In this paper, robust stabilization of a quadrotor aircraft attitude is investigated. The exact nonlinear attitude of a quadrotor model is presented by Linear-Parameter-Varying system with Linear-Fractional-Transformation representation (LFT-based LPV), when we took the nonlinearities as varying parameters. The closed loop interconnection is established by taking into account the external disturbances, measurement noises and actuator dynamics. The synthesis of H∞ gain-scheduling controller is achieved by scaling small gain theorem when the controller is an LFT-based LPV too. The simulations show the efficiency and the robustness of the proposed controller against the disturbances, noises and parametric uncertainties.

Robust Attitude Stabilization of a Quadrotor by Using LFT Linear-Parameter-Varying H∞

In this paper, a nonlinear disturbance observer-based adaptive explicit nonlinear model predictive control scheme is proposed to compensate for external disturbance and parametric uncertainty for a class of nonlinear multi-input-multi-output (MIMO) systems. Here, the analytical solution of the proposed adaptive control scheme is developed by approximating the tracking errors and control efforts with the Taylor series expansion method. In this approach, a nonlinear disturbance observer is used to observe the unknown external disturbance of the system. To restrict the parameters from leaving the compact parameter space, an adaptive parameter estimator using projection-based parameter adaptation laws is used. The performance of the designed control technique is enhanced by incorporating the estimated disturbance and estimated system parameters in the updating control law. Using an aerodynamic laboratory set-up known as the twin-rotor MIMO system (TRMS), the effectiveness of the proposed control algorithm has been verified. Simulation and real-time results show that the proposed control algorithm performs better than the existing control algorithm in the presence of unknown external disturbances and parameter uncertainties. 

Nonlinear Disturbance Observer Based Adaptive Explicit Nonlinear Model Predictive Control Design for a Class of Nonlinear MIMO System

The rapid growth of energy demand requires progressive energy generation. This, together with the demand for higher efficiency and flexibility, has promoted the application of power electronics in energy systems. During the past decade, model predictive control (MPC) of power electronics has witnessed significant advancements in both dynamic performance and optimal control of the multi-objective terms. Several of these terms can have equal control priorities, resulting in a symmetrical cost function; however, most objectives have different priorities and require weighting factors to resolve the asymmetry in the cost function. Currently, researchers continue to encounter challenges in the optimal design of weighting factors. Moreover, the relative performance of different techniques that either utilize or avoid the weighting factor are uncertain. Therefore, this study focuses on weighting factor design techniques in the literature as applied to wind/solar energy conversion, microgrids, grid-connected converters, and other high-performance converter-based systems. These are grouped under the heuristic, offline tuning, sequential, and online optimization methods. This study demonstrates that optimal online tuning of weighting factors and sequential MPC methods can both offer improved robustness against parameter uncertainties. In addition, the advantages and limitations of different techniques are highlighted.

/pdf/weighting-factor-design-techniques-for-predictive-control-of-3vavas1d.pdf

Weighting Factor Design Techniques for Predictive Control of Power Electronics and Motor Drives

The matrix representations of hypergraphs have been defined via hypermatrices initially. In recent studies, the Laplacian matrix of hypergraphs, a generalization of the Laplacian matrix, has been introduced. In this article, based on this definition, we derive bounds depending pair-degree, maximum degree, and the first Zagreb index for the greatest Laplacian eigenvalue and Laplacian energy of r-uniform hypergraphs and r-uniform regular hypergraphs. As a result of these bounds, Nordhaus–Gaddum type bounds are obtained for the Laplacian energy.

https://www.mdpi.com/2073-8994/15/2/382/pdf?version=1675235143

On Laplacian Energy of r-Uniform Hypergraphs

In this article, a nonlinear disturbance observer (NDO)-based adaptive explicit nonlinear model predictive control scheme is proposed to compensate for external disturbance and parametric uncertainty for a class of nonlinear multi-input-multi-output (MIMO) systems. Here, the analytical solution of the proposed adaptive control scheme is developed by approximating the tracking errors and control efforts with the Taylor series expansion method. In this approach, a NDO is used to observe the unknown external disturbance of the system. To restrict the parameters from leaving the compact parameter space, an adaptive parameter estimator using projection-based parameter adaptation laws is used. The performance of the designed control technique is enhanced by incorporating the estimated disturbance and estimated system parameters in the updating control law. Using an aerodynamic laboratory set-up known as the twin-rotor MIMO system, the effectiveness of the proposed control algorithm has been verified. Simulation and real-time results show that the proposed control algorithm performs better than the existing control algorithm in the presence of unknown external disturbances and parameter uncertainties.

A cascaded deadbeat predictive control strategy with online disturbance compensation is proposed for a three-phase interleaved boost converter in this paper. The topology of the three-phase interleaved converter is symmetric, so the inner loop controller is also designed symmetrically. For the purpose of realizing the error-free tracking of reference value, the deadbeat predictive control method is adopted for inner and outer loops with Luenberger observers, which are designed to estimate and compensate the disturbances of load variation in the power model as well as the unknown resistor of inductance in the current model. To eliminate the influence of a time delay, a two-step predictive control method is adopted in the predictive model. In the aspect of parameter design, the pole placement method is adopted to determine the gain of the observer. A series of simulations and experiments are carried out to test the proposed strategy under steady and dynamic conditions. It is shown that the proposed control strategy has faster dynamic response and stronger robustness against disturbance than the conventional model predictive control.

/pdf/luenberger-disturbance-observer-based-deadbeat-predictive-3itnygig.pdf

Luenberger Disturbance Observer-Based Deadbeat Predictive Control for Interleaved Boost Converter

The conventional model predictive control (MPC) method of the non-isolated two-stage AC–DC–DC converter has poor robustness and dynamic characteristics under conditions of model mismatch, external disturbance, and load disturbance. To solve this problem, a model-free predictive control method of the converter based on linear extended state observer (LESO) is proposed in this article. First, the ultra-local model of the two-stage converter is constructed to replace the mathematical model. Second, to improve the accuracy of the ultra-local model, LESOs are designed to estimate the uncertain part of each control loop. Third, the cost functions are adopted based on the deadbeat control method to achieve better dynamic performance. Finally, to further reduce the output current ripple, the carrier phase-shifting pulse width modulation is applied. The experimental results verify the high robustness and better control performance of the proposed method in a two-stage converter compared with the conventional MPC method. 

Model‐free predictive control of non‐isolated two‐stage AC–DC–DC converter based on linear extended state observer

This paper proposes a robust adaptive Backstepping controller for the quadrotor attitude dynamics. The attitude dynamic model is obtained to translate into a MIMO nonlinear system with generalized uncertainty. To overcome complex disturbances from various uncertainties, we design a strict feedback controller for the system. It's used to counteract the influence of the uncertainties by robust adaptive function, which includes matched disturbance and unmatched disturbance. We propose a new way to estimate the differential signal of the virtual control law and reduces the “computer explosion” problem. The tracking differentiator system is proved to be stable by the Lyapunov stability theorem. The validity and robustness of the proposed control strategy are demonstrated by simulations.

Robust adaptive nonlinear attitude control for a quadrotor UAV

To realize the brush-less operation for wound field vernier machines (WFVMs), a novel self-excited topology is proposed in this paper which involves a four-pole main armature winding and a two-pole excitation winding connected in series using an uncontrolled rectifier. Upon supplying current from a single current-controlled voltage source inverter (VSI), this procedure results in four-pole and two-pole magnetomotive force (MMF) components in the airgap. The four-pole MMF produces the main stator field while the two-pole MMF component develops a sub-harmonic field in the airgap. The rotor is altered to house a forty-four-pole rotor field and two-pole harmonic windings. The two-pole harmonic field is employed to induce a current in the harmonic winding, which is rectified by means of a full-bridge diode rectifier to energize the rotor field winding and realize brush-less operation for WFVM. Two-dimensional finite element analysis (2-D FEA) is implemented in JMAG-Designer to confirm the operation of the proposed WFVM topology and attain the electromagnetic performance for a four-pole, twenty-four-slot outer-rotor vernier machine.

https://ieeexplore.ieee.org/ielx7/6287639/6514899/09888074.pdf

Novel Self-Excited Brush-Less Wound Field Vernier Machine Topology

The general eccentric connectivity index of a graph R is defined as ξec(R)=∑u∈V(G)d(u)ec(u)α, where α is any real number, ec(u) and d(u) represent the eccentricity and the degree of the vertex u in R, respectively. In this paper, some bounds on the general eccentric connectivity index are proposed in terms of graph-theoretic parameters, namely, order, radius, independence number, eccentricity, pendent vertices and cut edges. Moreover, extremal graphs are characterized by these bounds.

/pdf/bounds-on-the-general-eccentric-connectivity-index-2sy5zwor.pdf

Xinhong Yu

Papers

Luenberger Disturbance Observer-Based Deadbeat Predictive Control for Interleaved Boost Converter

Model‐free predictive control of non‐isolated two‐stage AC–DC–DC converter based on linear extended state observer

Robust adaptive nonlinear attitude control for a quadrotor UAV

Novel Self-Excited Brush-Less Wound Field Vernier Machine Topology

Bounds on the General Eccentric Connectivity Index