High-order Sliding Mode Observer Research Articles

Adaptive fractional-order blood glucose regulator based on high-order sliding mode observer.

Type I diabetes is described by the destruction of the insulin-producing beta-cells in the pancreas. Hence, exogenous insulin administration is necessary for Type I diabetes patients. In this study, to estimate the states that are not directly available from the Bergman minimal model a high-order sliding mode observer is proposed. Then fractional calculus is combined with sliding mode control (SMC) for blood glucose regulation to create more robustness performance and make more degree of freedom and flexibility for the proposed method. Then an adaptive fractional-order SMC is proposed. The adaptive SMC protect controller against disturbance and uncertainties while the fractional calculus provides robust performance. Numerical simulation verifies that the proposed controllers have better performance in the presence of disturbance and uncertainties without chattering.

Fault-tolerant control for over-actuated hypersonic reentry vehicle subject to multiple disturbances and actuator faults

In this paper, a fault-tolerant control scheme is proposed for attitude tracking problem of hypersonic reentry vehicle subjected to multiple disturbances and time-varying actuator faults. For convenience of fault-tolerant controller design, conventional hypersonic reentry vehicle model is transformed into control-oriented model by incorporating actuator faults into lumped disturbance. Based on the lumped disturbance estimate provided by high order sliding mode observer, fault-tolerant controllers are developed within the frame of active disturbance rejection control in attitude loop and angular rate loop according to time-scale separation and singular perturbation principle. Then, the desired control moment is allocated to actuators based on recurrent neural network. With the well-designed fault-tolerant controllers and control allocation, a novel meta-heuristic dynamic adaptation salp swarm algorithm is employed to optimize control parameters to achieve minimum attitude tracking error. Comparative simulations are conducted to verify the effectiveness of the developed dynamic adaptation salp swarm algorithm and the investigated fault-tolerant control scheme.

Adaptive super-twisting sliding mode observer based robust backstepping sensorless speed control for IPMSM

This paper proposes a higher-order sliding mode observer based robust backstepping control to realize high-performance sensorless speed regulation for the interior permanent magnet synchronous motor (IPMSM). A new robust adaptive super-twisting higher-order sliding mode based observer is proposed to estimate the rotor position. The proposed observer has advantages of sliding chattering reduction and robustness against uncertainties. And, a new robust integral adaptive backstepping control with sliding mode actions is designed to achieve precise speed regulation. The uncertainties with unknown bounds can be stabilized by the sliding mode actions. And both transient and steady performance can be achieved by using the sliding mode and integral actions simultaneously. Then, a sensorless scheme is put forward to by combining the presented observer and the proposed controller. The stability of the observer and controller are verified. Simulation and experiment results validate the proposed approach.

Observer based sliding mode controller for vehicles with roll dynamics

In this work, considering the roll dynamics and actuator dynamics, an observer-based control scheme for a vehicle is proposed. The proposal considers a nonlinear higher order sliding mode observer to estimate unmeasurable lateral velocity, roll angle and roll velocity. Using the observer information, a controller based on block control with sliding mode technique is designed for the reference trajectory tracking of the lateral and yaw velocities of the vehicle. The stability of the complete closed-loop system including zero dynamics is analyzed. The effectiveness of the proposed scheme is demonstrated through CarSim simulations.

Omnidirectional mobile robot robust tracking: Sliding-mode output-based control approaches

This work deals with the robust position tracking control problem for an omnidirectional mobile robot. To this aim, four continuous Sliding-Mode Control strategies are presented. The position and orientation of the platform are assumed to be the only available information about the system. To implement the controllers as output-feedback controllers, a High-Order Sliding-Mode Observer is implemented for each output signal. The proposed robust control strategies are able to deal with some classes of external disturbances. The closed-loop stability of each controller is proved by means of Lyapunov functions and homogeneity concepts. Simulations and experiments validate the applicability of the proposed controllers.

Temperature gradient control of a solid oxide fuel cell stack

For a solid oxide fuel cell, temperature gradient has a great effect on its efficiency and durability. In recent years, several observers are developed to estimate the temperature gradient. However, the temperature gradient control strategies with suitable observers are not seen. Therefore, a compound nonlinear controller based on a high-order sliding mode observer is proposed to control the temperature gradient at desired values to improve the solid oxide fuel cell performance. The high-order sliding mode observer is firstly employed to estimate immeasurable internal temperature. Under the interference of the variations in the initial values of the internal states and measurement noises, the high-order sliding mode observer can estimate the internal temperature distribution with a high precise and a fast convergence. The compound controller which includes a feedback linearization controller and a feedforward controller is then applied to regulate the estimated temperature gradient. During load current changes, the compound controller has the best dynamic performance compared with the feedback linearization controller. However, the observed temperature gradient with the two control strategies can both reach the desired value.

High order sliding mode observer‐based backstepping fault‐tolerant control for induction motor

AbstractThis paper presents a robust fault tolerant control for an induction motor in presence of inter‐turn short‐circuit fault. The control strategy is based on Backstepping approach and high order sliding mode observer. That ensures a high‐performance control and a good dynamic in presence of inter‐turn short‐circuit fault. The stability of the Backstepping control is proved by Lyapunov theory. A high order sliding mode observer is used for rotor flux estimation. The performances of the fault tolerant control scheme will be examined via numerical simulation and validated through hardware implementation using MATLAB/Simulink with dSpace signal card. The analysis' results show the robustness of the proposed method for the tolerance of the inter‐turn short‐circuit fault.

Design of set-point weighting-based dynamic integral sliding mode control with nonlinear full-order state observers for quadcopter UAVs

This research is to develop set-point weighting-based dynamic integral sliding mode control with nonlinear full-order state observers to deal with nonlinear and underactuated coupled systems, and unforeseen circumstances of quadcopter UAVs systems. A comparative assessment through numerical simulations of sliding mode-based nonlinear observer approaches and Kalman filter is presented. These include quasi method, interval type-2 fuzzy logic system, super-twisting algorithm, higher order sliding mode observer, and extended Kalman filter. Chattering, noise rejection, estimation error and time required to track true states are evaluated to demonstrate the performance of each observer. In addition, to assess the proposed controller performance, maximum overshoot, rise time, chattering, and steady-state error are evaluated in relation to the use of each observer.

Design of set-point weighting-based dynamic integral sliding mode control with nonlinear full-order state observers for quadcopter UAVs

This research is to develop set-point weighting-based dynamic integral sliding mode control with nonlinear full-order state observers to deal with nonlinear and underactuated coupled systems, and unforeseen circumstances of quadcopter UAVs systems. A comparative assessment through numerical simulations of sliding mode-based nonlinear observer approaches and Kalman filter is presented. These include quasi method, interval type-2 fuzzy logic system, super-twisting algorithm, higher order sliding mode observer, and extended Kalman filter. Chattering, noise rejection, estimation error and time required to track true states are evaluated to demonstrate the performance of each observer. In addition, to assess the proposed controller performance, maximum overshoot, rise time, chattering, and steady-state error are evaluated in relation to the use of each observer.

Design of Vehicle Running States-Fused Estimation Strategy Using Kalman Filters and Tire Force Compensation Method

Accurate and reliable vehicle state estimation results are very significant to the active safety, energy optimization, and the intelligent control of vehicles. In this paper, to improve the accuracy and adaptability of vehicle running state estimation, the vehicle running states fused estimation strategy is presented for in-wheel motor drive electric vehicle using the Kalman filters and tire force compensation method. The concept of electric drive wheel model (EDWM) is developed and deduced, and then, considering that the EDWM is a nonlinear model with an unknown input, the design concept of high-order sliding mode observer is used to construct the state space equation of longitudinal force. To improve the accuracy and the reliability of vehicle state estimation, an overall estimation strategy with information fusion and tire force compensation is designed, in which a weighted square-root cubature Kalman filter with an adaptive covariance matrix of measurement noise is developed for observer design. Finally, the simulations in CarSim-Simulink co-simulation model and experiments are carried out, and the effectiveness of the designed estimation strategy is validated.

Barrier Lyapunov function-based robust flight control for the ultra-low altitude airdrop under airflow disturbances

This paper investigates the anti-disturbance constrained trajectory flight control for the ultra-low altitude airdrop under airflow disturbances, by innovatively integrating the finite time convergent high-order sliding mode observer and barrier Lyapunov function-based back-stepping technique. The dynamics of transport aircraft during the airdrop are established based on the fixed-wing aircraft's 6 DOF nonlinear model and are transformed into the affine nonlinear form for the convenient control design. These dynamics include the complex influence of the flow disturbances, the ground effect, the consecutive movement and abrupt extraction of the heavy cargo. Then, the flight controller is divided into several cascade subsystems via back-stepping technique. The items reflect the disturbances during the drop in each subsystem, as well as the items which are independent of the predefined virtual control variables, are taken as components of the “lumped disturbances” which are estimated and compensated by the specially designed finite time convergent high order sliding mode observer. On this basis, a barrier Lyapunov function-based back-stepping flight controller is proposed for the robust and safe flight control of the ultra-low altitude airdrop. And the closed-loop stability is discussed via the Lyapunov stability theorem. Simulation comparisons are conducted to verify the robustness and effectiveness of the proposed airdrop flight control method.

Software Sensor for Online Estimation of the VFA’s Concentration in Anaerobic Digestion Processes via a High-Order Sliding Mode Observer

This paper deals with the design of a software sensor based on a high-order sliding mode observer (HOSMO) for online estimation of the concentration of volatile fatty acids (VFA’s) in a class of continuous anaerobic digestion processes (AD). Taking into account the limited availability for online monitoring of AD processes, in this contribution it is assumed that only the methane outflow rate is available for online measurement. Considering a simple two-dimensional AD model, it is shown that the VFA concentration can be detectable from the online measurement of the methane outflow rate. The estimation method is based on a local coordinate transformation that converts the original model into an observable system. In the observable form, a supertwisting algorithm is proposed in order to provide robustness under perturbation and uncertainty conditions. The observer convergence is analyzed by using Lyapunov stability techniques. Numerical simulations illustrate the effectiveness of the proposed estimation sch...

Experimental study of robust output‐based continuous sliding‐modes controllers for Van der Pol oscillator

Robust output tracking control of Van der Pol oscillator is an important practical problem from an application point of view. Output feedback-based robust tracking control strategies are proposed in this work for that purpose. First, a high-order sliding-mode observer is used to estimate the oscillator states from the measurable output and to identify some types of disturbances. Then, five different continuous sliding-modes controllers (Continuous-SMCs) are provided to robustly track a desired time-varying trajectory, exponentially or in a finite time, for the Van der Pol oscillator despite the presence of external disturbances. The closed-loop stability for each Continuous-SMC is given based on input-to-state stability properties. Finally, experimental validations are also provided to show the feasibility of the proposed controllers in real time.

Output-Feedback Adaptive Neural Controller for Uncertain Pure-Feedback Nonlinear Systems Using a High-Order Sliding Mode Observer.

A novel adaptive neural output-feedback controller for SISO nonaffine pure-feedback nonlinear systems is proposed. The majority of the previously described adaptive neural controllers for pure-feedback nonlinear systems were based on the dynamic surface control (DSC) or backstepping schemes. This makes the control law as well as the stability analysis highly lengthy and complicated. Moreover, there has been very limited research till date on the output-feedback neural controller for this class of the systems. The proposed controller evades adopting adaptive backstepping or DSC scheme through reformulating the original system into the Brunovsky form, which considerably simplifies the control law. Combining a high-order sliding mode observer and single radial-basis function network with universal approximation property, it is shown that the controller guarantees closed-loop system stability in the Lyapunov sense.

Lane keeping of autonomous vehicles based on differential steering with adaptive multivariable super-twisting control

Abstract This paper investigates the lane keeping control for four-wheel independently actuated autonomous vehicles. To guarantee the vehicle safety when the active-steering motor entirely fails, the steering manoeuvre is realized by the differential drive assisted steering (DDAS) that is generated by the differential moment between the front wheels. A novel adaptive multivariable super-twisting control strategy is proposed to realize the control objective in finite time, considering the multiple unknown and mismatched disturbances of the steering system with the chattering effect removed. In the sliding surface, a nonlinear function is designed to adaptively change the damping ratio of the closed-loop system so as to improve the transient performance of the lane keeping control in the faulty steering condition. The controller design has avoided the use of the lateral velocity which is usually hard to measure in practice. Instead, the lane keeping errors and their time derivatives are estimated with a high-order sliding mode observer based on a vision system. The finite-time convergence of the closed-loop system is proved by the Lyapunov method. Results of CarSim-Simulink simulations with the proposed control strategy compared with a tradition sliding mode controller based on a high-fidelity and full-car model have verified the effectiveness and robustness of the proposed controller in the lane keeping control via DDAS with the guaranteed high performance.

Observer Design and Unknown Input Reconstruction for a Class of Switched Descriptor Systems

This correspondence paper is concerned with observer design problems for a class of unknown input switched descriptor systems under average dwell time switching signals. The switched descriptor system under consideration is first transformed into a general switched linear system, and then a switched reduced-order observer that can asymptotically estimate the system state without suffering the influence from the unknown inputs is developed. Besides, a high-order sliding mode observer is introduced to obtain the estimations of the output derivatives by using the system measured outputs. On the basis of estimations of the states and output derivatives, an unknown input reconstructing method is provided. Finally, two examples are presented to verify the effectiveness of the proposed approaches.

Approximation-Free Output-Feedback Control of Uncertain Nonlinear Systems Using Higher-Order Sliding Mode Observer

A novel output-feedback controller for uncertain single-input single-output (SISO) nonaffine nonlinear systems is proposed using high-order sliding mode (HOSM) observer, which is a robust exact finite-time convergent differentiator. The proposed controller utilizes (n + 1)th-order HOSM observer to cancel the uncertainty and disturbance where n is the relative degree of the controlled system. As a result, the control law has an extremely simple form of linear in the differentiator states. It is required no separate sliding-mode controller or universal approximators such as neural networks (NNs) or fuzzy logic systems (FLSs) that are adaptively tuned online. The proposed controller guarantees finite time stability of the output tracking error.

Observer Based Fuel Delivery Control for PEM Fuel Cells with a Segmented Anode Model

AbstractIn the anode of proton exchange membrane (PEM) fuel cells, the measurable outlet pressure is usually different with the actually utilized stack pressure. In this paper, the anode of PEM fuel cells is divided into three segments to reduce the modeling error between these two pressures and the impact of the spatial distribution of pressure, electrochemical reaction, and gas permeation. Specifically, we first model the fuel delivery system with anode recirculation and bleeding in a MIMO nonlinear compact form based on the segmented anode model. Then, a Lyapunov‐based full state feedback controller is proposed based on the developed model to guarantee adequate hydrogen supply and maintain the anode hydrogen at a suitable concentration level. Moreover, a high order sliding mode observer is proposed to estimate the unmeasurable pressure and the partial pressure in the fuel delivery system with known disturbance. Furthermore, an output feedback controller based on the proposed observer is developed with guaranteed stability. Simulation results illustrate the effectiveness of the proposed control and the estimation approaches.

Robust Trajectory Tracking for Unmanned Aircraft Systems using a Nonsingular Terminal Modified Super-Twisting Sliding Mode Controller

Precision trajectory tracking problem for Unmanned Aerial Systems (UAS) is addressed in this work. A novel algorithm that combines a Nonsingular Modified Super-Twisting Controller with a High Order Sliding Mode Observer to enable an aerial vehicle tracking a desired trajectory under the assumption that i) its translational velocities are not available and ii) there are unmodeled dynamics and external disturbances. The proposed Sliding Mode Controller is based on a nonlinear sliding mode surface that ensures that the position and velocity tracking errors of all system’s state variables converge to zero in finite time. Moreover, the proposed controller generates a continuous control signal eliminating the chattering phenomenon. Finally, simulation results and an extensive set of experiments are presented in order to illustrate the robustness and effectiveness of the proposed control strategy.

Finite-time and asymptotic left inversion of nonlinear time-delay systems

In this paper we investigate the left invertibility problem for a class of nonlinear time-delay systems. In both cases of time delay systems with and without internal dynamics the invertibility conditions are given. A new approach based on the use of higher order sliding mode observer is developed for finite-time left invertibility and for asymptotic left inversion. Causal and non-causal estimations of the unknown inputs are respectively discussed. The results are illustrated by numerical examples in order to show the efficiency of the method and its limits.