Control Law Design Research Articles

Reconfiguration Control Design of UAV against Actuator Faults Based on Control Allocation Method

The paper concentrates on the problem of fault-tolerant control of UAV against actuator faults from the perspective of flight control system architecture. Using backstepping control method and inverse optimization theory, the design of backstepping optimal control law was constructed. Based on the fault monitoring mechanism of vehicle management computer in the distributed flight control and control allocation system, a fault-tolerant control design method was established in the case of multiple failure modes of the actuators, which compensates the influence caused by the failures. Finally, the effectiveness of the proposed strategy was verified by numerical simulation.

Forced sliding mode control for chaotic systems synchronization

Synchronization of chaotic systems is considered to be a common engineering problem. However, the proposed laws of synchronization control do not always provide robustness toward the parametric perturbations. The purpose of this article is to show the use of synergy-cybernetic approach for the construction of robust law for Arneodo chaotic systems synchronization. As the main method of design of robust control, the method of design of control with forced sliding mode of the synergetic control theory is considered. To illustrate the effectiveness of the proposed law, in this article it is compared with the classical sliding mode control and adaptive backstepping. The distinctive features of suggested robust control law are the more good compensation of parametric perturbations (better performance indexes—the root-mean-square error (RMSE), average absolute value (AVG) of error) without designing perturbation observers, the ability to exclude the chattering effect, less energy consuming and a simpler analysis of the stability of a closed-loop system. The study of the proposed control law and the change of its parameters and the place of parametric perturbation’s application is carried out. It is possible to significantly reduce the synchronization error and RMSE, as well as AVG of error by reducing some parameters, but that leads to an increase in control signal amplitude. The place of application of parametric disturbances (slave or master system) has no effect on the RMSE and AVG of error. Offered approach will allow a new consideration for the design of robust control laws for chaotic systems, taking into account the ideas of directed self-organization and robust control. It can be used for synchronization other chaotic systems.

Revised semi-empirical aerodynamic estimation for modelling flight dynamics of an airship

Modelling of dynamics of an airship is essential in the prediction of the flight characteristics, stability analysis and the design of control laws for autonomous operation. In the dynamics model that was proposed by Ashraf and Choudhry [1], deviations were observed between the simulation results and the validation data since the lengths and areas associated with the calculation of aerodynamic coefficients were not normalised. This paper documents the revisions proposed to the incorporation of semi-empirical aerodynamic estimation technique in the dynamics modelling of an airship as well as the normalisation of aerodynamic coefficients. Simulations are performed on the revised airship dynamics model and are compared with the simulation results of preceding models. A satisfactory agreement is seen between the revised model and the validation data, both in terms of magnitude and trends.

Fuzzy-Based Adaptive Dynamic Surface Control for a Type of Uncertain Nonlinear System with Unknown Actuator Faults

In this paper, the adaptive control problem of a type of uncertain nonlinear system is addressed. The system discussed includes unknown nonlinear functions, uncertain nonlinear dynamics, and unknown actuator faults. Based on the fuzzy logic systems and dynamic surface control technique, an adaptive fuzzy control law is designed to solve the tracking control problem. In control law design, fuzzy logic systems are utilized to approximate uncertain nonlinear functions, and with the help of the dynamic surface control technique, the problem of the “explosion of complexity” can be overcome. Through stability analysis, it is confirmed that all of the signals in the closed-loop system are semi-global bounded, and the convergence of the tracking error to the specified small neighborhood of the origin can be ensured by adjusting the control law parameters. Finally, the effectiveness of the proposed control law is verified by simulation examples.

Robust feedback feed-forward PD-type iterative learning control for uncertain discrete systems over finite frequency ranges

This paper proposes a robust feedback feed-forward proportional-derivative type (PD-type) iterative learning control (ILC) scheme for a class of linear discrete systems with polytopic uncertainty over finite frequency ranges. First, the ILC process is transformed into an equivalent discrete linear repetitive process. Then, with the help of the generalized Kalman–Yakubovich–Popov lemma, the issue of a robust control law design algorithm in the process model is converted into the problem of solutions to the corresponding linear matrix inequality conditions. This procedure not only meets the robust performance specifications along the trial, but also guarantees the monotonic converge of the trial-to-trial error dynamics over finite frequency ranges. Finally, the simulations for a direct current servo motor system are adopted to show the effectiveness and superiority of the proposed method. Compared with previously established works, the new algorithm is more effective in delivering higher performance and achieving better tracking effect.

Control Algorithm for Trajectory Tracking of an Underactuated USV under Multiple Constraints

A trajectory tracking control method based on the cascade of optimal guidance and adaptive control laws was proposed for trajectory tracking of an unmanned surface vehicle under multiple motion constraints including an ocean current disturbance environment. Considering the velocity and acceleration constraints, angular velocity, and angular acceleration constraints in guidance law design, motion planning was conducted with three degrees of freedom using a motion model and predictive control, while optimal guidance law was designed through a rolling optimization strategy to stabilize the position error under multiple constraints. Moreover, the stability of the guidance law was proven. In control law design, an adaptive observer was introduced to estimate and compensate for ocean current disturbance, which affected the precision of control. The course and velocity control laws were designed with the adaptive sliding mode control technology to stabilize the course angle and longitudinal velocity errors; the stability of these control laws was further proven. Based on the system design, the stability of the entire closed-loop control system was proven with the cascade system and Lyapunov theory. Theoretical analysis and simulation experiments demonstrated the effectiveness and advancement of the proposed algorithm.

Complex Power Sharing Is Not Complex

This paper presents a distributed complex power sharing approach that solves the problem of active and reactive power sharing in inverter-based islanded microgrids. Previous state-of-the-art strategies based on droop controls with possibly virtual impedance methods and supplemented with hierarchical schemes may provide poor power sharing due to the R/X ratio and mismatched line impedances, even compromising microgrids stability if droop control parameters are not properly set. The novel control approach, that uses a communication network to exchange data among all inverters to fairly inject power, provides a set of appealing properties. First, it achieves accurate active and reactive power sharing for both resistive and inductive power lines with no additional control cost (avoiding unnecessary power injections), and regardless of load changes and connections and disconnections of inverters. Moreover, it ensures an exponential convergence rate, and the tuning of the control parameters can not compromise microgrid stability. The theoretical development relies on a change of variables that linearizes the complex power dynamics, thus easing the control law design task and providing the means for computing the appropriate amplitude and phase for each inverter output voltage. Selected experimental results on a laboratory microgrid certify the applicability and performance of the proposed control scheme.

Port-Hamiltonian Control of Nuclear Reactors

The port-Hamiltonian form (PHF) of nuclear reactor dynamics is first given with the corresponding Hamiltonian function determined by the shifted-ectropies of neutron kinetics and reactor thermal-hydraulics. Then, a passivity-based control (PBC) is proposed by adding extra damping injections to the PHF, and it is shown by theoretical analysis that satisfactory closed-loop stability can be guaranteed. The newly designed control law is applied to a nuclear heating reactor, and the simulation results not only verify the theoretical analysis but also show the satisfactory reactor power-level control performance.

Robust Fuzzy Control for Uncertain Nonlinear Power Systems

This paper presents a new control technique based on uncertain fuzzy models for handling uncertainties in nonlinear dynamic systems. This approach is applied for the stabilization of a multimachine power system subject to disturbances. In this case, a state-feedback controller based on parallel distributed compensation (PDC) is applied for the stabilization of the fuzzy system, where the design of control laws is based on the Lyapunov function method and the stability conditions are solved using a linear matrix inequalities (LMI)-based framework. Due to the high number of system nonlinearities, two steps are followed to reduce the number of fuzzy rules. Firstly, the power network is subdivided into sub-systems using Thevenin’s theorem. Actually, each sub-system corresponds to a generator which is in series with the Thevenin equivalent as seen from this generator. This means that the number of sub-systems is equal to the number of system generators. Secondly, the significances of the nonlinearities of the sub-systems are ranked based on their limits and range of variation. Then, nonlinearities with non-significant variations are assumed to be uncertainties. The proposed strategy is tested on the Western systems coordinating council (WSCC) integrated with a wind turbine. The disturbances are assumed to be sudden variations in wind power output. The effectiveness of the suggested fuzzy controller is compared with conventional regulators, such as an automatic voltage regulator (AVR) and power system stabilizers (PSS).

Design and Flight Test of a Stability Augmentation System for a Flexible Aircraft

Control law design for flexible aircraft with coupled flight and structural dynamics is currently a challenge. If not correctly addressed during control law design, the aeroservoelastic coupling can negatively affect the lateral-directional stability of the aircraft. In this context, this paper describes a methodology for the design of a stability augmentation system for the Instituto Tecnológico de Aeronáutica X-HALE flexible aircraft and proposes a performance index for numerical optimization of the closed-loop feedback gains. Comparisons between open-loop and closed-loop numerical simulation results show how the proposed control system attenuates the Dutch-roll response. An aeroservoelastic analysis is made in which it its demonstrated that the control system has small but beneficial effects on aeroelastic stability. Finally, experimental data obtained via flight tests with the real aircraft demonstrate the effectiveness of the control system in practice.

Advances in Variable Stiffness Vibration Isolator and its Application in Spacecraft

Variable stiffness vibration isolator (VSVI) can be switched between the low stiffness state and high stiffness state, respectively suitable for spacecraft requirement in cutting off the jitter transmitted from the bus to high accuracy payload and for avoiding long term adjustment during the process of attitude maneuver. For the advantage stated, the mechanism of VSVI is investigated for several types, considering the following factors: parallel manipulator with positive and negative stiffness components, structure with nonlinearity stiffness characteristics, smart materials or mechanisms, and maglev configuration. The design objectives of variable mechanisms are summarized into three indexes: adjustment range of stiffness, a lower limit of resonant frequency, and region with quasi-zero stiffness. Experimental studies for related isolators were presented, and the typical configuration or schematic diagram was shown under each index. As for the application of VSVI in spacecraft, research on the two significant problems, i.e. dynamic modeling and non-collocated control problem, is investigated for the design of control law of VSVI’s stiffness. Besides the complete description of spacecraft flexibility, variable stiffness characteristic that leads to a time-varying system and is easily coupled with the maneuvering process is worthy of more attention. Finally, challenges and future research are suggested for improving the performance in spacecraft application.

Adaptive neural network dynamic surface control of uncertain strict-feedback nonlinear systems with unknown control direction and unknown actuator fault

In this paper, the tracking control problem of a class of uncertain strict-feedback nonlinear systems with unknown control direction and unknown actuator fault is studied. By using the neural network control approach and dynamic surface control technique, an adaptive neural network dynamic surface control law is designed. Based on the neural network approximator, the uncertain nonlinear dynamics are approximated. Using the dynamic surface control technique, the complexity explosion problems in the design of virtual control laws and adaptive updating laws can be overcome. Moreover, to solve the unknown control direction and unknown actuator fault problems, a type of Nussbaum gain function is incorporated into the recursive design of dynamic surface control. Based on the designed adaptive control law, it can be confirmed that all of the signals in the closed-loop system are semi-global bounded, and the convergence of the tracking error to the specified small neighborhood of the origin could be ensured by adjusting the designing parameters. Finally, two examples are provided to demonstrate the effectiveness of the proposed adaptive control law.

Passivity voltage based control of the boost power converter used in photovoltaic system

Introduction. This paper presents a robust nonlinear control of the DC-DC boost converter feeding by a photovoltaic system based on the passivity control. The control law design uses the passivity approach. Novelty. The novelty consists in designing a control law for a photovoltaic system using a passivity approach based on energy shaping and associated with damping injection. Purpose. The purpose consists to develop a tool for design and optimize a control law of the photovoltaic system in order to improve its efficiency under some conditions such as the variations of the temperature, the irradiation and the parameters. Also, the control law design should be simple with a lower overshoot and a shorter settling time. Methods. This work uses the port Hamiltonian mathematical approach with minimization of the energy dissipation in boost converter of the photovoltaic system to illustrate the modification of energy and generate a specify duty cycle applied to the converter. Results. The results with MATLAB/SimPowerToolbox® have proven the robustness against parameter variations and effectiveness of the proposed control. Practical value. The experimental results, carried out using a dSPACE DS1104 system, are presented to show the feasibility and the robustness of the proposed control strategy against parameter variations.

Incorporating Physical Models for Dynamic Stall Prediction Based on Machine Learning

Unsteady aerodynamic prediction is an important part of modern aircraft safety and control law design. To improve the accuracy and efficiency for unsteady aerodynamic prediction of aircraft at high angles of attack, this paper proposed a machine learning framework based on multifidelity methods. The framework combines the linear dynamic derivative model and the fuzzy neural network model, which can achieve higher prediction accuracy under sparse experimental states. A series of wind-tunnel tests was carried out for the pitching motions of NASA Common Research Model at high angles of attack, to obtain steady and unsteady aerodynamic loads. These experimental data are used to verify the prediction accuracy of the unsteady model in a wide range of oscillation amplitude, frequencies, and mean angles of attack. The results show that the method has good generalization capability for the parameters of interest. At the same time, the comparison with the prediction results only from high-fidelity data shows that the proposed method can effectively reduce the amount of data required for the model of training and improve the modeling robustness to different types of motions.

Vertical take-off and landing hybrid unmanned aerial vehicles: An overview

AbstractThis article presents the research status and development trends of Vertical Take-off and Landing hybrid Unmanned Aerial Vehicles. In this research, a special emphasis is laid on the design philosophies, analysis techniques, dynamic modeling, and control laws of hybrid VTOL UAVs. It studies and compares various design configurations of hybrid VTOL UAVs, based on key design features such as aerodynamic performance, flight stability, structural strength, propulsive power, avionics systems, flight controls, autonomy, ease of fabrication and flight transition mechanisms. The benefits and shortcomings of each design configuration are expressed in detail. A selection problem is formulated in a fuzzy environment and the Multi-Attribute Decision-Making technique is employed. Ongoing research projects in the field are discussed and a novel design of tail sitter hybrid VTOL UAV is presented by the authors. This work serves as a useful guide for the prospective explorers of this challenging field of research.

Synchronisation of Unified Chaotic Systems Using Modified Nonlinear Active Control: Circuit Design, Implementation, and Secure Communication

This paper accounts synchronisation of unified chaotic systems using a modified nonlinear active control technique, its circuit analogue circuit implementation, and secure communication. The proposed nonlinear active control approach utilises appropriate states of the unified chaotic systems. The modified nonlinear active control leads to the coupled error dynamics and does not require the external forcing parameters or gains, which differs from the active control techniques reported in the literature. The designed control law ensures the asymptotic stability in large, and the necessary condition is derived using Lyapunov stability theory. Further, the performance of the designed nonlinear active controller is compared based on different time integral performance of the errors with active, adaptive, and sliding mode control techniques. Numerical and circuit simulations are performed in MATLAB and NI-Multisim environments, respectively. Circuit simulated results accord to MATLAB simulation results. Further, unified chaotic system, its synchronisation, and application to secure communication are validated with breadboard circuit/hardware implementation.

A Robust Dynamic Control Strategy for Standalone PV System under Variable Load and Environmental Conditions

Dual-stage standalone photovoltaic (PV) systems suffer from stability, reliability issues, and their efficiency to deliver maximum power is greatly affected by changing environmental conditions. A hybrid back-stepping control (BSC) is a good candidate for maximum power point tracking (MPPT) however, there are eminent steady-state oscillations in the PV output due to BSC’s recursive nature. The issue can be addressed by proposing a hybrid integral back-stepping control (IBSC) algorithm where the proposed integral action significantly reduces the steady-state oscillations in the PV array output under varying temperature and solar irradiance level. Simultaneously, at the AC stage, the primary challenge is to reduce both the steady-state tracking error and total harmonic distortion (THD) at the output of VSI, resulting from the load parameter variations. Although the conventional sliding mode control (SMC) is robust to parameter variations, however, it is discontinuous in nature and inherit over-conservative gain design. In order to address this issue, a dynamic disturbance rejection strategy based on super twisting control (STC) has been proposed where a higher order sliding mode observer is designed to estimate the effect of load disturbances as a lumped parameter which is then rejected by the newly designed control law to achieve the desired VSI tracking performance. The proposed control strategy has been validated via MATLAB Simulink where the system reaches the steady-state in 0.005 s and gives a DC–DC conversion efficiency of 99.85% at the peak solar irradiation level. The AC stage steady-state error is minimized to 0 V whereas, THD is limited to 0.07% and 0.11% for linear and non-linear loads, respectively.

A symplectic direct method for motion-driven optimal control of mechanical systems

For many practical actuators, laws of motion quantities are directly imposed to control the motion of mechanical systems. Motivated by this point, considering motion quantities as control inputs is more practical and applicable. Therefore, in this paper, a novel and valuable idea is to design control laws of motion quantities to drive mechanical systems which can be optimal and meet specified requirements. To find the control laws of motion quantities, we establish motion-driven optimal control problems of mechanical systems in this paper. For solving this kind of problems, nonlinear dynamical equations need to be discretized. If dynamical equations cannot be approximated well, results will be inaccurate, unreliable, and even distorted. To overcome this difficulty, in this paper, we further proposed a symplectic-preserving method to solve the motion-driven optimal control problems. In the proposed method, a symplectic-preserving discrete formula for dynamical equations with motion-driven constraints is proposed. It can provide excellent approximation quality. Three numerical examples of typical nonlinear crane systems are tested to show the performance of the proposed method. The energy deviation of the proposed method is sufficiently small even if sparse time intervals are set. Thus the energy behavior of the original mechanical systems is preserved well. If the obtained control inputs are imposed to systems, the systems can reach the given terminal state more accurately. Thus the obtained control inputs are more accurate and reliable. Besides, the proposed method can directly consider inequality constraints of velocity level and the inequality constraints can be strictly satisfied.

A Unified Approach for Finite-Time Global Stabilization of Affine, Rigid, and Translational Formation

This article studies the multiagent control problem for affine, rigid, and translational formation, with the aim of developing a unified distributed control strategy for global and finite-time convergence. Global stabilization of rigid formation in arbitrary dimensional spaces still remains open and challenging. This article provides a general solution to this open problem based on the sliding mode control idea. The control law design consists of two parts: the main control force regulates the trajectories of all agents to reach a sliding surface defined by an affine formation space in finite time and remain in it thereafter; the extra control force governs certain chosen leader agents towards the desired formation in the sliding surface. The article then presents in detail two approaches for designing the extra control force, one based on distance constraints and the other based on relative position constraints. For the first time, the proposed sliding mode formation control laws solve the open problem of (almost) global and finite-time stabilization of affine, rigid, and translational formations in any dimensional space. Simulation results are provided to illustrate the effectiveness of the proposed control schemes.

Waypoint Tracking Control for Autonomous Mobile Sampling and Dissolved Oxygen Enrichment of Unmanned Surface Vehicle

An autonomous monitoring and control system of unmanned surface vehicle (USV) with mobile water quality monitoring, sampling, and oxygenation functions is constructed. The control hardware and monitoring configuration software of the system is designed, respectively, which can be installed on USV and its remote control and monitoring terminal. The kinematic modeling of USV, waypoint trajectory-tracking control, distributed controller, simulation of tracking control, and verification of software and hardware design are carried out. In order to reject the system noise and external noise, a states estimation method with fully observable states is considered in the control law design. The software and hardware are also implemented to verify the effectiveness of the monitoring platform. Through setting a series of monitoring target points and monitoring parameters in the configuration software of the remote user terminal or in the APP of the mobile user terminal, the USV can realize the automatic cruise monitoring using an autonomous navigation and tracking control algorithm, and quantitative water sampling collection. The reliability of the system is verified by the experiment of the shore test station, and the waypoint trajectory tracking and sensors data are replaying in a logview GUI of MOOS-Ivp and APP.