Analysis and design of motion control systems with positive force/torque feedback using robust control methods

A novel 5-Degree of Freedom PCMM (parallel coordinate measuring machine) was proposed, and its motion control system was designed. Compared with the other structural PCMMs, the structure feature of proposed PCMM was described. Then its motion control system was designed with the modularized and open architecture. The controlled scheme of hardware, which based on PC, PMAC motion control card and the precision measuring probe, was developed. The software of the motion control system was written by Visual Basic6.0 language. Finally, the process of motion control for 4-UPS-UPU PCMM was proposed. The new method above for design of motion control system is simple and effective, and may be applied to other parallel machine.

Robust Adaptive Control

The object of this work is to present computer programs, written using Turbo Pascal version 5.5, which can be utilized for the analysis and design of control systems as required for undergraduate courses. The programs have been designed so that the student uses the computer as a tool for reducing computational drudgery and not as a substitute for engineering analysis. The software, which can be used on an IBM Personal Computer and compatibles, will be made freely available to interested educators. >

A survey is presented of the environment, the hardware, and the system, user interface, and applications software that can make engineering workstations effective tools for the analysis and design of control systems. The hardware discussion covers processors, memory, networks, and diskless workstations. Operating systems, distributed file systems, and software for developing user interfaces are highlighted, along with the most widely used applications packages for control system engineering.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Stability is one of the most important concepts of analysis and design of control systems. Stability analysis of fuzzy control systems has been difficult since fuzzy systems are essentially nonlinear systems. Recently, stability analysis techniques [l]-[6] [13]-[16] based on nonlinear stability theory have been reported. Langari and Tomizuka [2, 6] analyzed stability of fuzzy linguistic control systems. Kitamura [3] realized stability analysis of fuzzy control systems by using extended circle criterion. Farinwata [5] and Kato [14] utilized phase plane analysis type of techniques, tanaka and co-authors [1,3,4] applied Lyapunov approach to fuzzy control systems and recently developed LMI-based designs [10, 17, 28-37], where LMI stands for nonlinear matrix inequality.

This paper presents a comprehensive treatment of the complex motion control systems in the Sliding Mode Control (SMC) framework. The single and multi degrees of freedom (DOF) plants and applications to haptics and functionally related systems are discussed. The proposed algorithms are based on the application of the equivalent control observer and the convergence term that guaranty stability of the closed loop in a Lyapunov sense and enforces the sliding mode on selected manifolds. Presented SMC design leads to a solution that easily could be modified to include majority of the algorithms presented in the literature.

An intelligent motion control system design concept is proposed. The design is intelligent in that the designed system can adapt itself to operational, system itself and/or environmental variations. The key concept is to link system gain tuning with the variations explicitly and quantitatively. The effectiveness of the system is verified by an existing experiment.

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&amp;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&amp;C system. Then, using a simple nonlinear closed-loop GN&amp;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&amp;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.

In this second part of the paper on the analysis and design of uncertain fuzzy control systems, we present a controller design method for a class of uncertain fuzzy control systems. This class of systems can be represented by the discrete-time uncertain fuzzy models discussed in Part I. Since this model representation considers system uncertainties and system disturbance, the controller design problem for this kind of model becomes a H/sub /spl infin// control problem for a nonlinear uncertain system. A new stability analysis and control system design approach are then developed for this kind of uncertain fuzzy model. Furthermore, a constructive algorithm is developed to obtain the H/sub /spl infin// feedback control law.

Network-based control systems have been emerging technologies in control and computer communication fields over the past decade. This paper focuses on the analysis and design of network-based control systems with binary modulation. First, it is shown that different modulations can result in different delays which are inevitable in network-based control systems. The delay can be seen as constant delay when the transmission time is the main consideration. Second, channel noise can result in bit error while bit error is seen as active packet loss in this paper, in this context, the conditions of signal-to-noise ratio (SNR) for binary modulation that can guarantee the stability of systems are obtained according to the proposed algorithm. Third, the system with delay and noisy communication can be modeled as an asynchronous dynamic system (ADS); in addition, the stability is analyzed and controller is designed in terms of Lyapunov function and linear matrix inequality (LMI) scheme. Finally, without loss of generality, numerical simulation demonstrates the effectiveness of the proposed scheme and designed controller based on binary amplitude shift keying (2ASK) modulation.

To help along the analysis and design of nonlinear control systems the NONLINCON package, an acronym for nonlinear control, was developed. This note addresses the usefulness of symbolic computation, and of the NONLINCON package in particular, for the symbolic analysis and design of nonlinear control systems. The symbolic computation program MAPLE is used as computing substratum. Textbook problems show that the NONLINCON package can be used successfully. A larger scale problem is too complex, however, to be solved with the current versions of NONLINCON and MAPLE. The conclusion is that symbolic computation is a viable approach for textbook problems, but not yet for more complex ones. >

Design, Analysis and Real-time Implementation of Networked Predictive Control Systems

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.

Design and Analysis of Robust Control Systems in PARADISE

The paper presents a method of engineering analysis and design for complex control systems, the time-domain infinite-matrix method. The formulation of the infinite matrix follows from the convolution summation of sampled-data systems. The mathematical basis of the time-domain matrix formulation is related to the applicable concepts of infinite matrices and sequence spaces. The method is applicable to both continuous-data and sampled-data systems. For continuous systems it is necessary to introduce a fictitious sampler and `hold? of sufficient sampling rate to effect an accurate approximation. The time-domain-matrix method is presented and illustrated as a method of analysis and design of linear, non-linear, and time-varying systems of the continuous-data or sampled-data class. The investigation of non-linear systems is greatly simplified by the time-domain approach. Multi-loop systems may be investigated, and the signals at intermediate points throughout the loops are readily available. Also, systems with multiple non-linearities may be investigated. Two methods of design of a discrete compensator for a sampled-data system are presented. These methods are accomplished directly in the time domain and allow for a compromise of specifications in the time domain. In one design procedure the response between sampling instants is also accounted for. The time-domain-matrix method may be readily programmed on a digital computer, and therefore provides a rapid analysis and design technique.