is estimated using the adaptation law and incorporated in the final control law and then the overall immovability of the UAV system is confirmed by forming the negative semi-definiteness of Lyapunov functions. Note that the designed controller is adaptive to the mysterious parameter of the UAV and robust to external disturbances. Finally, the designed controller performance is experienced using a MATLAB simulation model under hovering flight condition and the performance is also compared with an existing nonlinear robust adaptive backstepping controller. The simulation results illustrate the sturdiness of the designed controller as compared to the existing nonlinear robust controller in terms of declining exterior wind gusts.

Nonlinear adaptive feedback linearisation-based backstepping controller design for islanded DC microgrid

A robust nonlinear control strategy, based on back-stepping, is presented to adjust the dc-link voltage from the PV system and the current which is used to control the amount of injected active or reactive power into the grid. The control system is projected using an adaptive backstepping technique taking the unknown parameters into consideration. But many times, the problems of differential expansion and the control saturation in backstepping theory are very hard and difficult, we employ a command filter to eliminate the impact of time derivative and control saturation. The devised controller is adaptive to the unknown parameters of the PV system and those parameters are estimate via the adaptive laws for the sake of guaranteeing the stability of dc-link voltage extracting from the PV solar and the appropriate amount active and reactive power injecting to the grid. The stability of the entire system is disposed on account of the Lyapunov functions (LPF). In the end, the effect of the proposed controller is measured on a grid-connected solar PV inverter system under the change of the reference values of PV system. The result of the simulation indicates excellent dynamic following performance and strong robustness with the proposed controller.

In this article, a nonlinear adaptive fuzzy backstepping controller combined with an adaptive backstepping controller and an adaptive fuzzy controller is proposed for real-time tracking control of an electro-hydraulic force loading system. Firstly, a nonlinear dynamic model for the electro-hydraulic force loading system is built with consideration of parameter uncertainties and external disturbances. Then, the adaptive backstepping controller is employed to obtain desired control output for the force loading control system considering parameter uncertainties and external disturbances. Furthermore, an adaptive fuzzy control scheme is designed to adjust uncertain control parameters based on adaptive fuzzy system to cope with the chattering condition that results from the overwhelming external disturbances. The stability of the overall system with the proposed control algorithm can be proved by Lyapunov stability theory. Finally, an electro-hydraulic force loading experimental system with xPC rapid prototyping technology is carried out to verify the effectiveness of the proposed nonlinear adaptive fuzzy backstepping controller. Experimental results verify that the proposed control method exhibit excellent performances on force loading tracking control of the electro-hydraulic force loading experimental system compared with a conventional proportional-integral-derivative (PID) controller with velocity feedforward and adaptive backstepping control schemes.

In this paper, a nonlinear adaptive backstepping controller is designed to control the common dc-bus voltage for different components in a dc microgrid under various operating conditions. The dc microgrid in this paper comprises a solar photovoltaic (PV) unit, a battery energy storage system (BESS), a backup diesel generator, and loads (both critical and noncritical). The controllers are designed for all components except loads where the main control objective for all controllers is to maintain a constant voltage at the dc-bus where all components are connected. This paper considers solar PV systems as the renewable energy source, whereas a diesel generator equipped with a rectifier is used as a backup supply to maintain the continuity of power supply in the case of emergency situations. The proposed controller is designed recursively based on the Lyapunov control theory, where all parameters within the model of different components are considered unknown. Adaptation laws are used to estimate these unknown parameters while the stability of the dc microgrid, with these adaptation laws, is ensured through the formulation of suitable control Lyapunov functions (CLFs) at different stages of the design process. The negative definiteness or semidefiniteness of these CLFs guarantees the stability of the dc microgrid. Finally, the performance of the proposed controllers is verified using both simulations and experiments on a test dc microgrid under different operating conditions. The proposed controller ensures the regulation of the dc-bus voltage within the acceptable limits under different operating conditions.

A cascaded control structure is proposed in this paper for injecting active and reactive power in a three-phase grid-connected solar photovoltaic (PV) system by considering external disturbances. In the proposed cascaded control structure, there are two control loops—the outer loop voltage controller is used to ensure a continuous balance in power flow between the PV arrays and electrical power grid whereas the inner loop current controller controls the output current of the inverter. Moreover, the DC-DC boost converter is controlled to achieve a constant voltage at the input of the inverter. In order to obtain the power balance and extract maximum power, an incremental conductance (IC) based maximum power point tracking (MPPT) method is used in this paper. The current controller is designed using a nonlinear adaptive backstepping technique to regulate the active and reactive components of the grid current. The regulation of these currents towards desired values which in turn control the active and reactive power delivered into the grid. The overall stability analysis of the system is performed based on the formulation of control Lyapunov functions (CLFs). Finally, the performance of the designed controller is tested on three-phase grid-connected PV systems with single as well as multiple PV units under different environmental conditions and compared with an existing sliding mode controller. Simulation results confirm the effectiveness of the proposed adaptive backstepping control scheme and demonstrate the superior performance over the sliding mode controller.

The main goal of this thesis is to investigate the potential of the nonlinear adaptive backstepping control technique in combination with online model identification for the design of a reconfigurable flight control system for a modern fighter aircraft. Adaptive backstepping is a recursive, Lyapunov-based, nonlinear design method, that makes use of dynamic parameter update laws to deal with parametric uncertainties. The idea of backstepping is to design a controller recursively by considering some of the state variables as ‘virtual controls’ and designing intermediate control laws for these. Backstepping achieves the goals of global asymptotic stabilization of the closed-loop states and tracking. The proof of these properties is a direct consequence of the recursive procedure, since a Lyapunov function is constructed for the entire system including the parameter estimates. The tracking errors drive the adaptation process of the procedure. Furthermore, it is possible to take magnitude and rate constraints on the control inputs and system states into account in such a way that the identification process is not corrupted during periods of control effector saturation. A disadvantage of the integrated adaptive backstepping method is that it only yields pseudo-estimates of the uncertain system parameters. There is no guarantee that the real values of the parameters are found, since the adaptation only tries to satisfy a total system stability criterion, i.e. the Lyapunov function. Increasing the adaptation gain will not necessarily improve the response of the closed-loop system, due to the strong coupling between the controller and the estimator dynamics. The immersion and invariance (I&I) approach provides an alternative way of constructing a nonlinear estimator. This approach allows for prescribed stable dynamics to be assigned to the parameter estimation error. The resulting estimator is combined with a backstepping controller to form a modular adaptive control scheme. The I&I based estimator is fast enough to capture the potential faster-than-linear growth of nonlinear systems. The resulting modular scheme is much easier to tune than the ones resulting from the standard adaptive backstepping approacheswith tracking error driven adaptation process. In fact, the closed-loop system resulting from the application of the I&I based adaptive backstepping controller can be seen as a cascaded interconnection between two stable systems with prescribed asymptotic properties. As a result, the performance of the closed-loop system with adaptive controller can be improved significantly. To make a real-time implementation of the adaptive controllers feasible the computational complexity has to be kept at a minimum. As a solution, a flight envelope partitioning method is proposed to capture the globally valid aerodynamic model into multiple locally valid aerodynamic models. The estimator only has to update a few local models at each time step, thereby decreasing the computational load of the algorithm. An additional advantage of using multiple, local models is that information of the models that are not updated at a certain time step is retained, thereby giving the approximator memory capabilities. B-spline networks are selected for their nice numerical properties to ensure smooth transitions between the different regions. The adaptive backstepping flight controllers developed in this thesis have been evaluated in numerical simulations on a high-fidelity F-16 dynamicmodel involving several control problems. The adaptive designs have been compared with the gain-scheduled baseline flight control system and a non-adaptive NDI design. The performance has been compared in simulation scenarios at several flight conditions with the aircraft model suffering from actuator failures, longitudinal center of gravity shifts and changes in aerodynamic coefficients. All numerical simulations can be easily performed in real-time on an ordinary desktop computer. Results of the simulations demonstrate that the adaptive flight controllers provide a significant performance improvement over the non-adaptive NDI design for the simulated failure cases. Of the evaluated adaptive flight controllers, the I&I based modular adaptive backstepping design has the overall best performance and is also easiest to tune, at the cost of a small increase in computational load and design complexity when compared to integrated adaptive backstepping control designs. Moreover, the flight controllers designed with the I&I based modular adaptive backstepping approach have even stronger provable stability and convergence properties than the integrated adaptive backstepping flight controllers, while at the same time achieving a modularity in the design of the controller and identifier. On the basis of the research performed in this thesis, it can be concluded that a RFC system based on the I&I based modular adaptive backstepping method shows a lot of potential, since it possesses all the features aimed at in the thesis goal.

Robust nonlinear adaptive backstepping excitation controller design for rejecting external disturbances in multimachine power systems

In this paper, a nonlinear adaptive backstepping controller is designed to control the bidirectional power flow (charging/ discharging) of battery energy storage systems (BESSs) in a DC microgrid under different operating conditions. The controller is designed in such a manner that the BESSs can store the excess energy from the renewable energy sources (RESs) in a DC microgrid after satisfying the load demand and also feeding back the stored energy to the load when RESs are not sufficient. The proposed controller is also designed to maintain a constant voltage at the DC bus, where all components of DC microgrids are connected, while controlling the power flow of BESSs. This paper considers solar photovoltaic (PV) systems as the RES whereas a diesel generator equipped with a rectifier is used as a backup supply to maintain the continuity of power supply in the case of emergency situations. The controller is designed recursively based on the Lyapunov control theory where all parameters within the model of BESSs are assumed to be unknown. These unknown parameters are then estimated through the adaptation laws and whose stability is ensured by formulating suitable control Lyapunov functions (CLFs) at different stages of the design process. Moreover, a scheme is also presented to monitor the state of charge (SOC) of the BESS. Finally, the performance of the proposed controller is verified on a test DC microgrid under various operating conditions. The proposed controller ensures the DC bus voltage regulation within the acceptable limits under different operating conditions.

This paper proposes a nonlinear adaptive back-stepping controller to damp the oscillations and improve the transient stability in multi-machine power systems. The designed controller is adaptive to unknown generator parameters. The proposed controller is designed based on a fourth order nonlinear model of a synchronous generator and the automatic voltage regulator model is considered so as to decrease the steady state voltage error. The construction of both control law and associated Lyapunov function is consistently systematic within the design methodology. A 3-machine power system is used to demonstrate the effectiveness of the proposed controller over other two controllers: one is the conventional damping controller (power system stabilizer) and the other is the one designed by the feedback linearization technique.

The problem of transient stability for a single machine infinite bus system with static VAR compensator (SVC) is addressed in this paper. In the system, the damping coefficients are measured inaccurately. A nonlinear robust controller and a parameter updating law are obtained simultaneously based on modified adaptive backstepping and Lyapunov methods. The system does not need to be linearized and the closed-loop error system is guaranteed to be asymptotically stable. Simulation results demonstrate that the proposed method provides better system response and robustness than the design based on conventional adaptive backstepping method.

In this paper, a nonlinear adaptive controller for regulating the grid of a current source inverter (CSI) based three-phase grid-connected photovoltaic (PV) system is proposed. The proposed control structure is composed with an outer control loop-responsible for controlling the DC-side inductor current and the inner current control loop-responsible for controlling injected current into the utility grid. The proposed adaptive controller is designed recursively by considering external disturbances within the system and these unknown external disturbances are estimated through the adaption laws. The overall stability of the whole CSI based three-phase grid-connected PV system is verified by formulating the control Lyapunov functions (CLFs) at different stages throughout the design process of the proposed controller. Finally, the performance of the designed controller is tested on a similar CSI based three-phase grid-connected PV system under different atmospheric conditions. Simulation results demonstrate that the proposed control scheme can effectively meet the desired control objectives as compared to the existing controller in terms of settling time and power quality.

This paper presents a nonlinear control scheme to regulate the dc-link voltage for extracting the maximum power from PV system and the current to control the amount of injected power into the grid. The controller is designed using an adaptive backstepping technique by considering the parameters of the system as totally unknown. The control of power injection into the grid requires the regulation of active and reactive components of the output current of the inverter in order to control active and reactive power, respectively. The proposed controller is adaptive to unknown parameters of grid-connected solar photovoltaic (PV) systems and these parameters are estimated through the adaptation laws while guaranteeing the extraction of maximum power from the PV system and delivering appropriate active and reactive power into the grid. The overall stability of the whole system is analyzed based on the formulation of control Lyapunov functions (CLFs). Finally, the performance of the designed controller is tested on a three-phase grid-connected PV system under changeing environmental conditions and the result is also compared with an existing backstepping controller in terms of improving power quality. Simulation results indicate the robustness of the proposed scheme under changing atmospheric conditions.

Considering the external disturbances, this paper proposes a new control approach, with the intention of improving the trajectory flight control in the longitudinal-lateral trajectory plane with constant altitude, to design a nonlinear adaptive controller for an unmanned autonomous helicopter (UAH). The unknown external disturbances are considered within the system model and estimated through adaption laws and incorporated with the control law to attest the robustness property of the intended control scheme. The designed controller is able to provide the robustness property against external turbulences as well as can overcome the over-parameterization problem which generally emerges in some conventional adaptive methods. To prove the convergence of longitudinal and lateral dynamics to a desired equilibrium point, in every stage of the design procedure a control Lyapunov function (CLF) is formulated and stability of the whole system is proved through the negative definiteness of the derivative of CLF. Finally, the performance of the proposed controller is verified in a MATLAB/SIMULINK model in the presence of external turbulence into the system. The robustness of the proposed controller, in terms of rejecting external disturbances, is illustrated through the simulation results.

Loop Heat Pipes (LHP) are complex, thermo-dynamic heat transport systems for the thermal control of temperature-sensitive systems with locally separated heat sources and heat sinks. Through evaporation and condensation of a working fluid, the two-phase LHP achieves a high heat transfer coefficient. The LHP operating temperature strongly depends on the heat load and the sink temperature. Therefore, an additional control heater on the compensation chamber is used to keep a desired operating temperature under changing operating conditions. Compared to the commonly used PID controller, the temperature control performance of the control heater is improved by a nonlinear model identification adaptive control design. Unknown time-variant model parameters are estimated online to improve the model accuracy. The temperature prediction is validated with experimental data from a LHP test bench. The presented nonlinear control algorithm is implemented and tested in a numerical simulation of the LHP.