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).

Dynamic Simulation of the Aircraft Environmental Control System

The dynamic research of aircraft environmental control system (ECS) is an important step in the advanced ECS design process. Based on the thermodynamics theory, mathematical models for the dynamic performance simulating of aircraft ECS were set up and an ECS simulation toolbox (ECS_1.0) was created with MATLAB language. It consists of main component modules (ducts, valves, heat exchangers, compressor, turbine, etc.). An aircraft environmental control system computer model was developed to assist engineers with the design and development of ECS dynamic optimization. An example simulating an existing ECS was given which shows the satisfactory effects.

Analysis of one dimensional and two dimensional fuzzy controllers

The analytical structures and the corresponding mathematical properties of the one dimensional and two dimensional fuzzy controllers are first investigated in detail. The nature of these two kinds of fuzzy controllers is next probed from the perspective of control engineering. For the one dimensional fuzzy controller, it is concluded that this controller is a combination of a saturation element and a nonlinear proportional controller, and the system that employs the one dimensional fuzzy controller is the combination of an open-loop control system and a closedloop control system. For the latter case, it is concluded that it is a hybrid controller, which comprises the saturation part, zero-output part, nonlinear derivative part, nonlinear proportional part, as well as nonlinear proportional-derivative part, and the two dimensional fuzzy controller-based control system is a loop-varying system with varying number of control loops.

Distributed Secondary Control and Optimal Power Sharing in Microgrids

We address the control problem of microgrids and present a fully distributed control system which consists of primary controller, secondary controller, and optimal active power sharing controller. Different from the existing control structure in microgrids, all these controllers are implemented as local controllers at each distributed generator. Thus, the requirement for a central controller is obviated. The performance analysis of the proposed control systems is provided, and the finite-time convergence properties for distributed secondary frequency and voltage controllers are achieved. Moreover, the distributed control system possesses the optimal active power sharing property. In the end, a microgrid test system is investigated to validate the effectiveness of the proposed control strategies. © 2014 Chinese Association of Automation.

Observer-based backstepping longitudinal control for carrier-based UAV with actuator faults

The paper presents the longitudinal control for the carrier-based unmanned aerial vehicle (UAV) system with unmeasured states, actuator faults, control input constraints, and external disturbances. By combining output state observer, adaptive fuzzy control, and constraint backstepping technology, a robust fault tolerant control approach is proposed. An output state observer with fuzzy logic systems is developed to estimate unmeasured states, and command filters rather than differentiations of virtual control law are used to solve the computational complexity problem in traditional backstepping. Additionally, a robust term is introduced to offset the fuzzy adaptive estimation error and external disturbance, and an appropriate fault controller structure with matching conditions obtained from fault compensation is proposed. Based on the Lyapunov theory, the designed control program is illustrated to guarantee that all the closed-loop signals of the given system are bounded, and the output errors converge to a small neighborhood of zero. A carrier-based UAV nonlinear longitudinal model is employed to testify the feasibility and validity of the control scheme. The simulation results show that all the controllers can perform at a satisfactory level of reference tracking despite the existence of unknown aerodynamic parameters and actuator faults. © 2017 Beijing Institute of Aerospace Information.

Neuro-Optimal Guidance Control for Lunar Soft Landing

Returning to moon has become a top topic recently. Many studies have shown that soft landing is a challenging problem in lunar exploration. The lunar soft landing in this paper begins from a 100 km circular lunar parking orbit. Once the landing area has been selected and it is time to deorbit for landing, a ΔV burn of 19.4 m/s is performed to establish a 100×15 km elliptical orbit. At perilune, the landing jets are ignited, and a propulsive landing is performed. A guidance and control scheme for lunar soft landing is proposed in the paper, which combines optimal theory with nonlinear neuro-control. Basically, an optimal nonlinear control law based on artificial neural network is presented, on the basis of the optimum trajectory from perilune to lunar surface in terms of Pontryagin's maximum principle according to the terminal boundary conditions and performance index. Therefore some optimal control laws can be carried out in the soft landing system due to the nonlinear mapping function of the neural network. The feasibility and validity of the control laws are verified in a simulation experiment.

Discrete Quasi-Sliding Mode Tracking Controller with Time Delay Technique

Robust discrete quasi-sliding mode tracking controller is developed with discrete reaching law for trajectory tracking in the presence of modeling uncertainty and unknown disturbance. The conventional prior knowledge of uncertainty upper bounds being replaced by an on-line estimation used in the controller to cancel the slowly varying uncertainties by the mechanism of time delay. This method reduces the feedback gain substantially and improves tracking accuracy. The system behavior in the vicinity of the sliding surface is examined for the existence and bandwidth of quasi-sliding mode. Simulation results show the effectiveness of the strategy.

On the Solutions of the Matrix Equations in Optimal Stochastic Control

In this paper, the matrix algebraic equations involved in the optimal control problem of time-invariant linear Ito stochastic systems, named Riccati- Ito equations in the paper, are investigated. The necessary and sufficient condition for the existence of positive definite solutions of the Riccati- Ito equations is obtained and an iterative solution to the Riccati- Ito equations is also given in the paper thus a complete solution to the basic problem of optimal control of time-invariant linear Ito stochastic systems is then obtained. An example is given at the end of the paper to illustrate the application of the result of the paper.

LMI-BASED AERO-ENGINE CONTROLLER DESIGN

The problem of analysis and synthesis of robust control is addressed in this work. The approach transferring the robust control design into Linear Matrix Inequality (LMI) is provided. The LMI standard structure of robust controller is also given and the controller is obtained through solving three LMIs. As an example, a robust control law is designed to the twin-spool turbojet engine system using the given approach. The result shows that LMI approach is feasible.

Dynamic Logic in Control

For the dynamic property in the control system, in this paper we advance dynamic logic to analyze and synthesize the control problems. This approach is similar to the way in which people always resolve such problems, and it can reflect the nature of the system. The dynamic logic combines the people's logic analysis with the dynamic property of the control system. On the basis of the dynamic logic qualitative model, the analyzing process and synthesizing process may go on. So there are many of the non-linear and logic factors which can be directly taken into consideration in the analyzing and designing process. The combination of the human intelligence and artificial intelligent techniques with the conventional methods of analysis and design, has provide an effective tool for the qualitative analysis and the qualitative design of the intelligent control system. We have successfully resolved the stabilizing problem of the inverted pendulum with dynamic logic.

Design of an Interpolated Controller for Stabilization of a Plant with Variable Operating Condition

In this paper, the stabilization of a linear SISO plant with variable operating condition is considered. The plant is described by a linear interpolation of proper stable co-prime factorizations of the transfer functions at two representative operating points. An interpolation of the stabilizing controllers for the representative models is designed to stabilize the plant, and the necessary and sufficient condition for the plant to be stabilized by the proposed controller is presented using the Nevanlinna-Pick interpolation theory. It is shown that the class of stabilization plants via the proposed controller in the paper is larger than that by the controller in reference. An example is also given to illustrate this fact.

The Study of Fuzzy Line Control for Multiple Intersections

The line control for multiple intersections is a hot spot in the area of transportation. According to the principle of system analysis and coordination, a method about fuzzy line control for multiple intersections is proposed. The system is made of two control units, one is the basic control unit for every single intersection, and the other is used for the function of coordination.

Importance of tip sensing for active control system of 30-m RIT primary mirror

The active control of 30-m ring interferometric telescope （RIT） needs edge sensing and tip sensing when its primary mirror is composed by trapezoid-shaped segments, and the imaging performance of the RIT is determined by the accuracy of these two detecting approaches. Considering the detecting accuracy available in current segmented telescope active control systems, the effect of these detecting approaches on the surface error of the RIT primary mirror is calculated from the point of error propagation. The corresponding effect on imaging performance （modulation transfer functions （MTFs） and point spread functions （PSFs） at several typical wavelengths） of the RIT primary mirror is also simulated. The results show that tip sensing is very important for increasing the active control quality of the RIT primary mirror under the present techniques.

Hopfield neural network-based image restoration with adaptive mixed-norm regularization

To overcome the shortcomings of traditional image restoration model and total variation image restoration model, we propose a novel Hopfield neural network-based image restoration algorithm with adaptive mixed-norm regularization. The new error function of image restoration combines the L2-norm and L1- norm regularization types. A method of calculating the adaptive scale control parameter is introduced. Experimental results demonstrate that the proposed algorithm is better than other algorithms with single norm regularization in the improvement of signal-to-noise ratio （ISNR） and vision effect.