Nonlinear observer-controller design for dynamic positioning of ships

The main focus is nonlinear model-based dynamic positioning (DP) control system design. A nonlinear uniform global exponential stability (UGES) observer produces noise-free estimates of the position, the slowly varying environmental disturbances and the velocity, which are used in a proportional-derivative (PD) + feedforward control law. The stability of this observer-controller system is proved by introducing a specific nonlinear cascaded system. The simulation results have successfully demonstrated the performance of designed DP control system.

Observer-Based Nonlinear Control of A Torque Motor with Perturbation Estimation

This paper presents an observer-based nonlinear control method that was developed and implemented to provide accurate tracking control of a limited angle torque motor following a 50Hz reference waveform. The method is based on a robust nonlinear observer, which is used to estimate system states and perturbations and then employ input-output feedbazk linearization to compensate for the system nonlinearities and uncertainties. The estimation of system states and perturbations allows input-output linearization of the nonlinear system without an accurate mathematical model of nominal plant. The simulation results show that the observer-based nonlinear control method is superior in comparison with the conventional model-based state feedback linearizing controller.

Exponential Nonlinear Observer Based on the Differential State-dependent Riccati Equation

This paper presents a novel nonlinear continuous-time observer based on the differential state-dependent Riccati equation (SDRE) filter with guaranteed exponential stability. Although impressive results have rapidly emerged from the use of SDRE designs for observers and filters, the underlying theory is yet scant and there remain many unanswered questions such as stability and convergence. In this paper, Lyapunov stability analysis is utilized in order to obtain the required conditions for exponential stability of the estimation error dynamics. We prove that under specific conditions, the proposed observer is at least locally exponentially stable. Moreover, a new definition of a detectable state-dependent factorization is introduced, and a close relation between the uniform detectability of the nonlinear system and the boundedness property of the state-dependent differential Riccati equation is established. Furthermore, through a simulation study of a second order nonlinear model, which satisfies the stability conditions, the promising performance of the proposed observer is demonstrated. Finally, in order to examine the effectiveness of the proposed method, it is applied to the highly nonlinear flux and angular velocity estimation problem for induction machines. The simulation results verify how effectively this modification can increase the region of attraction and the observer error decay rate.

Adaptive Fuzzy Sliding Mode Controller with Nonlinear Observer for Redundant Manipulators Handling Varying External Force

An Adaptive Fuzzy Sliding Mode Controller with Nonlinear Observer （AFSMCO） for the redundant robotic manipulator is proposed in this paper. This approach could achieve a precise trajectory tracking for a robot manipulator in the presence of uncertainties and disturbances. Primarily, a suitable observer using the recursive algorithm is presented for an accurate estima- tion of external disturbances caused by the varying external force. Secondly, the adaptive fuzzy logic is designed to approximate the parameters of the sliding mode controller （AFSMC） to avoid chattering in real time. Moreover, it is shown using the Lyapunov theory that the tracking error asymptotically converges to zero. Finally, the effectiveness of the proposed control approach and theoretical discussion are demonstrated by simulation results on a 7-1ink robot and tested on a 7-DOF manipulator platform.

Circle-criterion Based Nonlinear Observer Design for Sensorless Induction Motor Control

This paper deals with the design of a nonlinear observer for sensorless induction motor control. Based upon the circle criterion approach, a nonlinear observer is designed to estimate pertinent but unmeasurable state variables of the considered induction machine for sensorless control purpose. The observer gain matrices are computed as a solution of linear matrix inequalities(LMI) that ensure the stability conditions of the state observer error dynamics in the sense of Lyapunov concepts. Measured and estimated state variables can be exploited to perform a state feedback control of the machine system. The simulation results are presented to illustrate the effectiveness of the proposed approach for nonlinear observer design.

Dynamic Surface Control with Nonlinear Disturbance Observer for Uncertain Flight Dynamic System

A new robust control method of a nonlinear flight dynamic system with aerodynamic coefficients and external disturbance has been proposed.The proposed control system is a combination of the dynamic surface control(DSC)and the nonlinear disturbance observer(NDO).DSC technique provides the ability to overcome the″explosion of complexity″problem in backstepping control.NDO is adopted to observe the uncertainties in nonlinear flight dynamic system.It has been proved that the proposed design method can guarantee uniformly ultimately boundedness of all the signals in the closed-loop system by Lyapunov stability theorem.Finally,simulation results show that the proposed controller provides better performance than the traditional nonlinear controller.

Adaptive current compensation with nonlinear disturbance observer for single-sided linear induction motor considering dynamic eddy-effect

An adaptive current compensation control for a single-sided linear induction motor(SLIM) with nonlinear disturbance observer was developed. First, to maintain t-axis secondary component flux constant with consideration of the specially dynamic eddy-effect(DEE) of the SLIM, a instantaneously tracing compensation of m-axis current component was analyzed. Second,adaptive current compensation based on Taylor-discretization algorithm was proposed. Third, an effective kind of nonlinear disturbance observer(NDOB) was employed to estimate and compensate the undesired load vibrations, then the robustness of the control system could be guaranteed. Experimental verification of the feasibility of the proposed method for an SLIM control system was performed, and it showed that the proposed adaptive compensation scheme with NDOB could significantly promote speed dynamical response and minimize speed ripple under the conditions of external load coupled vibrations and unavoidable feedback control variables measured errors, i.e., current and speed.

Path-Following Control With Obstacle Avoidance of Autonomous Surface Vehicles Subject to Actuator Faults

This paper investigates the path-following control problem with obstacle avoidance of autonomous surface vehicles in the presence of actuator faults,uncertainty and external disturbances.Autonomous surface vehicles inevitably suffer from actuator faults in complex sea environments,which may cause existing obstacle avoidance strategies to fail.To reduce the influence of actuator faults,an improved artificial potential function is constructed by introducing the lower bound of actuator efficiency factors.The nonlinear state observer,which only depends on measurable position information of the autonomous surface vehicle,is used to address uncertainties and external disturbances.By using a backstepping technique and adaptive mechanism,a path-following control strategy with obstacle avoidance and fault tolerance is designed which can ensure that the tracking errors converge to a small neighborhood of zero.Compared with existing results,the proposed control strategy has the capability of obstacle avoidance and fault tolerance simultaneously.Finally,the comparison results through simulations are given to verify the effectiveness of the proposed method.

Optimal State Estimation and Fault Diagnosis for a Class of Nonlinear Systems

This study proposes a scheme for state estimation and,consequently,fault diagnosis in nonlinear systems.Initially,an optimal nonlinear observer is designed for nonlinear systems subject to an actuator or plant fault.By utilizing Lyapunov's direct method,the observer is proved to be optimal with respect to a performance function,including the magnitude of the observer gain and the convergence time.The observer gain is obtained by using approximation of Hamilton-Jacobi-Bellman(HJB)equation.The approximation is determined via an online trained neural network(NN).Next a class of affine nonlinear systems is considered which is subject to unknown disturbances in addition to fault signals.In this case,for each fault the original system is transformed to a new form in which the proposed optimal observer can be applied for state estimation and fault detection and isolation(FDI).Simulation results of a singlelink flexible joint robot(SLFJR)electric drive system show the effectiveness of the proposed methodology.

Enhanced adaptive nonlinear extended state observer for pure feedback systems with matched and mismatched disturbances

In this paper, an enhanced adaptive nonlinear extended state observer (EANESO) for single-input single-output pure feedback systems in the presence of external time-varying disturbances is proposed. In this paper, a nonlinear system with matched and mismatched disturbances is considered. The conventional extended state observer (ESO) can only be applied to systems that are in the form of integral chains. Moreover, this method has limitations in the face of mismatched disturbances. In the presence of time-varying disturbances, the traditional ESOs cannot estimate the disturbances accurately. To overcome this limitation, an EANESO is proposed in this paper. The main idea is to design the nonlinear ESO (NESO) to estimate the states of the system and multiple disturbances simultaneously. The observer gains are considered time-varying and adjusted with adaptation laws to improve the estimation accuracy and overcome the peaking phenomenon. Next, the proposed controller is designed based on output feedback to eliminate the effects of multiple disturbances and stabilize the closed-loop system. Subsequently, the stability analysis of the closed-loop system and convergence of the observer error are discussed. Finally, the proposed method is applied to the inverted pendulum system. The simulated results show good performance of the proposed method as compared with a recently published scheme in the related literature.

Design and Analysis of Fault Diagnosis and Fault-tolerant Control for a Class of MIMO Nonlinear State Systems

This paper presents a fault diagnosis and fault-tolerant control algorithm,which can be used for a class of multi-input multi-output(MIMO)nonlinear state systems.First,a state estimator is proposed,which is able to detect fault occurrence,by using a residual signal.Second,when the state is at an abnormal condition,the fault-tolerant control will be triggered to minimize the impact of the fault occurrence.This fault-tolerant control is designed by using a robust controller(original controller),and an on-line approximator to capture a nonlinear function that indicates the fault occurrence.The detailed analysis is given for the proposed fault accommodation control.

Observation of Two-Photon Absorption and Nonlinear Refraction in AlN

Two-photon absorption （TPA） and nonlinear refraction in AlN single crystals are revealed with the single beam Z-scan technique. A large TPA coefficient of 134-3 cm/CW at 355 nm and third-order nonlinear refractive indices of-1.91±0.38×10-13 cm2/W at 355nm, 1.79±0.36 × 10-13 cm2/W at 532nm and 1.61±0.32 ×10-12 cm2/W at 1064nm are derived. It is inferred that the TPA-generated free carriers are responsible for the large negative nonlinear refractive index at 355 nm, while the oxygen impurity induced bandgap narrowing may account for the large third-order nonlinear refractive indices at 532nm and 1064nm. The large nonlinear optical responses of AIN promise wide applications in the deep ultraviolet nonlinear optical devices.

Distributed Cooperative Anti-Disturbance Control for High-Order MIMO Nonlinear Multi-Agent Systems

To solve the synchronization and tracking problems,a cooperative control scheme is proposed for a class of higher-order multi-input and multi-output(MIMO)nonlinear multi-agent systems(MASs)subjected to uncertainties and external disturbances.First,coupled relationships among Laplace matrix,leader-following adjacency matrix and consensus error are analyzed based on undirected graph.Furthermore,nonlinear disturbance observers(NDOs)are designed to estimate compounded disturbances in MASs,and a distributed cooperative anti-disturbance control protocol is proposed for high-order MIMO nonlinear MASs based on the outputs of NDOs and dynamic surface control approach.Finally,the feasibility and effectiveness of the proposed scheme are proven based on Lyapunov stability theory and simulation experiments.

State Estimation of the Electric Drive Articulated Dump Truck Based on UKF

The requirements of vehicle dynamic stability control are higher than ever as the significant increase of electric drive articulated vehicle speed. According to the construction features of articulated dumping truck and nonlinear characteristics of moving vehicles,nonlinear observer of vehicle status is designed to strength robustness of dynamic control system in this paper. A 4-degree-of-freedom nonlinear dynamic model of articulated electric drive vehicle is built as reference model to estimate the state of the articulated vehicle. And by adopting Unscented Kalman Filter( UKF) algorithm,a series of state parameters such as longitudinal velocities of front and rear frames,yaw rate and side-slip angle are estimated. During the test of 60 t articulated electric drive vehicle,2 inertial navigation modules are installed in the front frame and rear frame respectively and the speed of each electric drive wheel is obtained simultaneously. As the test results suggest,in various working conditions,the algorithm based on UKF is able to accurately estimate the state parameters of articulated vehicle with the estimated error less than 5%. The proposed method is justified to be the theoretical basis and application guidance for articulated vehicle stability control.

Robust Observer-based Control of Nonlinear Multi-omnidirectional Wheeled Robot Systems via High Order Sliding-mode Consensus Protocol

This paper presents a novel observer-based controller for a class of nonlinear multi-agent robot models using the high order sliding mode consensus protocol. In many applications, demand for autonomous vehicles is growing;omnidirectional wheeled robots are suggested to meet this demand. They are flexible, fast, and autonomous, able to find the best direction and can move on an optional path at any time. Multi-agent omnidirectional wheeled robot(MOWR) systems consist of several similar or different robots and there are multiple different interactions between their agents, thus the MOWR systems have complex dynamics. Hence, designing a robust reliable controller for the nonlinear MOWR operations is considered an important obstacles in the science of the control design. A high order sliding mode is selected in this work that is a suitable technique for implementing a robust controller for nonlinear complex dynamics models. Furthermore, the proposed method ensures all signals involved in the multi-agent system(MAS) are uniformly ultimately bounded and the system is robust against the external disturbances and uncertainties. Theoretical analysis of candidate Lyapunov functions has been presented to depict the stability of the overall MAS, the convergence of observer and tracking error to zero, and the reduction of the chattering phenomena. In order to illustrate the promising performance of the methodology, the observer is applied to two nonlinear dynamic omnidirectional wheeled robots. The results display the meritorious performance of the scheme.

Adaptive NN stabilization for stochastic systems with discrete and distributed time-varying delays

A new adaptive neural network（NN） output-feedback stabilization controller is investigated for a class of uncertain stochastic nonlinear strict-feedback systems with discrete and distributed time-varying delays and unknown nonlinear functions in both drift and diffusion terms.First,an extensional stability notion and the related criterion are introduced.Then,a nonlinear observer to estimate the unmeasurable states is designed,and a systematic backstepping procedure to design an adaptive NN output-feedback controller is proposed such that the closed-loop system is stable in probability.The effectiveness of the proposed control scheme is demonstrated via a numerical example.

Constant-gain nonlinear adaptive observers revisited: an application to chemostat systems

This study deals with constant-gain adaptive observers for nonlinear systems,for which relatively few solutions are available for some particular cases.We introduce an asymptotic observer of constant gain for nonlinear systems that have linear input.This allows the observer design to be formulated within the linear matrix inequality paradigm provided that a strictly positive real condition bet ween the inpu t disturbance and the output is fulfilled.The proposed observer is t hen applied to a large class of nonlinear chemos tat dynamical systems that are widely used in the fermentation process,cell cultures,medicine,etc.In fact,under standard practical assumptions,the necessary change of the chemos tat state coordinates exis ts,allowing use of the const ant-gain observer.Finally,the developed theory is illustrated by estimating pollutant concentration in a Spirulina maxima wastewater treatment facility.

METHOD TO ELIMINATE THE INFLUENCE OF SERVO－MOTOR FRICTION TORQUEON ULTRA－LOW SPEED PERFORMANCE OFELEC

A nonlinear observer of friction torque is formulated for valve controlled servomotor system. The effect of the observer is studied with simulating method and its applied condition is analyzed. When the above observer is not suitable foe use, a simple PID controlling method with variable parameters is presented. The method has been proved to be effective by the experimental results.

Roll-pitch-yaw autopilot design for nonlinear time-varying missile using partial state observer based global fast terminal sliding mode control

The acceleration autopilot design for skid-to-turn （STT） missile faces a great challenge owing to coupling effect among planes, variation of missile velocity and its parameters, inexistence of a complete state vector, and nonlinear aerodynamics. Moreover, the autopilot should be designed for the entire flight envelope where fast variations exist. In this paper, a design of integrated roll-pitch-yaw autopilot based on global fast terminal sliding mode control （GFTSMC） with a partial state nonlinear observer （PSNLO） for STT nonlinear time-varying missile model, is employed to address these issues. GFTSMC with a novel sliding surface is proposed to nullify the integral error and the singularity problem without application of the sign function. The proposed autopilot consisting of two-loop structure, controls STT maneuver and stabilizes the rolling with a PSNLO in order to estimate the immeasurable states as an output while its inputs are missile measurable states and control signals. The missile model considers the velocity variation, gravity effect and parameters＇ variation. Furthermore, the environmental conditions＇ dynamics are mod- eled. PSNLO stability and the closed loop system stability are studied. Finally, numerical simulation is established to evaluate the proposed autopilot performance and to compare it with existing approaches in the literature.

Fault diagnosis of an intelligent hydraulic pump based on a nonlinear unknown input observer

Hydraulic piston pumps are commonly used in aircraft. In order to improve the viability of aircraft and energy efficiency, intelligent variable pressure pump systems have been used in aircraft hydraulic systems more and more widely. Efficient fault diagnosis plays an important role in improving the reliability and performance of hydraulic systems. In this paper, a fault diagnosis method of an intelligent hydraulic pump system（IHPS） based on a nonlinear unknown input observer（NUIO） is proposed. Different from factors of a full-order Luenberger-type unknown input observer, nonlinear factors of the IHPS are considered in the NUIO. Firstly, a new type of intelligent pump is presented, the mathematical model of which is established to describe the IHPS. Taking into account the real-time requirements of the IHPS and the special structure of the pump, the mechanism of the intelligent pump and failure modes are analyzed and two typical failure modes are obtained. Furthermore, a NUIO of the IHPS is performed based on the output pressure and swashplate angle signals. With the residual error signals produced by the NUIO, online intelligent pump failure occurring in real-time can be detected. Lastly, through analysis and simulation, it is confirmed that this diagnostic method could accurately diagnose and isolate those typical failure modes of the nonlinear IHPS. The method proposed in this paper is of great significance in improving the reliability of the IHPS.