Comparison of linear and nonlinear active disturbance rejection control method for hypersonic vehicle

Near space hypersonic vehicles have features of strong coupling, nonlinearity and acute changes in aerodynamic parameters, which are challenging for the controller design. Active disturbance rejection control (ADRC) method does not depend on the accurate system model and has strong robustness against disturbances. This paper discusses the differences between the fractional-order PID (FOPIλDμ) ADRC method and the FOPIλDμ LADRC method for hypersonic vehicles. The FOPIλDμ ADRC controller in this paper consists of a tracking-differentiator (TD), a FOPIλDμ controller and an extended state observer (ESO).The FOPIλDμ LADRC controller consists of the same TD and FOPIλDμ controller with the FOPIλDμ ADRC controller and a linear extended state observer (LESO) instead of ESO. The stability of LESO and the FOPIλDμ LADRC method is detailed analyzed. Simulation results show that the FOPIλDμ ADRC method can make the hypersonic vehicle nonlinear model track desired nominal signals faster and has stronger robustness against external environmental disturbances than the FOPIλDμ LADRC method

Adaptive Multivariable Integral TSMC of a Hypersonic Gliding Vehicle with Actuator Faults and Model Uncertainties

This paper presents a fault-tolerant control (FTC) strategy for a hypersonic gliding vehicle (HGV) subject to actuator malfunctions and model uncertainties. The control-oriented model of the HGV is estabilished according to the HGV kinematic and aerodynamic models. A single-loop design for HGV FTC under actuator faults is subsequently developed, where newly developed multivariable integral terminal sliding mode control (TSMC) and adaptive techniques are integrated. The multivariable integral TSMC is capable of ensuring the finite-time stability of the closed-loop system in the presence of actuator malfunctions and model uncertainties, while the adaptive laws are employed to tune the control parameters in response to the HGV status. Simulation studies based on a six degree-of-freedom (DOF) nonlinear model of the HGV are illustrated to highlight the effectiveness of the developed FTC scheme

Review of advanced guidance and control algorithms for space/aerospace vehicles

The design of advanced guidance and control (G&C) systems for space/aerospace vehicles has received a large amount of attention worldwide during the last few decades and will continue to be a main focus of the aerospace industry. Not surprisingly, due to the existence of various model uncertainties and environmental disturbances, robust and stochastic control-based methods have played a key role in G&C system design, and numerous effective algorithms have been successfully constructed to guide and steer the motion of space/aerospace vehicles. Apart from these stability theory-oriented techniques, in recent years, we have witnessed a growing trend of designing optimisation theory-based and artificial intelligence (AI)-based controllers for space/aerospace vehicles to meet the growing demand for better system performance. Related studies have shown that these newly developed strategies can bring many benefits from an application point of view, and they may be considered to drive the onboard decision-making system. In this paper, we provide a systematic survey of state-of-the-art algorithms that are capable of generating reliable guidance and control commands for space/aerospace vehicles. The paper first provides a brief overview of space/aerospace vehicle guidance and control problems. Following that, a broad collection of academic works concerning stability theory-based G&C methods is discussed. Some potential issues and challenges inherent in these methods are reviewed and discussed. Then, an overview is given of various recently developed optimisation theory-based methods that have the ability to produce optimal guidance and control commands, including dynamic programming-based methods, model predictive control-based methods, and other enhanced versions. The key aspects of applying these approaches, such as their main advantages and inherent challenges, are also discussed. Subsequently, a particular focus is given to recent attempts to explore the possible uses of AI techniques in connection with the optimal control of the vehicle systems. The highlights of the discussion illustrate how space/aerospace vehicle control problems may benefit from these AI models. Finally, some practical implementation considerations, together with a number of future research topics, are summarised

Continuous Recursive Sliding Mode Control for Hypersonic Flight Vehicle with Extended Disturbance Observer

A continuous recursive sliding mode controller (CRSMC) with extended disturbance observer (EDO) is proposed for the longitudinal dynamics of a generic hypersonic flight vehicle (HFV) in the presence of multiple uncertainties under control constraints. Firstly, sliding mode tracking controller based on a set of novel recursive sliding mode manifolds is presented, in which the chattering problem is reduced. The CRSMC possesses the merits of both nonsingular terminal sliding mode controller (NTSMC) and high-order sliding mode controller (HOSMC). Then antiwindup controller is designed according to the input constraints, which adds a dynamic compensation factor in the CRSMC. For the external disturbance of system, an improved disturbance observer based on extended disturbance observer (EDO) is designed. The external disturbance is estimated by the disturbance observer and the estimated value is regarded as compensation in CRSMC for disturbance. The stability of the proposed scheme is analyzed by Lyapunov function theory. Finally, numerical simulation is conducted for cruise flight dynamics of HFV, where altitude is 110000 ft, velocity is 15060 ft/s, and Mach is 15. Simulation results show the validity of the proposed approach

Robustness analysis of fractional order PID for an electrical aerial platform

This work was performed to objectively measure and assess the robustness and tracking performance of fractional order of proportional, integral and derivative (FOPID) controller as compared to the conventional PID control. In satellite research and development, the satellite undergoes numerous tests such as thermal, acoustic and vibration tests in the cleanroom environment. However, due to space limitation in the cleanroom and the sensitive components of the satellite, it requires vibration-free, smooth and precise motion when handling the satellite. In addition, measurement interference might occur due to cable routing during procedures or tasks performed by an operator. Unlike the previous work, the robustness analysis of FOPID controller was not systematically conducted. In this paper, the analysis took into account the actuator dynamics, and various tests were considered to measure the robustness of FOPID controller. The designed FOPID controller was implemented on the scissor-type lifting mechanism of motorized adjustable vertical platform (MAVeP) model, and its performance was compared with the traditional PID controller. A comprehensive verification using MATLAB and Solidworks was carried out to generate the model and conduct the analysis. Both controllers were initially tuned using Nichol-Ziegler technique, and the additional FOPID controller parameters was tuned using the Astrom-Hagglund method. From the simulation work, it was found that the FOPID controller’s tracking error was reduced between 10 % - 50 % for the disturbance rejection tests and reference to disturbance ratio (RDR) spectrum was higher as compared to PID. The analysis in this paper was predicted to be the main driver to implement FOPID controller in the complex system in the industry, especially for sensitive material handling and transportation such as satellite

Observer-based adaptive sliding mode fault-tolerant control for the underactuated space robot with joint actuator gain faults

summary:An adaptive sliding mode fault-tolerant controller based on fault observer is proposed for the space robots with joint actuator gain faults. Firstly, the dynamic model of the underactuated space robot is deduced combining conservation law of linear momentum with Lagrange method. Then, the dynamic model of the manipulator joints is obtained by using the mathematical operation of the block matrices, hence the measurement of the angular acceleration of the base attitude can be omitted. Subsequently, a fault observer which can accurately estimate the gain faults is designed, and the estimated results are fed back to the adaptive sliding mode fault-tolerant controller. It is proved that the proposed control algorithm can guarantee the global asymptotic stability of the closed-loop system through the Lyapunov theorem. The simulation results authenticate the effectiveness and feasibility of the control strategy and observation scheme

Optimized state feedback regulation of 3DOF helicopter system via extremum seeking

In this paper, an optimized state feedback regulation of a 3 degree of freedom (DOF) helicopter is designed via extremum seeking (ES) technique. Multi-parameter ES is applied to optimize the tracking performance via tuning State Vector Feedback with Integration of the Control Error (SVFBICE). Discrete multivariable version of ES is developed to minimize a cost function that measures the performance of the controller. The cost function is a function of the error between the actual and desired axis positions. The controller parameters are updated online as the optimization takes place. This method significantly decreases the time in obtaining optimal controller parameters. Simulations were conducted for the online optimization under both fixed and varying operating conditions. The results demonstrate the usefulness of using ES for preserving the maximum attainable performance

Fast terminal sliding-mode finite-time tracking control with differential evolution optimization algorithm using integral chain differentiator in uncertain nonlinear systems

This paper presents a fast terminal sliding-mode tracking control for a class of uncertain nonlinear systems with unknown parameters and system states combined with time-varying disturbances. Fast terminal sliding-mode finite-time tracking systems based on differential evolution algorithms incorporate an integral chain differentiator (ICD) to feedback systems for the estimation of the unknown system states. The differential evolution optimization algorithm using ICD is also applied to a tracking controller, which provides unknown parametric estimation in the limitation of unknown system states for trajectory tracking. The ICD in the tracking systems strengthens the tracking controller robustness for the disturbances by filtering noises. As a powerful finite-time control effort, the fast terminal sliding-mode tracking control guarantees that all tracking errors rapidly converge to the origin. The effectiveness of the proposed approach is verified via simulations, and the results exhibit high-precision output tracking performance in uncertain nonlinear systems

Introduction to State Estimation of High-Rate System Dynamics

Engineering systems experiencing high-rate dynamic events, including airbags, debris detection, and active blast protection systems, could benefit from real-time observability for enhanced performance. However, the task of high-rate state estimation is challenging, in particular for real-time applications where the rate of the observer’s convergence needs to be in the microsecond range. This paper identifies the challenges of state estimation of high-rate systems and discusses the fundamental characteristics of high-rate systems. A survey of applications and methods for estimators that have the potential to produce accurate estimations for a complex system experiencing highly dynamic events is presented. It is argued that adaptive observers are important to this research. In particular, adaptive data-driven observers are advantageous due to their adaptability and lack of dependence on the system model

Backstepping control with fixed-time prescribed performance for fixed wing UAV under model uncertainties and external disturbances

In this paper, a novel backstepping control scheme with fixed-time prescribed performance is proposed for the longitudinal model of fixed wing UAV subject to model uncertainties and external disturbances. The novel performance function with arbitrarily preassigned fixed-time convergence property is developed, which imposes priori performance envelops on both altitude and airspeed tracking errors. By using error transformed technology, the constrained fixed-time performance envelops are changed into unconstrained equivalent errors. Based on modified error compensation mechanism, a novel backstepping approach is proposed to guarantee altitude tracking equivalent error converges to the specified small neighborhood and presents excellent robustness against model uncertainties and external disturbances, and airspeed controller with fixed-time prescribed performance is designed. The proposed methodology guarantees the transient and steady-state performance of altitude and airspeed tracking errors within constrained fixed-time performance envelops in spite of lumped disturbances. Finally, numerical simulations are used to verify the effectiveness of the proposed control schem