A common energy harvesting device uses a piezoelectric patch on a cantilever beam with a tip mass. The usual configuration exploits the linear resonance of the system; this works well for harmonic excitation and when the natural frequency is accurately tuned to the excitation frequency. A new configuration is proposed, consisting of a cantilever beam with a tip mass that is mounted vertically and excited in the transverse direction at its base. This device is highly non-linear with two potential wells for large tip masses, when the beam is buckled. The system dynamics may include multiple solutions and jumps between the potential wells, and these are exploited in the harvesting device. The electromechanical equations of motion for this system are developed, and its response for a range of parameters is investigated using phase portraits and bifurcation diagrams. The model is validated using an experimental device with three different tip masses, representing three interesting cases: a linear system; a low natural frequency, non-buckled beam; and a buckled beam. The most practical configuration seems to be the pre-buckled case, where the proposed system has a low natural frequency, a high level of harvested power and an increased bandwidth over a linear harvester.

The design and analysis of energy harvesting devices is becoming increasing important in recent years. Most of the literature has focused on the deterministic analysis of these systems and the problem of uncertain parameters has received less attention. Energy harvesting devices exhibit parametric uncertainty due to errors in measurement, errors in modelling and variability in the parameters during manufacture. This paper investigates the effect of parametric uncertainty in the mechanical system on the harvested power, and derives approximate explicit formulae for the optimal electrical parameters that maximize the mean harvested power. The maximum of the mean harvested power decreases with increasing uncertainty, and the optimal frequency at which the maximum mean power occurs shifts. The effect of the parameter variance on the optimal electrical time constant and optimal coupling coefficient are reported. Monte Carlo based simulation results are used to further analyse the system under parametric uncertainty.

This article investigates the possibility of piezoelectric energy harvesters as energy scavenging devices in highway bridges. The structural vibration due to the motion of a load (vehicle) on the bridge is considered as the source of energy generation for the harvester. The energy generated in this way can be useful for wireless sensor networks for structural health monitoring of bridges by reducing or even eliminating the need for battery replacement/recharging. A highway bridge model with a moving point load is investigated and a linear single-degree-of-freedom model is used for the piezoelectric energy harvester. Two types of harvesters, namely, the harvesting circuit with and without an inductor, have been considered and the energy generated for a single vehicle has been estimated. These results may be used, together with traffic statistics, to obtain the variation of average power and thus, for a given application, help to design the energy management system.

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This paper presents an analysis of piezomagnetoelastic energy harvesters under broadband random ambient excitations for the purpose of powering low-power electronic sensor systems. Their nonlinear behavior as a result of vibration in a magnetic field makes piezomagnetoelastic energy harvesters different from classical piezoelastic energy harvesters. An equivalent linearization-based analytical approach is developed for the analysis of harvested power. A closed-form approximate expression for the ensemble average of the harvested power is derived and validated against numerical Monte Carlo simulation results. Our results show that it is possible to optimally design the system such that the mean harvested power is maximized for a given strength of the input broadband random ambient excitation. V

Diabetes is a long-term disease during which the body's production and use of insulin are impaired, causing glucose concentration level to increase in the bloodstream. Regulating blood glucose levels as close to normal as possible leads to a substantial decrease in long-term complications of diabetes. In this paper, an intelligent online feedback-treatment strategy is presented for the control of blood glucose levels in diabetic patients using single network adaptive critic (SNAC) neural networks (which is based on nonlinear optimal control theory). A recently developed mathematical model of the nonlinear dynamics of glucose and insulin interaction in the blood system has been revised and considered for synthesizing the neural network for feedback control. The idea is to replicate the function of pancreatic insulin, i.e. to have a fairly continuous measurement of blood glucose and a situation-dependent insulin injection to the body using an external device. Detailed studies are carried out to analyze the effectiveness of this adaptive critic-based feedback medication strategy. A comparison study with linear quadratic regulator (LQR) theory shows that the proposed nonlinear approach offers some important advantages such as quicker response, avoidance of hypoglycemia problems, etc. Robustness of the proposed approach is also demonstrated from a large number of simulations considering random initial conditions and parametric uncertainties.OPTIMAL BLOOD GLUCOSE REGULATION USING SNAC 197 levels as close to normal as possible leads to a substantial decrease in long-term complications of diabetes. A higher value as well as a lower value can lead to a serious illness in human beings. A higher blood sugar level leads to hyperglycemia, whereas a low blood sugar level results in hypoglycemia. Hyperglycemia in the long run can create problems such as stroke, cardiac arrest, blindness, etc. Hypoglycemia (less than 50 mg/dl of blood sugar concentration), on the other hand, has more serious consequence as it can rapidly lead to brain failure and hence death of the patient. The blood sugar concentration is normally controlled within these limits by different factors in the body. The most important regulators of the glucose level in the body are insulin and glucagon hormones that suppress and increase the blood sugar level, respectively. Insulin is anabolic and stimulates the glucose uptake capacity in tissues and thereby lowers the glucose level in the blood. Conversely, glucagon is catabolic. It stimulates the glucose production from fatty acids and amino acids when needed and results in increasing the blood sugar level. Different factors including food intake, rate of digestion, and exercise affect the glucose concentration in the blood.Diabetes mellitus is a disease in which blood glucose concentration is elevated because of deficient insulin secretion or abnormal insulin action. Diabetic patients require lifetime exogenous insulin injections to monitor the glucose concentration in blood within safe limits. Traditionally, man...

Energy harvesting is a promise to harvest unwanted vibrations from a host structure. Similarly, a dynamic vibration absorber is proved to be a very simple and effective vibration suppression device, with many practical implementations in civil and mechanical engineering. This paper analyzes the prospect of using a vibration absorber for possible energy harvesting. To achieve this goal, a vibration absorber is supplemented with a piezoelectric stack for both vibration confinement and energy harvesting. It is assumed that the original structure is sensitive to vibrations and that the absorber is the element where the vibration energy is confined, which in turn is harvested by means of a piezoelectric stack. The primary goal is to control the vibration of the host structure and the secondary goal is to harvest energy out of the dynamic vibration absorber at the same time. Approximate fixed-point theory is used to find a closed form expression for optimal frequency ratio of the vibration absorber. The changes in the optimal parameters of the vibration absorber due to the addition of the energy harvesting electrical circuit are derived. It is shown that with a proper choice of harvester parameters a broadband energy harvesting can be obtained combined with vibration reduction in the primary structure.

In this paper two nonlinear model based control algorithms have been developed to monitor the magnetorheological (MR) damper voltage. The main advantage of the proposed algorithms is that it is possible to directly monitor the voltage required to control the structural vibration considering the effect of the supplied and commanded voltage dynamics of the damper. The efficiency of the proposed techniques has been shown and compared taking an example of a base isolated three-storey building under a set of seismic excitations. Comparison of the performances with a fuzzy based intelligent control algorithm and a widely used clipped optimal strategy has also been shown.