dynamic modeling

Rehabilitation robots are very popular because they are beneficial tools in helping stroke patients and people with physical disabilities, so controlling them to get accurate performance is necessary. This paper presents a new super-twisting controller based on the determined gain with the TLBO algorithm (STA-TLBO) for an upper limb rehabilitation robot for the first time. One of the most important parts of designing the super twisting algorithm (STA) controller is determining the gains, which requires accurate calculations and obtaining disturbance. In this paper, the Teaching–Learning-Based Optimization (TLBO) algorithm is used to obtain the gains of the STA controller. To illustrate the validity of the proposed controller, the results are compared to PID, STA, and PID-TLBO controllers. The results indicate that the proposed controller ensures accurate tracking, finite-time convergence, and reduced chattering. The stability and the robustness of the PID-TLBO and STA-TLBO controllers are examined by three tests, parameter uncertainties, external disturbances, and step response. The results show that the STA-TLBO controller has a better performance than the others under different conditions; that means the proposed controller has a shorter convergence time, more accurate tracking, and fewer tracking error than the other three controllers.

The stone-carving robotic manipulators (SCRM) find a broad range of applications due to their high efficiency, wide range of processing and strong flexibility. However, the features of strong disturbance, uncertainty and variation in the parameters make the design of SCRM control systems more complicated. This paper introduced the inverse linear quadratic (ILQ) theory into the SCRM control system. First, we deduced the dynamic equation and state-space equation of the SCRM system with the Lagrange method. Then, the ILQ theory was used to achieve the desired closed-loop poles assignment of the system. To simplify the design process and meet the requirement of practical use, the state feedback optimal control law was determined by an improved ILQ design method. The proposed control scheme has the explicit capacity to achieve the desired joint angle and joint torque control performances, with fewer external disturbances and no sensitivity to changing model parameters. The effectiveness of the proposed control scheme compared with the traditional control strategies is shown in the simulation results. Thus, the vibration of the joint torque during the manufacturing process can be greatly reduced.

In this study, a real-time flexible modular modeling approach for the simulation of gas turbine engines dynamic behavior based on nonlinear thermodynamic and dynamic laws is addressed. The introduced model, which is developed in Matlab-Simulink environment, is an object-oriented high speed real-time computer model and is capable of simulating the dynamic behavior of a broad group of gas turbine engines due to its modular structure. Moreover, a Kalman filter-based model tuning procedure is applied to decrease the modeling errors. Modeling errors are defined as the mismatch between simulation results and available experimental data. This tuning procedure is an underdetermined estimation problem, where there are more tuning parameters than available measured data. Here, an innovative approach to produce a tuning parameter vector is introduced. This approach is based on seeking an optimal initial value for the Kalman filter tuning procedure. Three simulation studies are carried out in this paper to demonstrate the advantages, capabilities and performance of the proposed scheme. Furthermore, simulation results are compared with manufacturer’s published data, and with the experimental results gathered in either turbo-generator or turbo-compressor applications. Computational time requirement of the model is discussed at the end of the paper.

This paper presents a new modeling technique for fuel cell based switching converters. Often a step-up converter is used in the fuel cell applications due to its relative low voltage. Here a boost converter is used to convert the fuel cell voltage to the desired load level. The aim of this paper is to study through analysis and simulation, the voltage mode control and dynamic modeling of series interconnected topology of a fuel cell based system. Euler-Lagrange (EL) equation is used here as a modeling technique which relies on the energy balance equilibrium because fuel cell based systems can be considered as an energy processing structure. The fuel cell must be protected against the current harmonics or sudden transients so that it provides the regulated voltage for output load. We use a LC filter between fuel cell and converter to prevent the current harmonics from reaching the fuel cell since this may lead to oxygen starvation phenomena around the electrodes surface or other faults. The proposed modelling procedure is applicable for any other converter based on fuel cells. Finally, simulation is done by PSIM and MATLAB softwares to validate the proposed modeling technique. We run both the frequency and time domain analysis to show that the proposed modeling technique coincides exactly with the simulation results.

This work presents a new GA-Fuzzy method to model dynamic behavior of a process, based on Recurrent Fuzzy modeling through Mamdani approach whose inference system is optimized by Genetic Algorithms. By using the Mamdani approach, the proposed method surmounts the need to solve various types of mathematical equations governing the dynamic behavior of the process.
The proposed method consists of two steps; i) constructing a startup version of the model, ii) optimizing the shape of membership functions of the fuzzy sets corresponding to the variables exist in the fuzzy model, along with the production rules constituting the inference such that the obtained fuzzy model can predict the dynamic behavior of the process fairly accurately.
The proposed method is used to predict the dynamic behavior of the reaction section of the Tennessee Eastman (TE) benchmark. The overall accuracy of the obtained results compared to their corresponding counterparts in TE benchmark. The mean absolute percentage error (MAPE) of the key process variables which are temperature, pressure, and level of the reactor, and the reactor cooling water outlet temperature were calculated as 1.17%, 0.38%, 1.5%, and 1.57%, respectively, showing high prediction capability of the proposed method.

In this paper, a dynamical model-based SMC (Sliding Mode Control) is proposed for trajectory tracking of a 3-RPS (Revolute, Prismatic, Spherical) parallel manipulator. With ignoring small inertial effects of all legs and joints compared with those of the end-effector of 3-RPS, the dynamical model of the manipulator is developed based on Lagrange method. By removing the unknown Lagrange multipliers, the distribution matrix of control input vector disappears from the dynamical equations. Therefore, the calculation of the aforementioned matrix is not required for modeling the manipulator. It in trun results in decreased mathematical manipulation and low computational burden. As a robust nonlinear control technique, a SMC system is designed for the tracking of the 3-RPS manipulator. According to Lyapunov’s direct method, the asymptotic stability and the convergence of 3-RPS manipulator to the desired reference trajectories are proved. Based on computer simulations, the robust performance of the proposed SMC system is evaluated with respect to FL (feedback linearization) method. The proposed model and control algorithms can be extended to different kinds of holonomic and non-holonomic constrained parallel manipulators.

In this paper, integrated optimization of the guidance and control parameters of a dual spin flying vehicle is presented. The vehicle is composed of two parts: a free rolling aft body including the engine and the stabilizing fins and a roll isolated front body including all necessary guidance and control equipments such as onboard computer, control fins and an inertial navigation system. After developing the governing equations of motion, control loops and the guidance algorithm are constructed. Controllers are designed for two operating points and the guidance algorithm consists of a midcourse and a terminal phase. In midcourse phase, a virtual target, located on the nominal trajectory, is followed using proportional navigation law; while in the terminal phase, the vehicle is guided toward the real target. A new nonlinear saturation function is defined in order to saturate the maximum lateral acceleration command, as a function of dynamic pressure. Finally, the integrated tuning of 23 guidance and control parameters is formulated as an optimization problem. The optimization problem is solved using a metaheuristic algorithm, called tabu continuous ant colony system. The performance of the optimized guidance and control system is evaluated using Monte Carlo simulations, based on the complete nonlinear model.

Hysteresis motors are used in special applications such as gyroscope, centrifuge, and machine tool spindle drives due to their unique features such as synchronism, self-starting and developing smooth torque. Dynamic modeling of hysteresis motors is essential to predict of the transient performance, studying the dynamic stability and development of modern closed-loop control and estimation strategies. This paper develops a new dynamic modeling for a high-speed, circumferential-flux type hysteresis motor in synchronous dq reference frame. Major previous models use fixed parameters for rotor’s equivalent circuit parameters corresponding to the major B-H loop of rotor material, whereas operational B-H loop is significantly affected by stator voltage and load torque. In this paper, a time varying dynamic model is developed, in which the parameters of the equivalent circuit of hysteresis rotor material are adjusted based on operational B-H loop. For this purpose and based on elliptical assumption for B-H loops, the hysteresis lag angle β is updated due to the applied stator voltage and available load torque. Developed mathematical model satisfies many theoretical aspects of hysteresis motor behavior in transient and steady-state situations. The model offers a tool for studying the start-up of hysteresis motor, change of stator voltage, variation of load torque, frequency tracking for variable-speed applications and transient-state response to design parameters. Some simulations are provided to demonstrate the validity of developed model in Matlab/ Simulink environment and are verified via some experimental results. Proposed results verify the advantages of this model rather than previous works.