China
Africa
Explore chapters and articles related to this topic
Computer-Controlled Systems
Published in Jitendra R. Raol, Ramakalyan Ayyagari, Control Systems, 2020
Jitendra R. Raol, Ramakalyan Ayyagari
Different parts of an ECS can be developed separately, provided that the overall model is competent for testing, the development design process is concurrent engineering activity, Figure 12.3. The design trajectory of ECS is: (i) the dynamic behavior of the system is object–oriented-ly modeled, using bond graphs as a main modeling paradigm; (ii) using the model, the control laws are designed; (iii) ECS implementation is done by transforming the control laws to efficient concurrent algorithms (i.e. computer code) via a stepwise refinement process, after each step, the results are verified by simulation; and (iv) realisation of the ECS is done on a stepwise sequence. The stepwise refinement procedure for the embedded SW consists of: (i) control laws only, for the ideal situation; (ii) non-ideal components are modeled more precisely by considering their relevant dynamic effects; (iii) safety, and command interfacing, reaction to external commands (from the operator/connected systems) is specified; and (iv) effects due to non-idealness of computer HW/SW are added, and effects of computational latency and accuracy are checked. The impact of scheduling and/or algorithm optimisation techniques on the behavior of the ECS can be checked by extensive simulations. A top–down decomposition may be applied: (i) define the global architecture of the system, (ii) those control algorithms in which problems are expected may be developed, and (iii) the parts of the controller can be developed incrementally and combined to obtain the description of the total controller. In the realization step, simulation plays a relevant role when the design project is implemented in a concurrent engineering fashion: the available part of an ECS is tested together with the other parts that are still the simulated models; the verification process is a hardware-in-the-loop simulation (HILS).
Formalized Approach for the Design of Real-Time Distributed Computer Systems
Published in Katalin Popovici, Pieter J. Mosterman, Real-Time Simulation Technologies, 2017
Ming Zhang, Bernard Zeigler, Xiaolin Hu
Hardware-in-the-loop simulation, in which the environment model is simulated by a DEVS real-time simulator on one computer, whereas the control model under test is executed by a DEVS real-time execution engine on the real hardware.
Set-based fast gradient projection algorithm for model predictive control of grid-tied power converters
Published in Automatika, 2023
Renato Babojelić, Bruno Vilić Belina, Šandor Ileš, Jadranko Matuško
This paper presents a set-based fast gradient approach to control of grid-tied power converters with an LCL filter and proposes an efficient implementation of a set-based MPC algorithm using the modified fast gradient projection method for solving the optimization problem. The need for use of the Dual FGM to handle state constraints in the optimization problem is here circumvented by transforming the state constraints to input constraints using invariant sets theory; as the input constraints are ellipsoidal sets they allow for an efficient projection operation in the FGM. The proposed control approach, which is based on a sequence of one-step control invariant sets, also provides an explicit guarantee of closed-loop stability without introducing the additional conservatism found in MPC controllers with guaranteed stability. Furthermore, by extending this approach to linear parameter varying (LPV) systems, the MPC algorithm is made robust to the uncertainties in the variation of the grid inductance. The proposed approach was tested in hardware-in-the-loop simulation.
Flexible modelling and altitude control for powered parafoil system based on active disturbance rejection control
Published in International Journal of Systems Science, 2019
Hao Sun, Qinglin Sun, Wannan Wu, Shuzhen Luo, Jin Tao
In this paper, it is focused on the accurate altitude control of the powered parafoil system. It exists three main features: the flexible modelling method based on CFD, the control method based on ADRC and the flight experiment. Firstly, a novel flexible modelling method of the powered parafoil system based on CFD is presented. With this method, the aerodynamic model can accurately simulate the flight state of the system, including the wind influence and the flap deflection. It is of great help to the tuning of the controller parameters. After that, a double close-loop controller is designed for the altitude control based on ADRC. This controller structure not only has better reaction speed and stability, but also shows a huge improvement on the control effect. By the above methodology, the hardware-in-the-loop simulation is achieved under the windy environment previously. It mainly focuses on the executive condition of the actuator and proves the reliability of the system. At last, the actual flight experiment results present the validity and the correctness of the proposed modelling and control methodology. It also proves that the proposed method can provide effective guidance to the actual flight experiment of the parafoil delivery system.
Normal contact stiffness identification-based force compensation for a hardware-in-the-loop docking simulator
Published in Advanced Robotics, 2018
Qian Wang, Chenkun Qi, Feng Gao, Xianchao Zhao, Anye Ren, Yan Hu
To ensure the safety and reliability of the docking, thorough ground verification is necessary. The key point of ground verification for space docking is how to provide micro-gravity conditions. There are basically three kinds of options: pure hardware simulation, pure numerical simulation and hardware-in-the-loop simulation. Several commonly used pure hardware simulation methods are developed. Air-bearing tables allows the device to operate in plane; neutral buoyancy makes the 6-DOF experiment possible but suffers from drag force issue; parabolic flight and free fall methods use airplanes to fly in a parabolic trajectory or to do a free falling during the experiment, it can offer micro gravity environment, but the time is very short and the cabin space is limited; balancing mechanism is another option, it passively generates mechanical counter force against the gravity to reach a static balance, and the main drawback of this method is that it alters the multi-DOF dynamic behavior of the tested device [2,3]. In a pure numerical simulation, the motion of the spacecraft in micro-gravity conditions and the contact process are both emulated by software. Several influential contact dynamics models [4–6] has been established, and this is still a popular research topic. However, none of the available contact dynamics models are accurate enough yet, thus the verifications cannot only rely on pure numerical simulation.