Inverse System Method Research Articles

Adaptive Finite-Time Backstepping Integral Sliding Mode Control of Three-Degree-of-Freedom Stabilized System for Ship Propulsion-Assisted Sail Based on the Inverse System Method

The three-degree-of-freedom (3-DOF) stabilized control system for ship propulsion-assisted sails is used to control the 3-DOF motion of sails to obtain offshore wind energy. The attitude of the sail is adjusted to ensure optimal thrust along the target course. An adaptive finite-time backstepping integral sliding mode control based on the inverse system method (ABISMC-ISM) is presented for attitude tracking of the sail. Considering the nonlinear dynamics and strong coupling of the system, a decoupling strategy is established using the inverse system method (ISM). Constructing inverse dynamics to eliminate internal coupling, the system is transformed into independent pseudolinear subsystems. For the decoupled open-loop subsystems, an adaptive finite-time backstepping integral sliding mode control is designed to achieve closed-loop control. A backstepping-based integral sliding surface is proposed to eliminate the phase-reaching stage of the sliding surface. Considering the unmodelled dynamics and external disturbances, an adaptive extreme learning machine (AELM) was designed to estimate the disturbances. Furthermore, a sliding mode reaching law based on finite-time theory was employed to ensure that the system returns to the sliding surface in a finite time under chattering conditions. Experiments on a principle prototype demonstrate the effectiveness and energy-saving performance of the proposed method.

Research on wind turbine variable pitch control based on wind speed estimation

With the continuous promotion of the “double carbon” strategy, the capacity of wind turbines is increasing, and the dimensions of key parts such as the diameter of the wind turbine wheel, the height of the tower, and the radius of the tower tube are also increasing. Large wind turbines have a large inertia, so the execution time of the pitch actuator and the response time of the pitch action are usually longer, which leads to large fluctuations in the output power of the wind turbine when the wind speed changes rapidly under the working conditions above the rated wind speed and leads to complex loading problems. Therefore, in this paper, the design of pitch control is carried out by estimating the effective wind speed at the wind turbine surface and using the inverse system method to transform the nonlinear wind turbine system into a linear decoupled form. This method improves the pitch response speed, reduces the output power fluctuation, and better suppresses the load of the turbine to ensure the safe and stable operation of the turbine

Design of an Improved Active Disturbance Rejection Control Method for a Direct-Drive Gearshift System Equipped with Electromagnetic Linear Actuators in a Motor-Transmission Coupled Drive System

In this study, a type of direct-drive gearshift system integrated into a motor-transmission coupled drive system is introduced. It used two electromagnetic linear actuators (ELAs) to perform gearshift events. The adoption of ELAs simplifies the architecture of the gearshift system and has the potential to further optimize gearshift performance. However, a number of nonlinearities in the gearshift system should be investigated in order to enhance the performance of the direct-drive gearshift system. An active disturbance rejection control (ADRC) method was selected as the principal shifting control method due to the simple methodology and strong reliability. The nonlinear characteristics of the electromagnetic force produced by the ELA were subsequently reduced using the inverse system method (ISM) technique. The ADRC approach also incorporated an acceleration feedforward module to enhance the precision of displacement control. The extended state observer (ESO) module used a nonlinear function in place of the original function to improve the ability to reject disturbances. Comparative simulations and experiments were carried out between the ADRC method and improved ADRC (IADRC) method. The outcomes demonstrate the effectiveness of the designed control method. The shift force fluctuates less, and the shift jerk decreases noticeably during the synchronization procedure. In conclusion, combined with the optimized IADRC method, the direct-drive gearshift system equipped with ELAs shows remarkable gearshift performance, and it has the potential to be widely used in motor−transmission coupled drive systems for EVs.

6-Dimensional Virtual Human-Machine Interaction Force Estimation Algorithm in Astronaut Virtual Training

It is necessary to conduct virtual training for astronauts on the ground to improve the efficiency and safety of astronauts carrying objects in space. Cooperation between the two astronauts is required when handling massive objects. During this process, it is necessary to obtain the operating force of each astronaut. The research purpose of this paper was to propose an algorithm to map the astronaut’s operation on the VR handle to the human–machine interaction force without the robot’s participation, thereby saving costs. In this paper, a virtual robot simulation model is established, while the controller is designed based on the inverse system method. The virtual human–machine interaction force was obtained based on the inverse dynamics method. The influence of different parameters on the final position of the virtual object was analyzed. The physical engine was integrated into the virtual force sensor to ensure that the human–machine interaction forces of multiple astronauts can be coupled. The results showed that the virtual human–machine interaction force is similar to the real one and has a low output noise (approximately 5.5 N). This force can be applied to astronaut collaborative virtual training.

Multi-shaker shock response spectra replication control

Shock vibration environments frequently occur and threaten the reliability of products in aerospace engineering. This work deals with the shock response spectra replication control method for multi-shaker vibration test systems. Two synthetic methods for reconstitution of shock response signals with specified shock response spectra are presented. One is the random delay superposition method and the other is the filtering superposition method. The former utilizes a random time delay vector satisfying a normal distribution to simulate a shock response signal with symmetrical attenuated oscillation features while the latter is employed when the measured shock records are available. A time-domain inverse system method is formulated to obtain the multi-input drive signals based on a finite-difference equation. The multi-input multi-output frequency response functions are estimated first and then used to construct the inverse system. The multi-output shock response spectra are calculated by response signals from control sensors. A closed-loop iteration control procedure is provided to correct the drive signals according to the deviations between the responses and corresponding reference values. A numerical simulation and a triaxial vibration test are carried out and the results show the feasibility and effectiveness of the proposed methods.

Support Vector Regression Inverse System Control for Small Wind Turbine MPPT with Parameters’ Robustness Improvement

With the increasing penetration of the permanent-magnet direct-drive wind power system, the maximum wind-energy capture and the generation speed control are more and more important. In the literature, the dynamic performance of the generator speed is well documented by the inverse system method. However, conventional inverse system methods have parameter dependency that is not sufficient to meet the dynamic requirements for permanent magnet synchronous generator (PMSG) speed tracking. Therefore, this paper introduces a support vector regression machine (SVR) method, especially for the inverse system model, which could solve the inaccurate parameters problems. As the SVR has the nonlinear approximation ability to identify and adjust the parameters online, thus, the system robustness could be improved. Finally, the dynamic performance of generator speed is evaluated by using the SVR method. Proposed theoretical developments are verified by the Simulink Test and experimental test.

Enhanced wind turbine maximum wind-energy capture based on the inverse-system method

Wind-Energy systems based on permanent magnet synchronous generators (PMSG) offer attractive advantages due to the higher reliability and power density. Considering the uncertainty influence of wind speed, PMSG with the traditional control method has poor-dynamic performance. Therefore, the Maximum Wind-Energy Captured based on the Inverse-System (MWECIS) method is proposed to improve the control precision and speed tracking rapidity of PMSG. In this paper, the inverse system is illustrated according to the conventional PMSG systems, and two systems (inverse system and PMSG system) are cascaded to obtain a decoupled pseudo-linear system. The proposed MWECIS method contributes to present a linear control law for PMSG system. Compared with the tip–speed-ratio control based on proportional–integral​ (TSR-PI) method, the proposed MWECIS method shows the better dynamic performance such as quickly and stably speed tracking ability. The simulation and experimental results verify the effectiveness of the proposed method, which could achieve the maximum wind-energy capture.

Optimal controller design for non-affine nonlinear power systems with static var compensators for hybrid UAVs

A generalized non-affine nonlinear power system model is presented for a single machine bus power system with a Static Var Compensator (SVC) or State Var System (SVS) for hybrid Unmanned Aerial Vehicles (UAVs). The model is constructed by differential algebraic equations on the MATLAB-Simulink platform with the programming technique of its S-Function. Combining the inverse system method and the Linear Quadratic Regulation (LQR), an optimized SVC controller is designed. The simulations under three fault conditions show that the proposed controller can effectively improve the power system transient performance.

Mathematical Modeling and Simulation of Three-level STATCOM Based on Instantaneous Reactive Power Theory

Establishing an accurate static synchronous compensator (STATCOM) mathematical model is very important to the research of device performance, the design of main circuit parameters and control systems. The working principle of STATCOM and its multiple optimization technology are analyzed in this article, mathematical modeling of STATCOM is derived using the switch function method, and the stability of the model is analyzed using the Routh–Hurwitz stability criterion. Based on the traditional PI control of reactive current and instantaneous reactive power theory, a new control strategy is proposed by combining the inverse system method and sliding mode variable structure theory. The simulation research in MATLAB shows that the proposed model and control strategy can accurately and quickly reflect the transient process of STATCOM, it has obvious role for the ability to stabilize the bus voltage, and it can fast suppression load low-frequency fluctuations and voltage flicker.

Neural network inverse system decoupling fuzzy self-tuning proportional–derivative control strategy of a bearingless induction motor

In view of the problems that the analytical inverse system decoupling method of bearingless induction motor is sensitive to the change of motor parameters and is greatly affected by unmodeled dynamics, and that of traditional proportional–derivative controller lacking the self-adaptive regulation ability, a neural network inverse system decoupling fuzzy self-tuning proportional–derivative control strategy is proposed for a bearingless induction motor system. First, under the conditions of considering the stator current dynamic of torque winding, and by neural network inverse system method, the bearingless induction motor system is decoupled into four pseudo-linear integral subsystems. Second, the traditional proportional–derivative controller is improved, and the fuzzy control algorithm is used to adjust the parameters of improved proportional–derivative controller adaptively. Thus, a neural network inverse system decoupling fuzzy self-tuning proportional–derivative control system is constructed for a bearingless induction motor. The simulation experimental results show that the proposed control strategy not only can effectively improve the stability, robustness and steady-state control accuracy of bearingless induction motor system, but also can significantly improve the dynamic response speed and the ability to resist the influences of motor parameter change and load disturbance.

Continuous convolution and nonlinear transformation for multi-shaker non-Gaussian random vibration control

This study proposes a continuous convolution method combined with memoryless nonlinear transformation for multi-input multi-output stationary non-Gaussian random vibration tests. The challenge of the multi-shaker non-Gaussian random vibration test lies in the coupling problems that are manifested in the inherent physical system and in the existence of cross-spectral densities. In the presented method, the independent stationary Gaussian random signals pass through a designed finite impulse response filter with a convolution manipulation first, and then the resulting signals are transformed to the non-Gaussian random signals by the memoryless nonlinear transformation method. The desired drive signals are obtained by the input–output relationship in the frequency domain. The finite impulse response filter is constructed by the frequency sampling technique in which the amplitude characteristics of the filter are determined by the predefined reference power spectral densities. A new monotonic nonlinear transformation function with an approximate kurtosis solution is provided. It only contains one parameter for kurtosis control both in sub-Gaussian and super-Gaussian cases. The memoryless nonlinear transformation is used to maintain the cross-spectral densities, although some distortions are introduced to the power spectra during the transformation process. The inverse system method is used to overcome the coupling problem caused by the inherent physical system. A simulation example and a triaxial vibration test are carried out, and the results indicate the validity and feasibility of the proposed method.

Inverse-system method for identification of damping-rate functions in non-Markovian quantum systems

Identification of complicated quantum environments lies in the core of quantum engineering, which systematically constructs an environment model with the aim of accurate control of quantum systems. In this paper, we present an inverse-system method to identify damping rate functions which describe non-Markovian environments in time-convolution-less master equations. To access information on the environment, we couple a finite-level quantum system to the environment and measure time traces of local observables of the system. By using sufficient measurement results, an algorithm is designed, which can simultaneously estimate multiple damping rate functions for different dissipative channels. Further, we show that identifiability for the damping rate functions corresponds to the invertibility of the system and a necessary condition for identifiability is also given. The effectiveness of our method is shown in examples of an atom and three-spin-chain non-Markovian systems.

Multi-Input-Multi-Output Continuous Swept-Sine Vibration Test Realization by Inverse Multistep Prediction Model

As frequency-varying sine excitations in rotating machines are always emerging during run-ups and shutdowns, the multi-input-multi-output (MIMO) swept-sine test is of utter significance in product validation. At present, swept-sine vibration tests are mostly conducted with frequency-domain methods, where drive spectra are generated and updated by frequency response function (FRF), and drive signals are then generated with sinusoid oscillators. In this paper, a time-domain approach using an inverse system method based on a multistep prediction model is developed to realize the MIMO continuous swept-sine vibration test. First, the multistep prediction model of the original system is estimated in the time domain. Then, the inverse multistep prediction model is derived. After that, this model is truncated to guarantee the robustness of the inverse system and the smoothness of the generated drive signals. At last, the proposed method is validated by a simulation example with a cantilever beam and an actual test by using a three-axis shaker. The results show that the MIMO continuous swept-sine vibration test can be operated effectively by the proposed method.

Torque identification based on LMS adaptive delay inverse system method

In order to relieve the dependence of load estimation upon the prior knowledge of mechanical system, an adaptive delayed inverse model is proposed for identifying the torque time history based on adaptive delay inverse system identification method. The LMS (least mean square) algorithm was used to identify the inverse model of the rotating system, which instead of system characteristic matrix inversion in common determination methods and ill-posed problem is avoided consequently. The adaptive delayed inverse model was used to identify the time-domain torque by analyzing the angular acceleration response data of the working state. The single-point time-domain torque of the bare shaft was identified by the angular acceleration response in the case of noiseless interference. The simulation results illustrate that the recognition results of this method is satisfied. It is proved by the experiment that the method is also feasible to the shaft system with disk coupling. The proposed method can be applied in practical engineering as it is not necessary to grip the mathematical model and system parameters in advance.

Decoupling Control of Permanent Magnet Synchronous Motor With Support Vector Regression Inverse System Method

Inverse system method is effective for controlling permanent magnet synchronous motor (PMSM). A novel support vector regression(SVR) inverse system method is proposed to realize decoupling control of PMSM in the article. Firstly, kernel space feature of the inverse model is optimized by using the prior information provided by the mathematical model of analytical inverse system to build two accurate SVR inverse models, which can solve the unreasonable kernel space feature when conventional SVR algorithm is employed to model PMSM inverse system. Then, the inverse system composing of two inverse models is cascaded with the original system to decouple PMSM system into two pseudo-linear subsystems. Finally, PID controller is employed to form a closed-loop control system. The simulation and experiment results show that the proposed method improves the generalization ability of inverse model and achieves high-performance control of PMSM.

Decoupling control of chassis integrated system for electric wheel vehicle

In order to eliminate the mutual interferences among the differential assist steering system, the active suspension system and the electrical stability control, this paper proposes a sliding mode decoupling control strategy based on the inverse system method for the electric wheel vehicle. The dynamic model of the integrated chassis system is established, and the coupling relationship among the subsystems is analyzed by the correlation analysis. Based on the inverse system method, a compound pseudo linear system is constructed by an inverse system connected in series before the original chassis system, which is linearized and decoupled into three independent linear integral systems. In order to improve the robustness and anti-interference of the decoupled system, a pre-compensation controller based on the sliding mode control is designed for the pseudo linear system. The results of simulation and vehicle test show that the proposed decoupled controller has excellent decoupling performance, which can accomplish the single-channel control of the three decoupled subsystems, and eliminate their influences and interferences. Furthermore, it can effectively track the reference signal and reduce the impact of the external interference, which can obtain an excellent comprehensive performance of the chassis system.

Radial position control for magnetically suspended high‐speed flywheel energy storage system with inverse system method and extended 2‐DOF PID controller

To achieve high-precision position control for the active magnetic bearing high-speed flywheel rotor system (AMB-HFRS), a novel control strategy based on inverse system method and extended two-degree-of-freedom (2-DOF) proportional–integral–derivative (PID) controller is proposed in this study. First, the inverse system method is employed to decouple the AMB flywheel rotor system with strong non-linear and coupling, into four independent subsystems. Subsequently, extended 2-DOF PID controllers are used to regulate the decoupled subsystems, to obtain good performances of disturbance rejection and tracking simultaneously. In the extended 2-DOF PID controller, a differential signal is produced by a velocity observer to improve the ability of against noise. Finally, the characteristics of stability, tracking, disturbance rejection and robustness of the control strategy proposed are analysed in theory, and its ability and effectiveness to control the radial position of the AMB-HFRS are further studied by simulations and experiments. It is shown that the control strategy proposed can keep the AMB-HFRS suspending stably from static state to the speed of 24,000 rpm, has the advantages of good tracking, high disturbance rejection, strong robustness and good ability of against noise.

Decoupling and Optimal Control of Multilevel Buck DC–DC Converters With Inverse System Theory

Multilevel buck dc–dc converters have advantages of low switching voltage stress, small inductor size, and high power density. To take an advantage of these properties, the flying capacitor voltage must be balanced at appropriate voltage references value. However, the multilevel buck dc–dc converters are a multi-input multioutput nonlinear strongly coupled control system. To address the problems associated with the complexity of strongly coupled voltages while maintaining control, in this article we propose a decoupled optimal control strategy with an inverse system theory. On the basis of establishing a large signal average model, a universal method to choose the output function for full linearization is proposed with the help of the inverse system method. Furthermore, the linearization and decoupling of the system are achieved, and a number of single-input, single-output pseudolinear subsystems are obtained. Based on the linearized system, multiple optimal controllers are designed to control the subsystems, which significantly reduces the difficulty in controller design. Numerical simulation results show that compared to proportional integral control with linear decoupling, the proposed control strategy has better dynamic regulation performance and stronger robustness under a six-level buck dc–dc converter. Finally, the proposed approach is further verified with the experimental results of a three-level buck dc–dc converter prototype.

NONLINEAR METHOD OF VEHICLE VELOCITY DETERMINATION BASED ON INVERSE SYSTEM AND TENSOR PRODUCT OF LEGENDRE POLYNOMIALS - INTERMEDIATE CLASS

Presented paper discusses two different nonlinear approaches to precrash velocity determination for vehicles from Intermediate Car Class. Data that was used to perform analyses introduced in this paper was taken from National Highway Traffic Safety Administration (NHTSA) database. Such database is comprised of substantial number of crash cases and main focus was put on frontal impacts. Hitherto used energy methods are based on linear model which proves to be inaccurate and producing significant errors. Presented considerations concern the inverse system and tensor product of Legendre polynomials. The focus of those methods is to establish the value of nonlinear coefficient which is the slope factor of precrash velocity Vt and deformation ratio Cs function. The application of the least square method provides more precise results in both cases than in previously researched solutions, with a slight advantage of the tensor product method. The obtained mean relative error of the velocity determination using the inverse system method is approximately 16,22% for the linear model and 10,58% for the nonlinear model. In the case of the tensor product method the errors for linear and nonlinear models are respectively 6,74% and 6,3%.

Multiple-input multiple-output non-stationary non-Gaussian random vibration control by inverse system method

Abstract This paper investigates the control method for multi-input multi-output non-stationary non-Gaussian random vibration test with the specified references composed of stationary power spectra, moving root mean square distributions and moving kurtosis distributions. The objective of random vibration test is to force the response signals of test structure to satisfy the specified references within tolerances. An inverse system method in time domain is used to guarantee the control of response time-frequency characteristics independently and simultaneously. The evolutionary spectrum theory is utilized to establish the matrix representation of non-stationary non-Gaussian input-output relationships of a linear dynamic system in frequency domain. To analyze a non-stationary non-Gaussian vibration signal, two sets of random numbers named moving root mean square and moving kurtosis are used to modulate a stationary random signal. The transformation process theory is utilized to obtain moving root mean square and moving kurtosis by a moving root mean square distribution and a moving kurtosis distribution respectively. The control algorithms are presented to update the drive signals according to the deviations between responses and references. A numerical example by a cantilever beam and a biaxial vibration test are carried out and the results demonstrate the feasibility and validity of the proposed methods.