This paper presents a new observer design technique for Lipschitz nonlinear systems. Necessary and sufficient conditions for existence of a stable observer gain are developed using a S-Procedure Lemma. The developed condition is expressed in terms of the existence of a solution to an Algebraic Riccati Equation in one variable. Thus, the need to solve Linear Matrix Inequalities in multiple variables is eliminated. The advantage of the developed approach is that it is significantly less conservative than other previously published results for Lipschitz systems. It yields a stable observer for larger Lipschitz constants than other techniques previously published in literature.

Accurate detection of the danger of an impending rollover is necessary in order to effectively use active vehicle rollover prevention. A real-time rollover index is an indicator used for this purpose. A traditional rollover index utilizes lateral acceleration measurements and can detect only untripped rollovers that happen due to high lateral acceleration from a sharp turn. It fails to detect tripped rollovers that happen due to tripping from external inputs such as forces when a vehicle strikes a curb or a road bump. Therefore, this paper develops a new rollover index that can detect both tripped and untripped rollovers. The new rollover index utilizes vertical accelerometers in addition to a lateral accelerometer and is able to predict rollover in spite of unknown external inputs acting on the system. The accuracy of the developed rollover index is evaluated through simulations with industry-standard software CARSIM and experimental tests on a one-eighth-scaled vehicle. In order to show that the scaled vehicle experiments can represent a full-sized vehicle, the Buckingham π theorem is used to show dynamic similarity. The simulation and experimental results show that the new rollover index can reliably detect both tripped and untripped rollovers.

Accurate detection of the danger of an impending rollover is necessary for active vehicle rollover prevention systems. A real-time rollover index is an indicator used for this purpose. A traditional rollover index detects only untripped rollovers that happen due to high lateral acceleration from a sharp turn. It fails to detect tripped rollovers that happen due to tripping from external inputs such as forces when a vehicle strikes a curb or a road bump. Therefore, this paper develops a novel new rollover index that can detect both tripped and untripped rollovers. A methodology is developed for estimation of unknown inputs in a class of nonlinear systems. The methodology is based on the nonlinear observer design and dynamic model inversion to compute the unknown inputs from output measurements. The observer design utilizes the mean value theorem to express the nonlinear estimation error dynamics as a convex combination of known matrices with time-varying coefficients. The observer gains are then obtained by solving linear matrix inequalities. The developed approach can enable observer design for a large class of differentiable nonlinear systems with a globally (or locally) bounded Jacobian. The developed nonlinear observer is then applied for rollover index estimation. The developed rollover index is also evaluated through simulations with an industry standard software, CARSIM, and with experimental tests on a 1/8th scaled vehicle. In order to verify that the scaled vehicle experiments can represent a full-sized vehicle, the Buckingham π theorem is used to show dynamic similarity. The simulation and experimental results show that the developed nonlinear observer can reliably estimate vehicle states, unknown normal tire forces, and rollover index for predicting both untripped and tripped rollovers.

Alternative energy generated from people’s footsteps in a crowded area is sufficient to power smart electronic devices with low consumption. This paper aims to present the development of an energy harvesting floor—called Genpath—using a rotational electromagnetic (EM) technique to generate electricity from human footsteps. The dynamic models of the electro-mechanical systems were developed using MATLAB^®/Simulink to predict the energy performances of Genpath and help fine-tune the design parameters. The system in Genpath comprises two main parts: the EM generator and the Power Management and Storage (PMS) circuit. For the EM generator, the conversion mechanism for linear translation to rotation was designed by using the rack-pinion and lead-screw mechanism. Based on the simulation analysis, the averaged energy of the lead-screw model is greater than that of the rack-pinion model. Thus, prototype-II of Genpath with 12-V-DC generator, lead-screw mechanism was recently built. It shows better performance when compared to the previous prototype-I of Genpath with 24-V-DC-generator, rack-pinion mechanism. Both prototypes have an allowable displacement of 15 mm. The Genpath prototype-II produces an average energy of up to 702 mJ (or average power of 520 mW) per footstep. The energy provided by Genpath prototype-II is increased by approximately 184% when compared to that of the prototype-I. The efficiency of the EM-generator system is ~26% based on the 2-W power generation from the heel strike of a human’s walk in one step. Then, the PMS circuit was developed to harvest energy into the batteries and to supply the other part to specific loads. The experiment showed that the designed PMS circuit has the overall efficiency of 74.72%. The benefit of the design system is for a lot of applications, such as a wireless sensor and Internet of Thing applications.