Continuous higher order sliding mode control with adaptation of air breathing hypersonic missile

This is the peer reviewed version of the following article: Yu, P., Shtessel, Y., and Edwards, C. (2016) Continuous higher order sliding mode control with adaptation of air breathing hypersonic missile. International Journal of Adaptive Control and Signal Processing, which has been published in final form at 10.1002/acs.2664. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving: http://olabout.wiley.com/WileyCDA/Section/id-820227.html#terms}Hypersonic missile control in the terminal phase is addressed using continuous higher order sliding mode (AHOSM) control with adaptation. The AHOSM self-tuning controller is proposed and studied. The double-layer adaptive algorithm is based on equivalent control concepts and ensures non-overestimation of the control gain to help mitigates control chattering. The proposed continuous AHOSM control is validated via simulations of a hypersonic missile in the terminal phase. The robustness and high accuracy output tracking in the presence of matched and unmatched external disturbances and missile model uncertainties is demonstrate

Observer-Based Nonlinear Dynamic Inversion Adaptive Control with State Constraints

Hypersonic vehicle research and development has grown recently in the aerospace industry due to the powerful potential of operating a vehicle that flies at substantially higher speeds than typical aircraft. From a guidance, navigation and control perspective, hypersonic vehicles are particularly interesting due both to inherent vehicle complexities as well as practical concerns that only arise at high Mach numbers. Challenges inherent to the vehicle include nonlinearities, a wide range of operating conditions, high elasticity, high temperatures and parametric uncertainty. Although these challenges have by no means fully been explored in the literature, in the realm of control theory, they are somewhat common. Hypersonic vehicle control is difficult however, because in addition to these more traditional complexities a control designer must also deal with problems very specific to flying at high speeds such as: inlet unstart, overcoming sensing deficiencies at high speeds and creating an implementable digital control framework for a plant with extremely fast dynamics. This dissertation develops three novel theoretical approaches for addressing these challenges through advances in the nonlinear dynamic inversion adaptive control technique. Although hypersonic vehicle control is the motivation and often the application that the control algorithms in this dissertation are tested on, several of the theoretical developments apply to a general class of nonlinear continuous time systems. First, in order to address the problem of inlet unstart, two state constraint mechanisms which integrate into the nonlinear dynamic inversion adaptive control framework are presented. These state constraining control laws require full state feedback and are capable of restricting the outputs of nonlinear systems containing parameter uncertainty to specific regions of the state-space. The first state constraint mechanism achieves this objective using sliding mode control and the second uses bounding functions to smoothly adjust the control and adaptive laws and drive the states toward the origin when constraints are approached. Stability is proven using Lyapunov analysis and these techniques are demonstrated in a nonlinear simulation of a hypersonic vehicle. Second, an observer-based feedback controller is developed that allows for a nonlinear system to track a reference trajectory with bounded errors and without measuring multiple states. Again, the technique used is nonlinear dynamic inversion adaptive control, but because of uncertainty in the system state, it is not assumed that the nonlinear control effectiveness matrix can be canceled perfectly. A nonlinear observer is implemented to estimate the values of the unknown states. This observer allows for the closed-loop stability of the system to be proven through Lyapunov analysis. It is shown that parametric uncertainty can successfully be accounted for using an adaptive mechanism and that all tracking and estimation errors are uniformly ultimately bounded. Finally, a sampled-data nonlinear dynamic inversion adaptive control architecture is introduced. Despite the prevalence of digital controllers in practice, a nonlinear dynamic inversion adaptive control scheme in a sampled-data setting has not previously been developed. The method presented in this dissertation has the capability of extending the benefits of nonlinear dynamic inversion adaptive control - robust control of nonlinear systems with respect to model uncertainty - to more practical platforms

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

Fault Diagnosis Techniques for Linear Sampled Data Systems and a Class of Nonlinear Systems

This thesis deals with the fault diagnosis design problem both for dynamical continuous time systems whose output signal are affected by fixed point quantization,\ud referred as sampled-data systems, and for two different applications whose dynamics are inherent high nonlinear: a remotely operated underwater vehicle and a scramjet-powered hypersonic vehicle.\ud Robustness is a crucial issue. In sampled-data systems, full decoupling of disturbance terms from faulty signals becomes more difficult after discretization.\ud In nonlinear processes, due to hard nonlinearity or the inefficiency of linearization, the “classical” linear fault detection and isolation and fault tolerant control methods may not be applied.\ud Some observer-based fault detection and fault tolerant control techniques are studied throughout the thesis, and the effectiveness of such methods are validated with simulations. The most challenging trade-off is to increase sensitivity to faults and robustness to other unknown inputs, like disturbances. Broadly speaking, fault detection filters are designed in order to generate analytical diagnosis functions, called residuals, which should be independent with respect to the system operating state and should be decoupled from disturbances. Decisions on the occurrence of a possible fault are therefore taken on the basis such residual signals

The Design of Fixed-Time Observer and Finite-Time Fault-Tolerant Control for Hypersonic Gliding Vehicles

This paper proposes a fault-tolerant control scheme for a hypersonic gliding vehicle to counteract actuator faults and model uncertainties. Starting from the kinematic and aerodynamic models of the hypersonic vehicle, the control-oriented model subject to actuator faults is built. The observers are designed to estimate the information of actuator faults and model uncertainties, and to guarantee the estimation errors for converging to zero in fixed settling time. Subsequently, the finite-time multivariable terminal sliding mode control and composite-loop design are pursued to enable integration into the faulttolerant control, which can ensure the safety of the postfault vehicle in a timely manner. Simulation studies of a six degree-of-freedom nonlinear model of the hypersonic gliding vehicle are carried out to manifest the effectiveness of the investigated fault-tolerant control system

Disturbance rejection flight control for small fixed-wing unmanned aerial vehicles

Disturbance rejection flight control for small fixed-wing unmanned aerial vehicle

Stabilization of pan-tilt systems using acceleration based LMI-LQR controller

This paper extends the previous work on LPV modeling of a pan-tilt system [1] and tackles the robust stabilization problem by employing angular acceleration feedback in an LMI based optimal LQR controller. The state vector of the LPV model is augmented to include the integral of the position errors in addition to joint angles and velocities. Therefore, an extended polytopic quasi-LPV model of the pan tilt system is derived. The LMI based optimal LQR controller that utilizes acceleration feedback is synthesized based on the extended LPV model. Since the time varying parameter vector is 4 dimensional, the proposed controller is synthesized by interpolating LMIs at 16 vertices of the polytope. A cascaded nonlinear high gain observer is also designed to estimate reliable positions, velocities and accelerations from noisy encoder measurements. Simulation results show that the proposed LMI based optimal LQR controller outperforms the classical LMI based LQR controller

Observer-Based Nonlinear Dynamic Inversion Adaptive Control with State Constraints

Hypersonic vehicle research and development has grown recently in the aerospace industry due to the powerful potential of operating a vehicle that flies at substantially higher speeds than typical aircraft. From a guidance, navigation and control perspective, hypersonic vehicles are particularly interesting due both to inherent vehicle complexities as well as practical concerns that only arise at high Mach numbers. Challenges inherent to the vehicle include nonlinearities, a wide range of operating conditions, high elasticity, high temperatures and parametric uncertainty. Although these challenges have by no means fully been explored in the literature, in the realm of control theory, they are somewhat common. Hypersonic vehicle control is difficult however, because in addition to these more traditional complexities a control designer must also deal with problems very specific to flying at high speeds such as: inlet unstart, overcoming sensing deficiencies at high speeds and creating an implementable digital control framework for a plant with extremely fast dynamics. This dissertation develops three novel theoretical approaches for addressing these challenges through advances in the nonlinear dynamic inversion adaptive control technique. Although hypersonic vehicle control is the motivation and often the application that the control algorithms in this dissertation are tested on, several of the theoretical developments apply to a general class of nonlinear continuous time systems. First, in order to address the problem of inlet unstart, two state constraint mechanisms which integrate into the nonlinear dynamic inversion adaptive control framework are presented. These state constraining control laws require full state feedback and are capable of restricting the outputs of nonlinear systems containing parameter uncertainty to specific regions of the state-space. The first state constraint mechanism achieves this objective using sliding mode control and the second uses bounding functions to smoothly adjust the control and adaptive laws and drive the states toward the origin when constraints are approached. Stability is proven using Lyapunov analysis and these techniques are demonstrated in a nonlinear simulation of a hypersonic vehicle. Second, an observer-based feedback controller is developed that allows for a nonlinear system to track a reference trajectory with bounded errors and without measuring multiple states. Again, the technique used is nonlinear dynamic inversion adaptive control, but because of uncertainty in the system state, it is not assumed that the nonlinear control effectiveness matrix can be canceled perfectly. A nonlinear observer is implemented to estimate the values of the unknown states. This observer allows for the closed-loop stability of the system to be proven through Lyapunov analysis. It is shown that parametric uncertainty can successfully be accounted for using an adaptive mechanism and that all tracking and estimation errors are uniformly ultimately bounded. Finally, a sampled-data nonlinear dynamic inversion adaptive control architecture is introduced. Despite the prevalence of digital controllers in practice, a nonlinear dynamic inversion adaptive control scheme in a sampled-data setting has not previously been developed. The method presented in this dissertation has the capability of extending the benefits of nonlinear dynamic inversion adaptive control - robust control of nonlinear systems with respect to model uncertainty - to more practical platforms