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U ovom se istraživanju predstavlja novi projekt samobalansirajućeg robota na dva kotača - two wheeled self-balancing robot (TWSR). Robot je nazvan two-wheeled self-balancing vehicle-pendulum system (TWSVPS). U usporedbi s TWSR, TWSVPS ima jedno klatno (single pendulum (SP)) koje je pasivno spojeno s tijelom robota preko O1 osovine. Teškoća i složenost upravljanja te modeliranje povećani su zbog dodatnog stupnja slobode - degree of freedom (DOF) s klatnom koje rotira oko osovine O1. Zbog jednostavnije analize, TWSVPS se može smatrati vozilom s pokretnim dvostruko obrnutim klatnom. Zbog svoje relativne jednostavnosti, za izvođenje dinamike sustava primijenjena je Lagrangeova dinamička formulacija. Paralelni dvostruki fuzzy upravljač zasnovan na informacijskoj tehnologiji fuzije projektiran je i simuliran u MATLAB-u. Rezultati pokazuju da je metoda izvediva i TWSVPS je izvanredno stabilan u kretanju. Novo razvijena konfiguracija je od velike važnosti u raznim primjenama uključujući samo-balansirajuće robote, kolica za bolesnike na dva kotača, analizu stabilnosti višezglobnih sustava itd., A novel design of the two-wheeled self-balancing robot (TWSR) was presented in this research. The robot was called two-wheeled self-balancing vehicle-pendulum system (TWSVPS). Compared with TWSR, the TWSVPS has a single pendulum (SP), which was passively jointed to the robot body through the O1 axis. The difficulty and complexity of control and modelling were increased due to the additional degree of freedom (DOF) which was offered by the SP rotated around the O1 axis. To simplify the analysis, the TWSVPS can be considered to be the mobile double inverted pendulum. Lagrangian dynamic formulation is used to derive the system dynamics due to its relative simplicity. The parallel double fuzzy controller based on information fusion technology was designed and simulated in MATLAB. The results show that the method is feasible and TWSVPS has excellent moving stability. The new developed configuration is of great importance in various applications including self-balance robots, wheelchairs on two wheels, stability analysis of multi links system etc.

We consider the design of an optimal collision-free sensor schedule for a number of sensors which monitor different linear dynamical systems correspondingly. At each time, only one of all the sensors can send its local estimate to the remote estimator. A preliminary work for the two-sensor scheduling case has been studied in the literature. The generalization into multiple-sensor scheduling case is shown to be nontrivial. We first find a necessary condition of the optimal solution provided that the spectral radii of any two system matrices are not equal, which can significantly reduce the feasible optimal solution space without loss of performance. By modelling a finite-state Markov decision process (MDP) problem, we can numerically search an asymptotic periodic schedule which is proven to be optimal. From a practical viewpoint, the computational complexity is formidable for some special system models, e.g., the spectral radii of some certain system matrices are far from others'. Some simple but effective suboptimal schedules for any systems are proposed. We also find a lower bound of the optimal cost, which enables us to quantify the performance gap between any suboptimal schedule and the optimal one.