Inverse System Model Research Articles

Blood pressure estimation based on pulse rate variation in a certain period

Availability of daily continuous blood pressure (DCBP) has a strong impact to realization of healthy society. However, existing methods to obtain blood pressure of cuff type and cuff-less types utilizing correlation with pulse waveform, pulse transit time or pulse rate; or computation of circulation model are not suitable to obtain DCBP. Here we implemented a method based on a simple circulatory system model using pulse rate measurement to overcome the limitations, and showed that it provides appropriate estimation of DCBP. The present model consists of a circulatory dynamic system model and an inverse model of a circulatory control system with input of pulse rate and six model parameters representing standard pulse rate, elasticity of systemic arteries, peripheral vascular resistance, and characteristics of resistance and stroke volume control. Validity of the DCBP estimation method was examined by preliminary experiment for one subject in four days and that for four subjects in one day. DCBP estimation was performed with 24-hour pulse rate measurement by a wearable device and sphygmomanometer measurement for parameter determination and verification. Mean absolute errors in systolic/diastolic pressures were appropriate ones for preliminary experiments with 9.4/6.4 mmHg in four days and 7.3/5.9 mmHg in five subjects.

A Monte Carlo Dual-RLS Scheme for Improving Torque Sensing without a Sensor of a Disturbance Observer for a CMG

This article introduces a novel identification technique for the inverse model of a dynamical system by a dual-recursive least square (DRLS) algorithm to estimate the disturbance torque in the disturbance observer (DOB) configuration. Since the DOB uses the inverse model to estimate the disturbance, the accurate estimation of the inverse model affects the external torque estimation performance. To estimate the inverse model more accurately, Monte Carlo simulation is conducted for two RLS filters formed a back-to-back cascaded structure to identify both forward and inverse models simultaneously. Although the inverse model can be numerically driven by the identified forward model in the conventional way, we can have the improved accuracy of estimating the inverse model by dual-RLS filters. The effects on the external torque estimation accuracy by the proposed method are experimentally verified by evaluating the performance of estimating the disturbance torque in the control moment gyroscope (CMG) actuator.

Fuzzy MRAS rotor resistance identification of BL-IM based on reactive power

As for the inverse decoupling control system of a bearingless induction motor (BL-IM), in order to eliminate the influence of rotor resistance variation on its control performance, on the basis of the reactive power calculation of torque system, a novel fuzzy model reference adaptive (MRAS) identification method of rotor resistance is proposed. The reference model and adjustable model of instantaneous reactive power are derived in detail. In order to improve the identification performance of rotor resistance, a fuzzy PI adaptive law based on popov super stability theory is constructed. On this basis, a rotor resistance identifier is constructed, and it is used to on-line correct the rotor resistance parameter in the inverse system mathematical model of a BL-IM system. Based on the inverse decoupling control system of a BL-IM, the simulation experimental analysis and verification are carried out. The simulation experimental results have shown that when the proposed identification method of rotor resistance is used, not only the identification- and tracking-speed of rotor resistance can be effectively improved, but also the identification accuracy of rotor resistance can be improved; as for the BL-IM system, after the rotor resistance parameter is on-line corrected, not only the inverse dynamic decoupling control performance can be effectively improved, but also the robustness of BL-IM system to the variation of rotor resistance parameters can be improved.

A synergetic strategy of automobile intelligent cruise system based on fuzzy control adopting hierarchical structure

To improve automobile travel safety and relieve the intension of driving fatigue, a synergetic strategy on the throttle and brake combined control of automobile cruise system is proposed based on fuzzy control theory. A hierarchical control structure, including the upper fuzzy controller and the lower model match controller, is designed for integrated control function. The upper controller consists of the two input variables, that is, the deviation of the theoretical safe distance and the relative distance and the relative velocity between the host car and the preceding vehicle, and the single output variable, that is, the excepted acceleration of host car. The lower controller has achieved the fast compensation of excepted acceleration by adopting parallel feedforward and feedback compensator to input into the inverse dynamics model of automobile cruise system. Using MATLAB/Simulink, the control function on the proposed synergetic strategy is validated for different working cases. The results show that the synergetic strategy possesses an integrated capability involved automated stop & go control, and following the preceding car to prevent rear-end collision, and the constant velocity cruise whether the driving conditions of the city road or expressway.

A centrifuge-based flight simulator: Optimization of a baseline acceleration profile based on the motion sickness incidence

Simulator sickness is a common problem when using centrifuge-based flight simulator. During centrifuge-based training, achieving a G-baseline level and returning to a complete stop after each G-profile still cause unpleasant sensations and motion sickness. The aim of this study was to determine the optimal G-baseline level and the optimal approach motion cueing when the centrifuge-based flight simulator achieved and returned from this G-baseline level. A model of motion sickness incidence (MSI) was used to elucidate the optimal solution of motion cueing. The motion stimuli were computed based on an inverse kinematics model of the centrifuge-based motion system. For each analysed G-baseline profile, there were stimuli that provoked the occurrence of MSI. These stimuli were directly proportional to the applied G-onset rate. There was found the optimal G-baseline level at 1.41 G and optimal motion cueing (0.05 G s−1) that gave the minimal MSI. Up to 41% and 32% a reduction in the MSI could be obtained during the achievement and return from this G-baseline level, respectively. In order to confirm obtained results further studies should be performed with participants in an actual centrifuge-based flight simulator.

LS-SVM Inverse System Decoupling Control Strategy of a Bearingless Induction Motor Considering Stator Current Dynamics

The bearingless induction motor (BL-IM) is a multivariable, nonlinear and strongly coupled object, in order to achieve its dynamic decoupling control with high performance, on the basis of the least square support vector machine(LS-SVM) principle, a novel LS-SVM inverse system decoupling control strategy is proposed. Firstly, under the conditions of taking the stator current dynamics of torque windings into account, the state equations of the BL-IM system are established. Secondly, based on the approximation and identification fitting ability of the LS-SVM to arbitrary nonlinear function, the inverse system mathematical model of the BL-IM system considering the stator current dynamics is trained and obtained. After that, according to the decoupling principle of inverse system, the BL-IM system is decoupled into four second-order pseudo-linear integral subsystems, include a motor speed subsystem, a rotor flux-linkage subsystem and two radial displacement component subsystems. At the end, the comprehensive simulation analysis of the LS-SVM inverse decoupling control system are carried out. From the simulation results, it can be known that the dynamic decoupling control among the motor speed, rotor flux-linkage and two radial displacement components can be realized, meanwhile after considering the dynamics of the stator current, the LS-SVM inverse decoupling control system of BL-IM has the characteristics of fast response and strong anti-interference ability.

Stator flux orientation inverse system decoupling control strategy of bearingless induction motor considering stator current dynamics

The bearingless induction motor (BLIM), is a multi‐variable, nonlinear, and strongly coupled system. In order to improve its dynamic control performance, considering the stator current dynamics, a stator flux orientation (SFO) inverse system decoupling control strategy is proposed in this paper. Taking the dynamic characteristics of the torque winding current into account, the state equation of the BLIM system based on SFO is established. Then, on the basis of invertibility analysis, the inverse system dynamic mathematical model of the BLIM system is derived, the inverse system dynamic decoupling control strategy is presented, and the comprehensive design of the closed loop for each decoupled linear subsystem is carried out. Simulation experimental results show that the BLIM control system has excellent dynamic and static decoupling control performance, the influence of rotor parameters can be effectively overcome, and the ability to resist the load torque disturbance can be obviously improved. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Adaptive Inverse Control Based on Kriging Algorithm and Lyapunov Theory of Crawler Electromechanical System

The electromechanical system of a crawler is a multi-input, multioutput strongly coupled nonlinear system. In this study, an adaptive inverse control method based on kriging algorithm and Lyapunov theory is proposed to improve control accuracy during adaptive driving. The electromechanical coupling model of the electromechanical system is established on the basis of the dynamic analysis of the crawler. In accordance with the kriging algorithm, the inverse model of the electromechanical system of the crawler is established by offline data. The adaptive travel control law of the crawler is obtained on the basis of Lyapunov theory. Combined with the kriging algorithm, the adaptive driving reverse control method is designed, and the online system is used to update and perfect the inverse system model in real time. Finally, the virtual prototype model of the crawler is established, and the control effect of the adaptive inverse control method is verified by theoretical analysis and virtual prototype simulation.

Neural network inverse system decoupling control strategy of BLIM considering stator current dynamics

The bearingless induction motor (BLIM) is a multi-variable, non-linear, strong coupling system. To achieve higher performance control, a novel neural network inverse system decoupling control strategy considering stator current dynamics is proposed. Taking the stator current dynamics of the torque windings into account, the state equations of the BLIM system is established first. Then, the inverse system model of the BLIM is identified by a three-layer neural network; by means of the neural network inverse system method, the BLIM system is decoupled into four independent second-order linear subsystems, include a rotor flux subsystem, a motor speed subsystem and two radial displacement component subsystems. On this basis, the neural network inverse decoupling control system is constructed, the simulation verification and analyses are performed. From the simulation results, it is clear that when the proposed decoupling control strategy is adopted, not only can the dynamic decoupling control between relevant variables be achieved, but the control system has a stronger anti-load disturbance ability, smaller overshoot and better tracking performance.

Data-driven predictive control of molten iron quality in blast furnace ironmaking using multi-output LS-SVR based inverse system identification

Abstract Control of blast furnace (BF) ironmaking process has always been a hot and difficult issue in metallurgic engineering and automation. In this paper, a novel data-driven inverse system identification based predictive control method is proposed for multivariate molten iron quality (MIQ) indices in BF ironmaking process. First, since the widely used least-square support regression (LS-SVR) algorithm cannot cope with the multi-output problem directly, this paper uses multi-task transfer learning technology to construct a novel multi-output LS-SVR (M-LS-SVR) for multivariable nonlinear systems. Then, this M-LS-SVR is adopted to identify the inverse system model of the controlled BF ironmaking process with the help of the presented modeling performance comprehensive evaluation and NSGA II based multi-objective parameter optimization. In order to better perform the control of the MIQ indices, the identified inverse system model is used to compensate the controlled nonlinear BF system to a compounded pseudo linear system with linear transitive relation. Such an inverse system based data-driven predictive control can effectively improve the control performance of the conventional nonlinear predictive control. Data experiments using actual industrial data from a large BF show that the proposed methods are effective, advanced and practical, and provide a solution to the operational control and optimization of the BF ironmaking process.

Convertible aircraft dynamic modelling and flatness analysis

This paper describes the dynamic modelling of a vertical take-off and landing (VTOL) aircraft and shows the flatness of the proposed model. Flat systems have the property that the inputs and the states can be written as functions of a set of the system outputs (called flat outputs) and the derivatives of these flat outputs. The flatness property allows to compute an inverse dynamic model of the given system. This can be used in path planning, nonlinear control and fault detection and isolation. The convertible aircraft presented in this paper uses redundant actuators. The advantage of this design is twofold. Firstly, it is possible to configure actuators to optimize both stationary and fast horizontal flight. Secondly, in case of one actuator failure, it provides sufficient flexibility to reconfigure the actuators in order to land safely. An important contribution of this paper is the demonstration of the flatness property for the proposed dynamical model of the convertible aircraft.

Effect of Constraint Loading on the Lower Limb Muscle Forces in Weightless Treadmill Exercise.

Long exposure to the microgravity will lead to muscle atrophy and bone loss. Treadmill exercise could mitigate the musculoskeletal decline. But muscle atrophy remains inevitable. The constraint loading applied on astronauts could affect the muscle force and its atrophy severity. However, the quantitative correlation between constraint loading mode and muscle forces remains unclear. This study aimed to characterize the influence of constraint loading mode on the lower limb muscle forces in weightless treadmill exercise. The muscle forces in the full gait cycle were calculated with the inverse dynamic model of human musculoskeletal system. The calculated muscle forces at gravity were validated with the EMG data. Muscle forces increased at weightlessness compared with those at the earth's gravity. The increasing percentage from high to low is as follows: biceps femoris, gastrocnemius, soleus, vastus, and rectus femoris, which was in agreement with the muscle atrophy observed in astronauts. The constraint loading mode had an impact on the muscle forces in treadmill exercise and thus could be manipulated to enhance the effect of the muscle training in spaceflight. The findings could provide biomechanical basis for the optimization of treadmill constraint system and training program and improve the countermeasure efficiency in spaceflight.

H-Shaped Multiple Linear Motor Drive Platform Control System Design Based on an Inverse System Method

Due to its simple mechanical structure and high motion stability, the H-shaped platform has been increasingly widely used in precision measuring, numerical control machining and semiconductor packaging equipment, etc. The H-shaped platform is normally driven by multiple (three) permanent magnet synchronous linear motors. The main challenges for H-shaped platform-control include synchronous control between the two linear motors in the Y direction as well as total positioning error of the platform mover, a combination of position deviation in X and Y directions. To deal with the above challenges, this paper proposes a control strategy based on the inverse system method through state feedback and dynamic decoupling of the thrust force. First, mechanical dynamics equations have been deduced through the analysis of system coupling based on the platform structure. Second, the mathematical model of the linear motors and the relevant coordinate transformation between dq-axis currents and ABC-phase currents are analyzed. Third, after the main concept of inverse system method being explained, the inverse system model of the platform control system has been designed after defining relevant system variables. Inverse system model compensates the original nonlinear coupled system into pseudo-linear decoupled linear system, for which typical linear control methods, like PID, can be adopted to control the system. The simulation model of the control system is built in MATLAB/Simulink and the simulation result shows that the designed control system has both small synchronous deviation and small total trajectory tracking error. Furthermore, the control program has been run on NI controller for both fixed-loop-time and free-loop-time modes, and the test result shows that the average loop computation time needed is rather small, which makes it suitable for real industrial applications. Overall, it proves that the proposed new control strategy can be used in industrial applications that have high-precision and high real-time performance requirements.

Sequential forward-inverse design for genetic network modeling

This paper proposes methods for forward and inverse system modeling using Bayesian and least squares regression. These methods are based on both space-filling design criteria for multiple response problems and linear optimality criteria focusing on D-optimality. Modeling with and without the constant term is considered motivated by the case study application of genetic network modeling. We propose extended one-factor-at-a-time experimentation followed by augmentation of next stage design which offers biologists simplicity. Results are illustrated both numerical examples, a test problem from the literature, and a case study motivated by an real world biological research related to genetic network modeling.

Data-Based Tuning of Reduced-Order Inverse Model in Both Disturbance Observer and Feedforward With Application to Tray Indexing

Performance of traditional model-based control relies upon accurate modeling. In motion control of flexible systems, it is desirable to use the reduced-order model for ease of trajectory planning and pole placement, but its performance is constrained by modeling inaccuracies due to the existence of friction and multiple flexible modes. To improve the tracking performance, we have developed a data-based method for iterative tuning of the parameters in the reduced-order inverse model within a three-degree-of-freedom composite control structure. The proposed method solely makes use of the input-output data obtained during closed-loop experiments to fine-tune the inverse system model, and accurate system modeling is not required. Unbiasedness of the cost function gradient estimation is proven under reasonable assumptions of stochastic properties of the perturbations. Simulation and experiments are conducted to further illustrate the proposed method and show its practical appeals in industrial applications.

A unified dynamic algorithm for wheeled multibody systems with passive joints and nonholonomic constraints

This paper presents a systematic approach to develop a generalized symbolic/numerical dynamic algorithm for modeling and simulation of multibody systems with branches and wheels. The proposed dynamic algorithm includes the direct kinematic and inverse dynamic models of the wheeled systems with prismatic/revolute as well as actuated/passive degrees of freedom. Using the geometric configuration of the system through modified Denavit–Hartenberg convention, symbolic equations in general algorithmic form are developed for kinematic constraints associated with the wheel–ground contacts. The Newton–Euler equations are used to develop an algorithm for the inverse dynamic model of the multibody system. The complete algorithm is then used to solve the kinematics and dynamics of the system, and computes: (i) the kinematics of the external/internal passive degrees of freedom of the system, (ii) the Lagrange multipliers associated with the wheel–ground contacts, and (iii) the driving forces/torques of the actuated degrees of freedom. Some examples are solved with the help of the proposed algorithm, using MATLAB, to illustrate its implementation on different wheeled systems. These examples include a differential wheeled robot, a snake-like wheeled system, and a bicycle.

Inverse system modeling and decoupling control of bearingless induction motor based on air gap flux orientation

Inverse system modeling and decoupling control of bearingless induction motor based on air gap flux orientation

Automotive vehicle engine mount based on an MR squeeze-mode damper: modeling and simulation

The study investigates the performance of a semi-active vehicle engine mount incorporating an MR damper working in the squeeze mode (MRSQD), summarising its design, operating principles and key characteristics. The mathematical model of the mount is formulated based on the newly developed MRSQD. Two control algorithms are proposed for MRSQD control. The first algorithm (ALG1) uses the inverse model of the engine-frame system, the other is the sliding mode algorithm (ALG2). The effectiveness of the engine mount system is demonstrated in computer simulation.

A Convenient Vibration Compensation and Control Method of Bearingless Induction Motor

To achieve the rotor’s high precision suspension control of bearingless induction motor, a kind of convenient vibration compensation and control method is presented. The inverse model of magnetic suspension system is established, and by inverse system method, the decoupling control between two radial displacement components are achieved firstly; after then, through the compensation of unbalanced vibration control current, the compensation control force of unbalanced vibration that is used to counteract the unbalanced exciting force of bearingless rotor, is generated. Simulation results have shown that when adopting the proposed control strategy, the unbalanced vibration of bearingless rotor can be inhibited effectively either in the start stage or in the steady operation state.

Trajectory generation and control of a knee exoskeleton based on dynamic movement primitives for sit-to-stand assistance

This paper presents a novel control approach for a knee exoskeleton to assist individuals with lower extremity weakness during sit-to-stand motion. The proposed method consists of a trajectory generator and an impedance controller. The trajectory generator uses a library of sample trajectories as the training data and the initial joint angles as the input to predict the user’s intended sit-to-stand trajectory. Utilizing the dynamic movement primitives theory, the trajectory generator represents the predicted trajectory in a time-normalized and rather a flexible framework. The impedance controller is then employed to provide assistance by guiding the knee joint to move along the predicted trajectory. Moreover, the human-exoskeleton interaction force is used as the feedback for on-line adaptation of the trajectory speed. The proposed control strategy was tested on a healthy adult who wore the knee exoskeleton on his leg. The subject was asked to perform a number of sit-to-stand movements from different sitting positions. Next, the measured data and the inverse dynamic model of the human-exoskeleton system are used to calculate the knee power and torque profiles. The results reveal that average muscle activity decreases when the subject is assisted by the exoskeleton.