A PID model of human balance keeping

This paper analyzes the dynamic friction models on the turntable from the engineering practicality. As turntable has the peculiarities such as large tracking range, sudden transferring, high-precision and stability at a low velocity, a control model combining PID Control and Intelligent Sliding Model Control is put forward in this paper. In this model, the switch works according to a threshold. PID Control will be adopted when the tracking error is greater than the threshold and Fuzzy Sliding Model will be used otherwise. The chattering phenomenon is effectively alleviated and the control output is softened by adopting the improved Fuzzy Sliding Model. The genetic algorithm is adopted to dynamically optimize the fuzzy rule of the Fuzzy Sliding Model Control. The global asymptotic stability of the system is proved via Lyapunov's direct method. The effectiveness and feasibility of the presented control model is proved by the results of simulation and practical tests gained after applying it to the high-precision turntable.

Neurofeedback systems can be modeled as closed loop control systems with negative feedback. However, little work to date has investigated the potential of this representation in gaining a better understanding of the actual dynamics of neurofeedback towards explaining subjects' performance. In this paper, we analyze neurofeedback training data through a PID control model. We first show that PID model fitting can produce curves that are qualitatively aligned to the measured BCI signal. Secondly, we examine how brain activity during neurofeedback can be related to common characteristics of control systems. For this, we formalized a pre-existing neurofeedback EEG experiment using a SimulinkR model that captures both the neural activity and the external algorithm that was utilized to generate the feedback signal. We then used a regression model to fit individual trial data to PID coefficients for the control model. Our results suggest that successful trials tend to be associated to higher average values of Ki, which represents the error-reducing component of the PID controller. It hints that convergence in successful neurofeedback is progressive but complete in approaching the target.

The control of the human body sway by the central nervous system, muscles, and conscious brain is of interest since body sway carries information about the physiological status of a person. Several models have been proposed to describe body sway in an upright standing position, however, due to the statistical intractability of the more realistic models, no formal parameter inference has previously been conducted and the expressive power of such models for real human subjects remains unknown. Using the latest advances in Bayesian statistical inference for intractable models, we fitted a nonlinear control model to posturographic measurements, and we showed that it can accurately predict the sway characteristics of both simulated and real subjects. Our method provides a full statistical characterization of the uncertainty related to all model parameters as quantified by posterior probability density functions, which is useful for comparisons across subjects and test settings. The ability to infer intractable control models from sensor data opens new possibilities for monitoring and predicting body status in health applications.

In practice, the volatile organic compounds (VOCs) pollution can exist when refueling due to the properties of the gasoline, low viscosity and high saturated-vapor pressure. A new gasoline vapor recovery system involving frequency conversion technology and machine learning is developed to cope with this problem. In the proposed system, firstly, the pumping capacity of the vacuum pump is evaluated, and test shows an almost linear relationship between suction volume and frequency. Then, the Multi-Layer Perception (MLP) neural network and the support vector regression (SVR) are employed to predict the gas-liquid ratio, and the numerical examples are presented to prove the high prediction accuracy of the MLP and SVR, respectively, where the MLP neural network has better generalization ability. Finally, compared with the two gasoline vapor recovery systems based on the 1: 1 fixed control model and the PID control model, respectively, the gasoline vapor recovery efficiency is improved significantly by the new gasoline vapor recovery system.

Model predictive control strategy of energy-water management in urban households

In this paper, PID control model was set up for the main steam temperature control system of modern large-scale power plant, combined the immune algorithm and particle swarm optimization, and improved by adding adaptive crossover and adaptive mutation. It is optimized the main steam temperature control system which in typical load conditions with the improved algorithm. By comparison with the traditional genetic algorithm shows, this algorithm has certain advantages on convergence and robustness.

The cognitive trait of hypnotizability, associated with the proneness to accept suggestions, exhibits several physiological correlates including the modulation of sensorimotor integration and, in particular, of postural control. In this respect, we have shown that, at eyes closure, healthy subjects with high hypnotizability scores (highs) having their feet 2 cm apart show larger and faster body sway with respect to low hypnotizable individuals (lows). The aim of the present study was to investigate whether hypnotizability modulates body sway during slightly more demanding and very difficult postural conditions such as feet together bipedal posture and one legged stance, respectively. The Center of Pressure (CoP) Area, mean Velocity, the CoP mean position (Xmean, Ymean) and its variability (SDx, SDy) in the frontal and sagittal planes were acquired in 18 highs (9 females) and 18 lows (9 females). Results showed that the previously observed lows' smaller and slower body sway was not present any longer. Nonetheless, hypnotizability interacted with gender in the modulation of the variability of the CoP movement in the frontal plane during both the bipedal feet together posture and one legged stance, as significant gender differences were observed only among lows. In conclusion, results confirm a role of hypnotizability in sensorimotor integration and support the relevance of hypnotic assessment in clinical settings, as hypnotizability may be responsible for part of the postural variability.

In order to better understand the background behind the origin of human bipedality, the functional significance of the human upright posture in terms of stability should be more investigated. Therefore, in this study, we examined postural stability of human upright posture against external perturbations and compared it with that of ape-like bent-hip, bent-knee posture. Five male participants were ask to stand on a stabilometer and forward and backward horizontal surface perturbations were applied. Fluctuation of the center of pressure, electromyographic signals, and body sway were monitored.The results show the human upright posture, despite of its relatively higher location of the center of body mass (COM), is not significantly less stable against the external perturbations than the ape-like flexed posture. Moreover, it is suggested that postural adjustments against external perturbations become more difficult in the flexed posture, since muscles have to be more activated not only to cope with the body sway, but also to sustain the flexed posture against the gravity. Therefore, the upright posture seems to be more advantageous than the mechanically more stable flexed posture as a whole. Due to this inherent advantage, it is deduced that the human ancestors could probably transfer to the upright posture in a relatively early stage, once bipedality becomes necessary.

Model reference adaptive control with adjustable gain for piezoelectric actuator

In order to improve the accuracy and dynamic characteristics of unmanned aerial vehicle (UAV) undertaking platform with Stewart mechanism, a posture control strategy based on dynamic model predictive control algorithm is proposed in this paper. First, the dynamics of the Stewart platform is analyzed, and the state space expression of the dynamic model of the Stewart platform is established. Then, the algorithm based on the dynamic model predictive control is proposed, and the model predictive controller is designed. Finally, a simulation model of the UAV undertaking platform is established, the parameters of the model predictive controller are tuned, and the undertaking platform pose control simulation experiment is carried out. Physical experiments are performed to compare the control effects of traditional PID control and dynamics-based model predictive control on the undertaking platform.The results show that the model predictive control method based on dynamics can effectively improve the control accuracy and dynamic characteristics of the UAV undertaking platform.

The effects of passive tactile cues about body sway on stability during standing were evaluated in subjects with a wide range of sensorimotor and balance performance. Healthy young adults, diabetic subjects with varying degrees of peripheral sensory neuropathy and older subjects aged 70-80 years were studied. Body sway was measured when subjects stood on the floor and on a foam rubber mat, with or without an applied stimulus that rubbed on the skin at the leg or shoulder as the body swayed. The results show that this stimulus reduced body sway (mean reduction 24.8%+/-1.5) and thus had a stabilizing effect as big as vision or sensory information from the feet. The reduction in sway was not based on active touch. The stimulus was not restricted to a particular region of the body, but was more effective on the shoulder than the leg, and was more effective when standing with eyes shut or when standing on the foam mat. It was also most effective in those subjects who had the greatest sway during normal standing. Thus, the response appears to be graded with the amplitude of the stimulus. We concluded that, if passive sensory input about posture is available, the postural control process adapts to this input, modulating postural stabilizing reactions.

The aim of this study is to improve and facilitate the methods used to assess risk of falling at home among older people through the computation of a risk of falling in real time in daily activities. In order to increase a real time computation of the risk of falling, a closed-loop balance model is proposed and compared with One-Leg Standing Test (OLST). This balance model allows studying the postural response of a person having an unpredictable perturbation. Twenty-nine volunteers participated in this study for evaluating the effectiveness of the proposed system which includes seventeen elder participants: ten healthy elderly ( 68.4 ±5.5 years), seven Parkinson's disease (PD) subjects ( 66.28 ±8.9 years), and twelve healthy young adults ( 28.27 ±3.74 years). Our work suggests that there is a relationship between OLST score and the risk of falling based on center of pressure measurement with four low cost force sensors located inside an instrumented insole, which could be predicted using our suggested closed-loop balance model. For long term monitoring at home, this system could be included in a medical electronic record and could be useful as a diagnostic aid tool.

In the paper is highlighted the industrial objects as cars, spacecraft, telescopes, plotters, lasers, elevators, etc., which are described by the mathematical model with double astatism. These models of control objects have a double pole in the origin of the coordinate axes. In order to tune the PID controller to the model of object with double astatism, it was elaborated the tuning algorithm based on the maximum stability degree method with iterations. It was done the computer simulation of the automatic control system with the respectively model of object and PID controller and it was done the analysis of the obtained performance. The advantages of the maximum stability degree method with iterations were highlighted by the reducing calculations and time, which lead to the procedure simplification of the PID controller tuning.

Control design of a TRMS system resembling helicopter is very complicated task. Since it is highly non-liner system, which makes the controller design for TRMS system very complex problem. TRMS system is connected with two rotors, in which first one is main rotor and the other is tail rotor. This is based on a beam, supported by a counter balance. Two degrees of freedom (2DOF) PID controller and FOPID controller model of TRMS involving horizontal and vertical plane has been obtained for controller design. 2-DOF PID and FOPID controller both have been discussed in this paper. With the Simulation results obtained for vertical and horizontal plane, factional order PID controller has been found to be better than 2-DOF controller. The results of all the simulation work has been performed on the MATLAB/Simulink environment.

Control of upright standing posture during low-frequency linear oscillation