Analysis and design of control system with equivalent-input-disturbance estimation

While linear covariance analysis is widely used for navigation system design and analysis, it is often overlooked as a tool for closed-loop guidance navigation and control (GN&C) system design and analysis. This article presents an overview of the techniques and methods required to develop a linear covariance analysis tool for a close-loop GN&C system. Then, using a simple nonlinear closed-loop GN&C problem as a guide, the capabilities of linear covariance analysis for the design and analysis of closed-loop systems are demonstrated. It is shown that linear covariance can be accurately applied to a closed-loop system with time-to-go guidance, dead-reckoning navigation, and a Kalman filter for state estimation. The accuracy and efficiency of linear covariance analysis is shown by direct comparison to Monte Carlo analysis results, and the value of linear covariance analysis is highlighted by presenting several analysis capabilities that are often required in the design and analysis of closed-loop GN&C systems. It is also shown how the efficiency of linear covariance enables new design methodologies, one of which is presented in this article, that would otherwise be prohibitive with Monte Carlo analysis.

We review practical case studies of a developing method of highly reliable real-time embedded control systems using a CPU model-based hardware/software co-simulation. We take an approach that enables us to fully simulate a virtual mechanical control system including a mechatronics plant, microcontroller hardware, and object code level software. This full virtual system approach simulates control system behavior, especially that of the microcontroller hardware and software. It enables design space exploration of microarchitecture, control design validation, robustness evaluation of the system, software optimization before components design. It also avoids potential problems. The advantage of this work is that it comprises all the components in a typical control system, enabling the designers to analyze effects from different domains, for example mechanical analysis of behavior due to differences in controller microarchitecture. To further improve system design, evaluation and analysis, we implemented an integrated behavior analyzer in the development environment. This analyzer can graphically display the processor behavior during the simulation without affecting simulation results such as task level CPU load, interrupt statistics, and the software variable transition chart. It also provides useful information on the system behavior. This virtual system analysis does not require software modification, does not change the control timing, and does not require any processing power from the target microcontroller. Therefore this method is suitable for real-time embedded control system design, in particular automotive control system design that requires a high level of reliability, robustness, quality, and safety. In this study, a Renesas SH-2A microcontroller model was developed on a CoMET™platform from VaST Systems Technology. An electronic throttle control (ETC) system and an engine control system were chosen to prove this concept. The electronic throttle body (ETB) model on the Saber® simulator from Synopsys® and the engine model on MATLAB®/Simulink®simulator from MathWorks can be simulated with the SH-2A model using a newly developed co-simulation interface between MATLAB®/Simulink® and CoMET™. Though the SH-2A chip was being developed as the project was being executed, we were able to complete the OSEK OS development, control software design, and verification of the entire system using the virtual environment. After releasing a working sample chip in a later stage of the project, we found that such software could run on both actual ETC system and engine control system without critical problem. This demonstrates that our models and simulation environment are sufficiently credible and trustworthy.

The increasing complexity associated with many modern engineering applications, including autonomous robot guidance and navigation, process control in sensor-rich environments, and control of biological systems, has far-reaching implications for control system design. As an example, reactive, embedded software systems, interacting among themselves and remote users over communication networks, introduce a whole new set of system-level challenges, and classic control design objectives such as stability, performance, and robustness are being complemented with a number of new questions. These include the cost of hardware implementation, measured for example not only by computational requirements such as speed and memory, but also by communication requirements such as available communication bandwidth. Moreover, the complexity associated with specifying the control procedures and with verifying the behavior of the closed-loop system increasingly plays a fundamental role, especially in safety-critical control systems arising in energy and transportation networks, and in medical applications.

COMPUTER AIDED INSTRUCTION SYSTEM WITH AN INVERTED PENDULUM EQUIPMENT

At the University of Nevada, Reno, we strongly believe that effective control system education must include experimental exercises that complement the theory presented in lectures. Preferably, the exercises should include the design and implementation of a control system. Limited resources and a cap on the number of credit hours required for the undergraduate degree make it impossible to offer a laboratory course with every control class in most electrical engineering curricula. We have solved this problem by including a laboratory project in each of our two senior electives. Each project is a comprehensive modeling, analysis, design and implementation of a physical control system. The students are divided into groups and each group must independently complete the design project and submit a formal report summarizing their results and experiences. Each student must submit an individual commentary on the exercise and the experimental results obtained. Student feedback indicates an increased appreciation of the lecture material and an awareness of the limitations of the theory and simulation that was lacking prior to the introduction of laboratory exercises.

The INteractive Controls Analysis (INCA) program was developed at the Goddard Space Flight Center to provide a user friendly efficient environment for the design and analysis of linear control systems. Since its inception, INCA has found extensive use in the design, development, and analysis of control systems for spacecraft, instruments, robotics, and pointing systems. Moreover, the results of the analytic tools imbedded in INCA have been flight proven with at least three currently orbiting spacecraft. This paper describes the INCA program and illustrates, using a flight proven example, how the package can perform complex design analyses with relative ease.

The problem encountered while developing the RKX-200TJ/booster is the measurement of mass vehicle (center of gravity). The thrust line of the rocket booster does not coincide with the center of gravity can induce a pitch disturbance. By controlling the pitch parameter, the pitch disturbance phenomenon can be minimized. In this paper is presented the flight performance and dynamics analysis and the design of pitch and roll control system for RKX200TJ/booster during rocket booster and climb phase. The result indicates that the pitch disturbance can be reduced until decrease about 27% whereas roll angle ( ) can be damped at zero level ( ). Pitch angle ( ) can be maintained at angle 5° for climb phase. Although the one of moment arm case shows the static instability and uncontrollability during rocket booster phase, the control system can control vehicle the further phase. This simulation presented in X-Plane and Simulink. The PID controller is selected in control system design.

The paper presents novel tools for model-based control system design based on FMI/FMU standard (Functional Mock-up Interface / Unit). It is focused on application of FMI standard for easy integration of control system development cycle starting with Model-in-the-Loop (MIL) simulation and finishing with Hardware-in-the-Loop (HIL) simulation. It is shown, how the Functional Mock-up Units (FMU) containing dynamic differential-algebraic equations of various parts of the device (mechanical, electrical, hydraulic, thermal, etc.) can be easily deployed to unified simulation environment where the control system is designed, consequently. The procedure allows to combine inputs from various Modelica-based tools at the process model side, utilizing power of Matlab/Simulink for design, analysis and optimization of control system and perform final test via HIL scenario where both the model and control system are simulated in real-time on separated HW units. The pros and cons of both FMI concepts, i.e. Co-Simulation and Model Exchange are discussed in detail. The whole procedure is demonstrated on a steam turbine example combining component-based and equation based modeling. Both the turbine model and the full control loop are validated in all phases of control system development. It is shown, that monolithic simulation block with proprietary solver reduces computational burden compared to automatic FMU concept.

A digital closed-loop control system with all digital phase locked loop (ADPLL) is designed and optimized, in order to improve the bias stability and transient response of the gyroscope. The nonlinear mathematical models for the closed-loop amplitude and phase control system are established. The linearization method is applied to analyze the nonlinear models. The control parameters of the drive loop are optimized. The experimental results show that the phase deviation between the demodulation reference signal of the drive loop and the sense signal is less than 0.25° in the temperature range from-40°C to 60°C, within 0.15° of the variation. At room temperature, the overshoot amount of the gyroscope control system is 4.5% with setting time of 0.12s. The bias stability is 1.45°h. Compared to the analog control scheme, the digital control system has advantages of short setting time, small overshoot, short phase locked time, large locked range, high phase precision, etc.

Model-based development (MBD), which utilizes system models to design complex products, has received increasing attention. However, an advanced control system design scheme is required to accurately control the developed products under harsh conditions for practical usage. This paper proposes a control system that integrates a data-driven compensator (DDC) with a model-based control (MBC) system design. The proposed method considers a hierarchical control structure comprising an upstream control system based on the MBC design approach and a downstream control system that includes a plant control loop with a DDC. The proposed system can always maintain the desired performance by driving the MBC based on an ideal model because the downstream control system, DDC, maintains the characteristics of the ideal model even if the plant properties change owing to changes in operational and/or environmental conditions. In this study, the design scheme for unifying models and data in the MBD process is called smart MBD (S-MBD), and the proposed control system design scheme is based on the S-MBD approach. The effectiveness of the proposed hierarchical control system is verified by applying it to a hydraulic excavator.

The present work exposes the analysis and design of the Equipment Loan Control System (SCPE). We developed a system in its analysis and design phases of control of equipment inputs and outputs (loans), reducing time and showing reports to be able to make decisions about a subsequent acquisition of equipment or different administration. The functionality of the system is based on the procedure P-EDU-05 http://sgi.utvtol.org.mx/ mainly on the points: 8.2 (update of the equipment inventory) 8.4 (Delivery of laboratory hours) 8.5 (Verification of the laboratory schedule) 8.7 Registration of PTC/PA (Full Time Professor/Subject Professor) in a later version using a fingerprint reader. In this delivery, procedures, processes and calculations will be analyzed; as well as define interfaces. In point 8.7, it will register compliance of the service at the end of the practice. It will also include a processing, calculating the compliance rates according to the procedure. The laboratory/equipment registration interface will reflect what is required in the R-EDU-20-General requirements for laboratory/workshop practices. Finally, the RAD (Rapid Application Development) methodology will be used to develop the system due to the use of fourth generation techniques to reuse existing programs.

This paper addresses the command tracking control system (CTCS) design problem for plants involving input quantization and input saturation. A novel approach is proposed and demonstrated to the angle of attack (AOA) CTCS and bank angle CTCS of hypersonic reentry vehicles (HRV) driven by a reaction control system (RCS). First, the six-degree-of-freedom (6-DOF) nonlinear dynamic model of HRV and the mathematical model of RCS are established, and dynamic analysis is conducted based on the linearized model of HRV. Second, a general CTCS for plants involving input quantization and saturation is designed by solving a convex optimization problem based on linear matrix inequalities (LMIs). Formulations of the domains of attraction and convergence of the closed loop CTCS are derived. Furthermore, input to state stability (ISS) of the closed loop system is analyzed. Finally, the proposed approach is applied to design the longitudinal AOA CTCS and lateral–directional bank angle CTCS of HRV driven by an RCS. ...

We study the evolution law of information measure in the stochastic control system. For linear Gaussian systems, we derive the exact evolution formulas for the entropy, mutual information, divergence, and the components dependent degree (CDD) of the state vectors. A simple example is used to illustrate how the feedback will influence the information evolutions. The view of information evolution seems very useful in the analysis and design of control system.

CAD FOR EDUCATION OF DIGITAL CONTROL SYSTEMS

Recently there has been an increasing interest in the application of computer algebra to control system analysis and design. Control system design is to find out feasible parameters to be designed for which a target system satisfies given control design specifications. Many important control system design problems are regarded as parametric and non-convex optimization problems. We have been developing a MATLAB toolbox for robust control via a parameter space approach based on symbolic-numeric computation. First we explain how we can practically solve such control system design problems by using algebraic methods, quantifier elimination. Then we show an effective visualization of the results i.e. the feasible regions of design parameters in a parameter space. All these results are implemented as the MATLAB toolbox for parametric robust control. We also demonstrate our MATLAB toolbox by using actual control design problems