Hybrid system modeling and autonomous control systems

Integrating self-health awareness in autonomous systems

In this paper we describe the architecture and the performances of a hybrid modular acquisition and control system prototype for environmental monitoring and geophysics. The system, an improvement of a VME-UDP/IP based system we developed for interferometric detectors of gravitational waves, is based on a dual-channel 18-bit low noise ADC, a 16-bit DAC module at 1MHz, and a 20-bit slower ADC necessary for the acquisition of an external calibration signal. The module can be configured as stand-alone or mounted on a motherboard as mezzanine in parallel with other modules. Both the modules and the motherboard can send/receive the configuration and the acquired/correction data for control through a standard EPP parallel port to a standard PC, where the real-time computation is performed. Experimental tests have demonstrated that the distributed control systems implemented with this architecture exihibit a delay time of less than 25 μs on a single channel, that is a sustained sampling frequency of more than 40kHz. The system is now under extensive test in two different experiments: the remote control and data acquisition of a set of seismometers, velocimeters and accelerometers to simulate a geophysics networks of sensors and the remote control of the end mirrors of a suspended Michelson interferometer through electrostatic actuators for interferometric detectors of gravitational waves.

The paper considers several models of linear hybrid systems described by discrete-difference and difference-differential equations with control. Special attention is paid to the difference-differential hybrid systems in symmetric form. For solutions of such systems, a variation-of-constants formula is proposed and the relative controllability-observability principle is established. For stationary systems, we introduce the determining equations and present solutions in the form of series of their determining equation solutions. Then algebraic properties of solutions of determining equation are investigated, in particular, the well-known Hamilton-Cayley matrix theorem is extended to the solutions of the system of determining equations. As a result, parametric criteria for the relative controllability and relative observability are given.

Analyzed the influence of main perturbation sources including non-spherical gravitational perturbation, atmospheric drag perturbation and third body gravitation perturbation to the satellite orbit, compensates the influence through the method that biased the semi-major axis and the inclination angle, which enhanced the orbital stability of satellite. Designed the satellite autonomous orbital control system, and discussed the method that through controlling the semi-major axis, the eccentricity and the inclination angle to complete the revisions to ascending node right ascension deviation and phase deviation. Finally through the simulation and the experiment of a satellite which running on nearly earth regression, circular orbit, simulation results indicated the system scheme satisfied the demand of satellite autonomous control

The synchronization of somatic motor outflow and sympathetic efferent activity during exercise has important functional consequences. For example, a certain degree of sympathetic vasoconstriction to active skeletal muscle vascular beds may be required to prevent an excessive decrease in vascular resistance during intense dynamic exercise involving a large skeletal muscle mass. Moreover, the redistribution of blood flow away from non-exercising vascular beds to contracting skeletal muscles is necessary to meet their increased metabolic demands. Historically, the nervous system has been separated arbitrarily into a volitional (somatic) and a reflex (autonomic) control system that does not necessitate volitional input (Koizumi & Brooks, 1972). However, during exercise this partition of the somatic and autonomic control systems is replaced by an overlapping control system that influences both somatic and sympathetic outflows in a parallel fashion. Previous work has suggested that the integration and co-ordination of the somatic and sympathetic motor responses during exercise were mediated by a supraspinal neural mechanism referred to as central command (Waldrop et al. 1996). However, there is an accumulating body of evidence, including papers on the role of the spinal cord in the regulation of sympathetic outflow (Weaver & Stein, 1989), suggesting that rhythmic neural activity destined for somatomotor and sympathetic outflows may be under the control of intrinsic neuronal circuitry in the spinal cord. In this issue of The Journal of Physiology, the paper by Chizh et al. (1998) demonstrates for the first time that some components of somatic motor and sympathetic neural outflows are synchronized by a spinal mechanism. The authors studied the relationship between sympathetic and somatic motor outflows from the thoraco-sacral spinal cord using an isolated trunk-hindquarters preparation of the adult mouse. They found that some of the activity in both somatic and sympathetic outflows was coupled. However, since there was also sympathetic neural activity that showed burst discharges in the absence of somatic motor activity, the spinal mechanism responsible for generating sympathetic burst activity was not the same mechanism that was responsible for somato-sympathetic coupling. Therefore, there remained spinal mechanisms that were capable of generating bursting activity independently of somatic and sympathetic activities. When NMDA was added to the perfusate to induce rhythmic somatic motor activity, a dose-dependent bursting pattern in sympathetic efferent and somatic motor nerves was evoked that was coupled at similar frequencies. Correlational analyses found a strong coherence between somatic motor outflow and sympathetic efferent discharge when triggered from peaks in somatic motor activity. However, this synchronization was not found when triggered from the peaks of sympathetic discharge. This finding led Chizh et al. (1998) to hypothesize that the generating mechanism responsible for somatic locomotor activity was the same mechanism responsible for coupling somatic outflow to sympathetic activity. These findings support the notion that the spinal cord possesses the necessary neuronal ‘machinery’ for generating and coupling sympathetic discharge with somatic motor outflow independently of supraspinal structures (i.e. the spinal rhythm generator represents a spinal central command). Important adjustments occur in the heart and blood vessels during exercise in order to provide the appropriate oxygen delivery to match the metabolic demand of contracting skeletal muscle. The coupling of somatic motor and sympathetic outflows is mediated by supraspinal neural mechanisms (supraspinal central command) in humans and animals (Fig. 1). In humans, intense intermittent static exercise produced a one-to-one synchronization of somatic motor activity with muscle sympathetic nerve activity that was purportedly directed to skeletal muscle vasculature (Victor et al. 1995). This synchronization persisted in the presence of both partial neuromuscular blockade (i.e. to increase central command) and after local anaesthetic block of the arm nerves to eliminate afferent feedback from skeletal muscle. Likewise, electrical and chemical stimulation of the hypothalamic locomotor region in decorticate cats after neuromuscular blockade evokes fictive locomotion that produces increases in arterial blood pressure (Waldrop et al. 1996) and synchronization of sympathetic nerve activity with hindlimb motor nerve activity (Hajduczok et al. 1991). And, as seen in humans, the synchronization of somatic motor activity and sympathetic discharge was unaffected by peripheral feedback mechanisms. These findings suggest that central command signals of supraspinal origin can regulate and co-ordinate sympathetic and somatomotor outflows during exercise. Figure 1 Synchronization of somatic motor outflow and sympathetic efferent activity during exercise is mediated by supraspinal and spinal mechanisms. The important work of Chizh et al. (1998) extends our understanding of the synchronization of somatic motor activity and sympathetic outflow by highlighting the role of a spinal somato-sympathetic generator (Fig. 1). Also, the coupling of somato-sympathetic neural outflows in the spinal cord may represent an exquisite mechanism to finely tune sympathetic discharge to the segmental level of somatic motor outflow during exercise. Finally, {fontsize the degree to which supraspinal central command signals influence the somato-sympathetic spinal generator needs to be studied to further our understanding of somato-sympathetic coupling during volitional exercise.

The authors propose a control scheme that combines the concepts of hybrid control and learning control for controlling force and position of a six-degree-of-freedom robotic end-effector with a closed-kinematic chain mechanism, which performs repeatable tasks. The control scheme consists of two control systems: the hybrid control system and the learning control system. The hybrid control system is composed of two feedback loops, a position loop and a force loop, which produce inputs to end-effector actuators, based on errors in position and contact forces of selected degrees of freedom. The learning control system, consisting of two proportional-derivative type learning controllers also arranged in a hybrid structure, provides additional inputs to the actuators to improve the end-effector performance after each trial. Experimental studies performed on a two-degree-of-freedom end-effector show that the control scheme provides path tracking with satisfactory precision while maintaining contact forces with minimal errors after several trials. >

A survey of modeling and control of hybrid systems

This paper investigates the application of a robust hybrid control design for a small scale helicopter flying with multiple linearised mathematical models. A hybrid control architecture is proposed and will be developed to cope with the complexity of the non-linear system. A class of this control system is known as hybrid control systems which deal with dynamic changes and jump transition behaviour between the changes. The small scale helicopter is known to inherently have these features. In this paper, the behaviours of the small scale helicopter are represented into five linearized models at trim conditions. When a wider region of flight envelope is considered, this approach leads to a switching problem representing changes from one mode to another mode in a predifined order for a safe and successful flight. In this paper we specifically investigate the control of transition dynamics between many modes as a hybrid system. One approach of control for hybrid switch system is characterized by Linear Matrix Inequalities (LMIs) for performance analysis and control synthesis. State jumps of the controller responding to switched of plant dynamics are exploited to improve control performance.

Hybrid actuator–damper–bracing control (HDABC) system with intelligent strategy and soil–structure interaction

Recently there has been increased research interest in the study of the hybrid dynamical systems (Sun & Ge, 2005) and (Li et al., 2005). These systems involve the interaction of discrete and continuous dynamics. Continuous variables take the values from the set of real numbers and the discrete variables take the values from finite set of symbols. The hybrid systems have the behaviour of an analog dynamic system before certain abrupt structural or operating conditions are changed. The event driven dynamics in hybrid control systems can be described using different frameworks from discrete event systems (Cassandras & Lafortune, 2008) such as timed automata, max-plus algebra or Petry nets. For dynamic systems whose component are dominantly discrete event, main tools for analysis and design are representation theory, supervisory control, computer simulation and verification. From the clasical control theory point of view, hybrid systems may be considered as a switching control between analog feedback loops. Generally, hybrid systems can achieve better performance then non-switching controllers because they can to reconfigure and reorganize their structures. For that is necessery correct coordination of discrete and analog control variables. The mathematical model for real process, generally, has the Hammerstein-Wiener form (Crama & Atkins, 2001) and (Zhao & Chen, 2006). It means that on the input and output of the process are present nonlinear elements (actuator and sensor). Here we will consider Hammerstein model which has the input saturation as nonlinear element. That is the most frequent nonlinearity encountered in practice (Hippe, 2006). Also, unmodeled dynamics with matching condition is present. As a control strategy will be used switching control. The switched systems can be viewed as higher abstraction of hybrid systems. The design of switching controllers having guaranted stability, known as the picewise linear LQ control (PLC), is first considered in (Wredenhagen & Belanger, 1994). The picewise linear systems are systems that have different linear dynamics in different regions of the continuous state space (Johansson, 2003). The PLC control has the associated switching surfaces in form of positively invariant sets and yields a relatively low-gain controller. In the LHG (low-and-high gain) design a low gain feedback law is first designed in such a way

In this paper, by applying interval methods, a new framework for analysis and control of discrete-time hybrid systems with parameter uncertainty is proposed. In analysis and control of hybrid systems, there are problem formulations such that convex polyhedra are computed, but for high-dimensional systems, it is difficult to solve these problems within the practical computation time. In this paper, instead of computing convex polyhedra, an interval method, which is one of classical methods in verified numerical computation, is applied to analysis and control of hybrid systems. By applying an interval method, discrete-time piecewise systems with parameter uncertainty can be approximately transformed into a mixed logical dynamical model.

Modeling concept for the infrastructure of autonomous logistic processes

Basic study for realization of adaptation, evolution, and self-diagnosis on an artificial heart has been carried out by an autonomous distributed control system for an ultra-lightweight pulsatile VAD (volume of 285 ml and weight of 360 g). The autonomous distributed control system was build by 4 layers (input layer, measurement layer, control layer, output layer) and an object manager, which was realized on a l chip microcomputer (Hitachi, SH7044, Japan). The input and output layer are composed of ND, PIO, SIO for interface with the VAD. The measurement layer consists of 4 autonomous objects: current measurement, velocity measurement, position measurement, and timer. The control layer consists of 3 autonomous objects: position control, velocity control, and current control. The position and velocity control object are constructed by fuzzy inference algorism in order to build doctors' and engineers' knowledge into the VAD control. The object manager paces events on each object in order to maintain time series processes. The control system can he adapted to an axial flow VAD by exchanging the position measurement and position control object into a flow estimation and flow control object. In vitro experiment showed that The VAD was driven stably enough to maintain cardiac function by cooperation of independently operated each object like cells in the control system. In conclusion, the above results shows that the autonomous distributed control system promises suitability as a new superior artificial control system.

This study proposes a hybrid supervisory H∞ control system using a recurrent cerebellar model articulation controller (RCMAC) for achieving high precision position tracking performance of permanent-magnet synchronous motor (PMSM) servo drive. The hybrid control system is composed of a RCMAC, a supervisory controller and a robust H∞ controller. The RCMAC is used as the main position tracking controller to mimic a perfect computed torque control law, and the robust H∞ controller is designed with adaptive bound estimation algorithm to compensate for the approximation error between the RCMAC and the ideal controller. The supervisory controller is designed based on the uncertainty bound of the PMSM to stabilise the system states around a predefined bound region and achieve satisfactory tracking performance. The online adaptive control laws are derived based on the Lyapunov stability analysis, so that the stability of the system can be guaranteed. A computer simulation is developed and an experimental system is established to validate the effectiveness of the proposed hybrid control system. All control algorithms are implemented in a TMS320C31 digital signal processor-based control computer. The simulated and experimental results confirm that the proposed hybrid control system grants robust performance and precise response regardless of load disturbances and PMSM parameters uncertainties.

A mathematical approach to discrete-event dynamic modelling of hybrid systems