Stabilization of Controlled Current Induction Motor Drive Systems via New Nonlinear State Observer

A nonlinear state observer can be used as a resolver-to-digital converter (RDC); however, when the speed is not constant, its performance deteriorates. In this paper, a composite state observer is presented. The estimation speed from the nonlinear state observer is compensated by the estimation speed from the arctangent method in the feed-forward form. Compared with the arctangent method, this method has a strong ability to suppress random disturbances. Compared with an RDC based on a nonlinear state observer, the accuracy of the angle and speed is improved as the appearance of phase delay is weakened. Experiments demonstrate the effectiveness of the observers.

On Stabilization of Classes of Nonlinear Systems with State Observers

Safe cooperative path following with relative-angle-based collision avoidance for multiple underactuated autonomous surface vehicles

In this article we compare the performance of four nonlinear state observers for a combustion engine test bench simulator including combustion oscillations, noisy measurements and disturbed inputs. These observers are the high-gain observer (HGO), the sliding-mode observer (SMO), the nonlinear extended state observer (NESO) and the extended Kalman Filter (EKF). The different observers are compared in open-loop in terms of the mean quadratic estimation error, computing time and convergence rate. A first important result obtained is that the NESO performance is good, although it does not need to know the engine friction model. Then the best of these is compared in closed-loop with a partial Luenberger observer which requires the knowledge of the model of the combustion oscillations. It turns out that we can achieve similar tracking results without the knowledge of the combustion oscillations model.

Dynamic observers are commonly used in feedback loops to estimate the system’s states from available control inputs and measured outputs. The presence of measurement noise degrades the performance of the observer and consequently degrades the performance of the controlled system. This paper presents a novel nonlinear higher-order extended state observer (NHOESO) for efficient state and disturbance estimation in presence of measurement noise for nonlinear single-input–single-output systems. The proposed nonlinear function allows a fast reconstruction of the system’s states and is robust against uncertainties and measurement noise. An analytical parameterization technique is proposed to parameterize the coefficients of the proposed nonlinear higher-order extended state observer in the case of measurement noise in the output signal. Several scenarios are simulated to demonstrate the effectiveness of the proposed observer.

In this work, an adaptive neural network (NN) optimized output-feedback control problem is studied for a class of stochastic nonlinear systems with unknown nonlinear dynamics, input saturation, and state constraints. A nonlinear state observer is designed to estimate the unmeasured states, and the NNs are used to approximate the unknown nonlinear functions. Under the framework of the backstepping technique, the virtual and actual optimal controllers are developed by employing the actor-critic architecture. Meanwhile, the tan-type Barrier optimal performance index functions are developed to prevent the nonlinear systems from the state constraints, and all the states are confined within the preselected compact sets all the time. It is worth mentioning that the proposed optimized control is clearly simple since the reinforcement learning (RL) algorithm is derived based on the negative gradient of a simple positive function. Furthermore, the proposed optimal control strategy ensures that all the signals in the closed-loop system are bounded. Finally, a practical simulation example is carried out to further illustrate the effectiveness of the proposed optimal control method.

The state of charge (SOC) estimation of lithium‐ion batteries is complex due to the various nonlinear uncertainties present in the battery. However, in this paper, a new nonlinear state observer (NSO) is proposed to be designed for the estimation of accurate and robust SOC. This proposed observer is suitable for both continuous and discrete‐time nonlinear systems. To design the nonlinear observer, two‐RC equivalent circuit model state equations are simulated for the dynamic behavior of the lithium‐ion battery. The seventh‐order polynomial fitting approach is assumed for the nonlinear relationship between open‐circuit voltage (OCV) and SOC, and the exponential fitting method is used to estimate the battery's offline parameters. Lyapunov's stability criterion achieves the stability and convergence capability of the proposed method. An urban dynamometer driving schedule (UDDS) cycle was adopted to estimate the performance of the proposed observer by comparing it with the well‐established methods like unscented Kalman filter (UKF) and sliding mode observer (SMO) algorithms, and it was found that the proposed observer achieved better performance like accurate SOC, high convergence capability, and less SOC error.

Adaptive neural control for mobile manipulator systems based on adaptive state observer

The problem of actuator fault estimation for a kind of nonlinear discrete time varying (NDTV) systems is investigated. Norm bounded disturbance is considered and the nonlinear function is assumed to fulfill a Lipschitzlike condition. Fault estimation is accomplished by a novel nonlinear state observer and a dynamic post filter. First, the nonlinear state observer is designed with the help of the small gain theorem and the H∞ filtering approach. Then for the error dynamic of the observer, the dynamic post filter is constructed to estimate the fault. In this scheme, no approximation of the nonlinear function is taken, and the problem of infeasibility resulting from multiple synthesis conditions is considerably improved. Simulation studies are carried out with a nonlinear unmanned aerial vehicle (UAV) model. The turbulent condition is considered and the feed back control loop is employed. Simulation results show that the proposed method can accomplish the estimation work, while the residual evaluation based approach fails to detect the fault.

Attitude control for quadrotors subjected to wind disturbances via active disturbance rejection control and integral sliding mode control

Considering the market‐oriented multi‐area power system with wind power integration, a fully distributed control scheme is proposed, and investigating the consensus problem of event‐triggered control in nonlinear multi‐area power systems (MPSs) is the main focus of the research. First of all, a nonlinear state observer is introduced to estimate the states of each area in the system based on the measured values of the systems actual output. Meanwhile, aiming at the consensus and stability issues of multi‐node systems, an innovative adaptive consensus protocol for multi‐node network communication based on a nonlinear observer is proposed. Then, in order to further reduce the burden on the MPSs network and mitigate denial of service attacks in the communication network, a novel dynamic event‐triggered mechanism is proposed. Secondly, the gain matrices of the observer and controller are obtained by solving linear matrix inequalities, thereby ensuring the consensus of MPS. Lastly, a typical five‐region LFC system is presented, and the superiority and effectiveness of the proposed control method are verified through simulation experiments.

Direct field-oriented technique for high-performance control of induction motors requires the use of rotor flux magnitude and angular position. Whenever direct measure of the rotor flux is not available an observer must be included in the control loop to reconstruct the flux using available measurements, like rotor speed and stator currents and voltages. In this paper the use of a nonlinear closed-loop observer in a standard field-oriented controller is investigated As opposed to simplified linear methods, the nonlinear observer fully takes into account for the nonlinear dynamics of the induction motor, providing good performances in the whole range of machine operations. In our implementation the observer provides, as a by-product, also the estimate of the mechanical load. >

Disturbance attenuation of nonlinear control systems using an observer-based fuzzy feedback linearization control

This paper is dedicated to the robust nonlinear control of friction-induced vibrations (FIV), more particularly those generated according to the mode-coupling mechanism. A nonlinear scheme which consists of a sliding-mode controller implemented by using a high-gain state observer is proposed. The main objective is to suppress or mitigate the generated vibrations by taking into account of the nonlinearities and uncertainties inherent to friction systems. Hence, this study proposes the analysis of the closed-loop performances of the high-gain observer-based sliding-mode controller when used for the active control of vibrations issued from the mode-coupling mechanism. Based on numerical simulations, the proposed controller has shown suitable performances distinguished from an effective suppress of the generated vibrations. Otherwise, it is shown that the gain of the used nonlinear state observer must be tuned in order to ensure a suitable compromise between the robustness level of the performances with respect to parameter uncertainty and the robustness level with respect to the measurement noise.

Power-level control is a crucial technique for the safe, stable and efficient operation of modular high temperature gas-cooled nuclear reactors (MHTGRs), which have strong inherent safety features and high outlet temperatures. The current power-level controllers of the MHTGRs need measurements of both the nuclear power and the helium temperature, which cannot provide satisfactory control performance and can even induce large oscillations when the neutron sensors are in error. In order to improve the fault tolerance of the control system, it is important to develop a power-level control strategy that only requires the helium temperature. The basis for developing this kind of control law is to give a state-observer of the MHTGR a relationship that only needs the measurement of helium temperature. With this in mind, a novel nonlinear state observer which only needs the measurement of helium temperature is proposed. This observer is globally convergent if there is no disturbance, and has the L2 disturbance attenuation performance if the disturbance is nonzero. The separation principle of this observer is also proven, which denotes that this observer can recover the performance of both globally asymptotic stabilizers and L2 disturbance attenuators. Then, a new dynamic output feedback power-level control strategy is established, which is composed of this observer and the well-built static state-feedback power-level control based upon iterative dissipation assignment (IDA-PLC). Finally, numerical simulation results show the high performance and feasibility of this newly-built dynamic output feedback power-level controller.