Research on Self-balancing Two Wheels Mobile Robot Control System Analysis

The paper presents the research on self-balancing two-wheels mobile robot control system analysis with experimental studies.The research problem in this work is to stabilize the mobile robot with self-control and to carry the sensitive things without failing in a long span period.The main objective of this study is to focus on the mathematical modelling of mobile robot from laboratory scale to real world applications.The numerical expression with mathematical modelling is very important to control the mobile robot system with linearization.The fundamental concepts of dynamic system stability were utilized for maintaining the stability of the constructed mobile robot system.The controller design is also important for checking the stability and the appropriate controller design is proportional,integral,and derivative-PID controller and Linear Quadratic Regulator(LQR).The steady state error could be reduced by using such kind of PID controller.The simulation of numerical expression on mathematical modeling was conducted in MATLAB environments.The confirmation results from the simulation techniques were applied to construct the hardware design of mobile robot system for practical study.The results from simulation approaches and experimental approaches are matched in various kinds of analyses.The constructed mobile robot system was designed and analyzed in the control system design laboratory of Yangon Technological University(YTU).

Dynamical system analysis of Dirac-Born-Infeld scalar field cosmology in coincident f(Q)gravity

In this article,we present a dynamical system analysis of a Dirac-Born-Infeld scalar field in a modified f(Q)gravity context.We considered a polynomial form of modified gravity,used two different types of scalar potential,polynomial and exponential,and found a closed autonomous dynamical system of equations.We analyzed the fixed points of such a system and evaluated the conditions under which deceleration to late-time acceleration occurs in this model.We note the similarity of the two models and show that our result is consistent with a previous study on Einstein s gravity.We also investigated the phenomenological implications of our models by plotting EoS(ω),energy density(Ω),and deceleration parameter(q)w.r.t.to e-fold time and comparing to the present value.We conclude the paper by observing how the dynamical system analysis differs in the modified f(Q)gravity,and present the future scope of our research.

Convergence analysis of self-tuning Riccati equation for systems with correlation noises

For linear discrete time-invariant stochastic system with correlated noises,and with unknown state transition matrix and unknown noise statistics,substituting the online consistent estimators of the state transition matrix and noise statistics into steady-state optimal Riccati equation,a new self-tuning Riccati equation is presented.A dynamic variance error system analysis(DVESA)method is presented,which transforms the convergence problem of self-tuning Riccati equation into the stability problem of a time-varying Lyapunov equation.Two decision criterions of the stability for the Lyapunov equation are presented.Using the DVESA method and Kalman filtering stability theory,it proves that with probability 1,the solution of self-tuning Riccati equation converges to the solution of the steady-state optimal Riccati equation or time-varying optimal Riccati equation.The proposed method can be applied to design a new selftuning information fusion Kalman filter and will provide the theoretical basis for solving the convergence problem of self-tuning filters.A numerical simulation example shows the effectiveness of the proposed method.