Full-order Observer Research Articles

Adaptive PLL-Based Sensorless Control for Improved Dynamics of High-Speed PMSM

This article presents an adaptive quadrature phase-locked loop (AQPLL) for improving the dynamic performance of sensorless high-speed permanent magnet synchronous motors (PMSMs). A conventional quadrature phase-locked loop (QPLL) operating with a fixed bandwidth tends to have a tradeoff between antidisturbance performance and phase delay. The AQPLL can start to operate with a low bandwidth, while the bandwidth is adapted during motor acceleration in real time. Thus, the position estimation error is quickly minimized, leading to correctly decoupled rotor currents and higher available torque. Key parameters of the adaptation mechanism are examined. Sensorless field-oriented control (FOC) with a full-order observer and an AQPLL has been implemented on a field-programmable gate array and verified using a 100 kr/min PMSM. When motor dynamics is unknown or the QPLL cannot be tuned properly, the AQPLL can auto-tune the bandwidth, facilitating up to 25% faster acceleration from 5 to 100 kr/min. The steady-state position estimation error is less than 3 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${}^{\circ }$</tex-math></inline-formula> at 100 kr/min. Experimental results confirm the effectiveness of the method for achieving a high-performance sensorless FOC of high-speed PMSMs. Furthermore, the AQPLL algorithm has the potential to replace the ordinary QPLL, helping to avoid time-consuming online phase-locked loop tuning in standard drives. This article is accompanied by a MATLAB script demonstrating proposed AQPLL fundamentals.

Design of Full-Order State Observer for Two-Mass Joint Servo System Based on the Fixed Gain Filter

This article mainly designs a novel full-order state observer for the two-mass elastic servo system. In order to observe all the states of the two-mass system without the aid of any additional sensors, the model of the observer is constructed that includes two relative parts. Based on the theory of steady-state Kalman filter (KF), the fixed gain filter (FGF) scheme is studied. To overcome the heavy computational processing burden from the KF, the mechanism of the only one adjustable parameter is studied for the FGF-based observer. The adjustable parameter can be further refined by stability analysis and control characteristics within a small range, and the exact value can be calculated according to the desired observation performance, by compromising both the noise sensitivity and tracking capability. The proposed full-order observer method is experimentally verified in a two-mass system to provide easy parameter tuning, decreased computational complexity, and flexible observation performance in all cases.

A parametric design method of observer‐based state feedback controller for quasi‐linear systems

This paper designs an observer-based feedback controller for quasi-linear systems when the entire state vector is unavailable for measurement. First, based on the solution of a type of generalised Sylvester equations, general complete parameterisation of the full-order observer is proposed. Second, the traditional separation principle is applied to the quasi-linear systems. In other words, the design of a state feedback and the design of a state observer can be carried out independently. Further, general complete parameterisation of the state feedback controller is also established. Finally, numerical examples and simulations are adopted to verify the effectiveness of the proposed method.

Reduced-order intermediate variable observer based fault estimation and fault-tolerant control for fuzzy stochastic systems with exogenous disturbance

This paper studies fault estimation and fault-tolerant control problems for fuzzy systems with exogenous disturbance and stochastic noise. The fuzzy reduced-order intermediate variable observers and the disturbance observers are proposed to reconstruct the sensor fault, the actuator fault and the disturbance. According to the estimated results, the observer based fault-tolerant controllers are devised. Compared with the full-order observer design method, the designed reduced-order observers are with lower dimensions and less cost. Different from the classic intermediate observer, the feedback term of the output estimation error is introduced into our observers, which increases the design freedom. And the obtained linear matrix inequality conditions can ensure that the whole closed-loop systems are mean-square exponentially stable. Finally, two examples are offered to verify the feasibility of the proposed method.

Speed Sensorless Model Predictive Torque Control of Induction Motors Using a Modified Adaptive Full-Order Observer

In this article, a new design of the state observer is proposed to reduce the unstable low-speed region of the adaptive full-order observer (AFO) based speed sensorless speed control of induction motors (IM). The proposed state observer is designed in z-domain rather than in s-domain following the pole-placement approach. The convergence rate of the proposed observer can be made faster than that of the IM poles without extra oscillation effects and the unstable low-speed region of AFO can be reduced to the zero-synchronous-frequency (ZSF) line. Also, a modified adaptation law of the AFO is derived to estimate the rotor speed. Based on the modified AFO, a continuous control set model predictive control (CCS-MPC) is designed for the inner-loop torque control. The cost function of the CCS-MPC is made of the predicted tracking errors on the state and control input. Finally, the dual-loop speed sensorless speed control using the modified AFO and CCS-MPC is presented in simulations and experiments.

Optimal design of full order state observer for active surge control in centrifugal compressors using genetic algorithm

This paper presents the design of a genetic algorithm (GA) based full order state observer for a compressor system. The observer measures the compressor system parameters and computes the difference between the measured output and the setpoint, which is used as feedback to the active surge controller. The proposed control structure with a GA tuned compressor characteristic is required to minimize system oscillations and energy losses induced by the piston actuation gas recycling technique. The design method for GA based full order observer begins with a state observer modelling, observer error estimation based on the magnitude of fluid friction and mechanical effects on measured parameters. The aim of the controller is to regulate the compressor driver speed such that the measured output achieves its required set point. In order to achieve a maximum compressor operating capacity, the compressor characteristics were optimized using GA, where the mass flow was maximized to improve the compressor efficiency. Simulations were carried out, and results showed the viability of GA based full order state observer compared with the piston actuation recycle method to control active surge in centrifugal compressor systems

Generalized Full Order Observer Subject to Incremental Quadratic Constraint (IQC) for a Class of Fractional Order Chaotic Systems

In this paper, we used Lyapunov theory and Linear Matrix Inequalities (LMI) to design a generalized observer by adding more complexity in the output of the dynamic systems. Our designed observer is based on the optimization problem, minimizing error between trajectories of master and slave systems subject to the incremental quadratic constraint. Moreover, an algorithm is given in our paper used to demonstrate a method for obtaining desired observer and gain matrixes, whereas these gain matrixes are obtained with the aid of LMI and incremental multiplier matrix (IMM). Finally, discussion of two examples are an integral part of our study for the explanation of achieved analytical results using MATLAB and SCILAB.

A Generalized Minimum Variance Controller Based on a Modified Full-Order Observer Equivalent to Polynomial Approach

A Generalized Minimum Variance Controller Based on a Modified Full-Order Observer Equivalent to Polynomial Approach

Sliding Model-Based Predictive Torque Control of Induction Motor for Electric Vehicle

This article presents a sliding model-based predictive torque control (S-PTC) of an induction motor for the electric vehicle application. In this work, a battery-operated bidirectional converter fed induction machine-driven power train system is considered. In the conventional predictive torque control (C-PTC), only the machine model is used for the prediction of stator flux, current, and electromagnetic torque. Unlike the C-PTC, the presented control scheme offers a nonlinear switching feedback term in the prediction equation to overcome the model uncertainties, disturbances, and variation in motor parameters. The gains of the feedback terms are selected based on the Lyapunov stability criterion. Adaptive full order observer is used for the estimation of speed and rotor flux. This method is implemented and the speed response and torque ripple of the motor are analyzed for various operating modes of the vehicle. The robustness of the control is verified for variation in motor parameters and a comparison is shown to justify the achievement of objectives through S-PTC than with C-PTC. The control algorithm for the developed system is verified experimentally through the laboratory prototype.

New Identification Approach and Methods for Plasma Equilibrium Reconstruction in D-Shaped Tokamaks

The paper deals with the identification of plasma equilibrium reconstruction in D-shaped tokamaks on the base of plasma external magnetic measurements. The methods of such identification are directed to increase their speed of response when plasma discharges are relatively short, like in the spherical Globus-M2 tokamak (Ioffe Inst., St. Petersburg, Russia). The new approach is first to apply to the plasma discharges data the off-line equilibrium reconstruction algorithm based on the Picard iterations, and obtain the gaps between the plasma boundary and the first wall, and the second is to apply new identification methods to the gap values, producing plasma shape models operating in real time. The inputs for on-line robust identification algorithms are the measurements of magnetic fluxes on magnetic loops, plasma current, and currents in the poloidal field coils measured by the Rogowski loops. The novel on-line high-performance identification algorithms are designed on the base of (i) full-order observer synthesized by linear matrix inequality (LMI) methodology, (ii) static matrix obtained by the least square technique, and (iii) deep neural network. The robust observer is constructed on the base of the LPV plant models which have the novelty that the state vector contains the gaps which are estimated by the observer, using input and output signals. The results of the simulation of the identification systems on the base of experimental data of the Globus-M2 tokamak are presented.

On the use of parallel full-order state observers for damage detection in mechanical systems

On the use of parallel full-order state observers for damage detection in mechanical systems

Adaptive output feedback control for a class of switched stochastic nonlinear time-delay systems

This article investigates the adaptive output feedback control problem for a class of switched stochastic nonlinear time-delay systems with the triangular structure. To conquer the effects of unknown homogeneous growth rate and time-varying delays, two dynamic gains and a Lyapunov–Krasovskii (L–K) functional are introduced. Finally, a new homogeneous output feedback controller is designed by using a full-order observer. On the basis of the celebrated nonnegative semimartingale convergence theorem, it is proved that all signals of the closed-loop system are bounded almost surely (a.s.). Two examples are presented to verify the effectiveness of the presented strategy.

Integrated design of fault-tolerant control for flight control systems using observer and fuzzy logic

PurposeFault detection, isolation and reconfiguration of the flight control system is an important problem to obtain healthy flight. This paper aims to propose an integrated approach for aircraft fault-tolerant control.Design/methodology/approachThe integrated structure includes a Kalman filter to obtain without noise, a full order observer for sensor fault detection, a GOS (generalized observer scheme) for sensor fault isolation and a fuzzy controller to reconfigure of the healthy sensor. This combination is simulated using the state space model of a lateral flight control system in case of disturbance and under sensor fault scenario.FindingsUsing a dedicated observer scheme, the detection and time of sensor fault are correct, but the sensor fault isolation is evaluated incorrectly while the faulty sensor is isolated correctly using GOS. The simulation results show that the suggested approach works affectively for sensor faults with disturbance.Originality/valueThis paper proposes an integrated approach for aircraft fault-tolerant control. Under this framework, three units are designed, one is Kalman filter for filtering and the other is GOS for sensor fault isolation and another is fuzzy logic for reconfiguration. An integrated approach is sensitive to faults that have disturbances. The simulation results show the proposed integrated approach can be used for any linear system.

Adaptive output feedback control for a class of uncertain stochastic nonlinear systems

This article concentrates on the output feedback controller design for a class of stochastic nonlinear systems with unknown homogeneous growth rates. First, a full-order observer is proposed coupling with a dynamic gain so as to obtain system state estimates. Then, an adaptive output feedback controller is put forward by the homogeneity theory and adding a power integrator technique. Combined with the stochastic Barbalat’s lemma, the signals of the closed-loop system are demonstrated to be bounded and all the system states are proved to converge to the origin in probability. Besides, the results are also expanded to the controller design of upper-triangular stochastic nonlinear system. Two simulation results indicate usefulness of the designed control algorithm.

Actuator Fault Diagnosis for Discrete-Time Systems via Augmenting State Approach

For the problem of the actuator fault diagnosis in the control systems, this paper presents a novel method by using an interval estimation approach to detect the faults and reconstruct them. In order to make estimations of the unavoidable measurement noise, a descriptor system form is built. Firstly, a full-order interval observer is developed to detect actuator faults for its sensitiveness to them. Then, a reduced-order one, which is robust to actuator faults, is presented. This method does not need the boundary information of faults; thus, the design condition is more relaxed. In order to make the interval observer stable and cooperative, linear matrix inequalities and a time-varying transformation are employed to ensure the error system matrix to be Schur and nonnegative. Based on the interval estimation results of the aforementioned method, an interval reconstruction method of actuator faults is proposed. Finally, results of the two simulation examples verify the proposed methods are effective and accurate.

Adaptive tracking control of uncertain large-scale nonlinear time-delay systems with input saturation

This paper investigates the adaptive tracking control problem of uncertain large-scale nonlinear time-delay systems with input saturation. Unknown constants and continuous functions with respect to output or delayed output are allowed in the nonlinear interconnected functions. The dynamic gain control technique is used to study the tracking control problem of considered system, which simplifies design process and form of controller. By introducing a full-order state observer and three dynamic equations, output feedback tracking control scheme is constructed to ensure that all signals of the closed-loop system are globally uniformly ultimately bounded (GUUB). In addition, the tracking error can converge to a small neighbourhood around the origin by selecting appropriate parameters. Finally, a practical example is presented to illustrate the feasibility of the proposed control scheme.

Sensor-less Speed and Flux Control of Dual Stator Winding Induction Motors Based on Super Twisting Sliding Mode Control

This paper proposes a direct speed and flux control system for Dual Stator Winding Induction Machines (DSWIMs) based on Super Twisting Sliding Mode Control (STSMC). The proposed nonlinear controller which has finite time convergence of error to zero, is designed such that the Lyapunov stability condition is satisfied. Furthermore, a novel torque-sharing algorithm is introduced for DSWIMs. This algorithm enables them to operate in a wide speed region, including zero speed, such that the required electromagnetic torque is supplied by two winding sets based on their power ratings. In addition, a Sliding Mode Control (SMC) based full order observer is proposed for DSWIMs. This observer, which is able to estimate the winding fluxes, flux angles and rotor speed with high-accuracy, guarantees the optimal flux condition. The functionality of the proposed sensor-less DSWIM drive scheme is evaluated through some experimental tests performed on a 3.3 kW DSP-based DSWIM drive system. The experimental results confirm the effectiveness of the proposed control method, torque sharing algorithm and the full order observer in various speed regions.

Fault-Tolerant Tracking Control of Discrete-Time T-S Fuzzy Systems With Input Constraint

Active fault-tolerant control strategy aimed at tracking is studied for a class of discrete-time Takagi-Sugeno (T-S) fuzzy systems in the presence of input constraint and additive fault. In the fault-free case, the state space of the system is partitioned based on the presence or absence of inputs. Using the parallel distributed compensation technique, input-to-state stability is proved for the error dynamics. For input constraint satisfaction, a model predictive control based reference-management unit is proposed in the form of an online optimization module that solves a quadratic programming problem. In the faulty case, the fault-free system is used as a reference model that satisfies the input constraint. Then, the concept of virtual actuator is used to make the behavior of the faulty system similar to the behavior of the fault-free system by controlling the performance degradation. In this article, a full-order observer can be used for fault estimation. In order to keep the control input of the faulty system within the admissible range defined for the fault-free system, a constraint-change scenario is considered. After detecting the fault, the constraint on the input of the fault-free system is changed in a way to keep the control input of the faulty system in the specified range. All design criteria are formulated as a linear matrix inequality problem. In order to evaluate the proposed control approach, simulations are performed on two systems: a 3-DoF helicopter and a 2-D overhead crane.

Passive-based adaptive control with the full-order observer for induction motor without speed sensor

The conventional linear control methods are difficult to meet the control requirements of high-performance speed regulation of asynchronous motor due to the nonlinear and multi-variable problems of induction motor. A passive-based control method of induction motor with the full-order state observer is proposed with the Euler–Lagrange equation of motion of the induction motor. Based on the relationship between passivity and stability of induction motor, the state feedback is used for torque and speed tracking. The full-order state observer is adopted with rotor current and rotor flux as state variables, and the adaptive speed controller is designed to realize the passive-based control. The experimental results show that the errors between the estimated value based on the proposed full-order observer and the actual value of rotor current, speed and flux are small; the speed with the proposed adaptive control can reach the expected value quickly. The proposed control method can effectively meet the high-performance requirements of induction motor.

Adaptive Full-Order Displacement Observer for Sensorless Resonant Frequency Tracking Control of Linear Oscillatory Machines

Linear oscillatory machines are becoming more widely used in refrigeration compressors due to advantages of compact volume, little maintenance, and so on. In order to further increase the efficiency and reduce the cost of the whole system, both resonant frequency tracking control and sensorless control strategies should be implemented simultaneously. In this article, an adaptive full-order observer with simple structure and less computation is proposed, which can not only provide accurate displacement estimation signals for the system piston stroke control, but also achieve resonant frequency tracking control through the estimation of machine parameters. The system stability analysis proves the quick convergence of the proposed observer, and comprehensive simulation and experimental results demonstrate the effectiveness of the proposed algorithm.