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The combination of Java applications as graphical user interfaces and the Matlab-Simulink environment as the simulation engine seems to be a good solution for taking a particular control lab to distant students. In this paper, it is presented a new kind of simulation environment for qualitative teaching on concepts of Control Engineering by means of a suitable configuration of experiments by the tutor or teacher.

Active power filter (APF) is one of the most important measures to deal with the power quality problem. Mathematically, APF model in a power grid is typical nonlinear. Since the passivity-based control is a powerful tool to study the stabilization of nonlinear system, it could be applied in current tracking controller design of APF. In this paper, the state space model of an n-phase APF is established first. Then, this model is applied to design a controller for current tracking from the viewpoint of passivity. Subsequently, the sufficient conditions to achieve gradual tracking and to keep the internal stability of the APF control system are given. Simulation results performed with PSCAD verify the validity of the approach.

This paper addresses stability and control issues of systems with uncertain and time-varying sampling period and time-delay. These arise e.g. in embedded or networked control applications where limited computation or communication resources have to be scheduled. The uncertain and time-varying sampling period and time delay are transformed into polytopic and additive norm-bounded uncertainties in the discretized system description. Control design and stability analysis methods are given in the form of LMIs applying switched parameter-dependent quadratic Lyapunov functions. A reduction algorithm is proposed in order to decrease the amount of LMIs necessary for stability analysis. The control design and stability analysis methods as well as the reduction algorithm are illustrated by an example.

The problem of real-time reliability analysis and prediction is considered in this paper based on degradation measurements. Given the nonlinear degradation path model with random parameters, the prior distribution of the random parameters is updated into a posterior distribution according to Bayesian formula based on the measurable degradation information. Then, the reliability during a certain period in the future can be predicted by Monte Carlo integration. An example by use of the fatigue crack growth data is given for illustration.

This paper is concerned with the output feedback stabilization problem of networked control systems (NCSs) with random communication delays. Mean-square stability is derived for the closed-loop NCSs. Based on this, the one-mode-dependent output feedback controller is designed, and the explicit expressions of the controller gains are obtained in terms of linear matrix inequalities (LMIs). A numerical example is provided to show the effectiveness and applicability of the proposed results.

This paper presents methods to analyze two-dimensional (2D) sheet variations obtained from a non-scanning full-sheet measuring system for control and diagnostics applications. A functional decomposition scheme is applied to extract and classify sheet variations in two dimensions. The 2D sheet variations are decomposed into controllable, diagnostic, and unclassifiable variation patterns. The disturbances that cause sheet variations can be identified with the separated patterns. The separated patterns give sheet-makers a new visibility to pinpoint the process problems and to improve sheet uniformity.

This paper presents a control algorithm that reduces the vibrations of a human-riding biped robot, HUBO FX-1 during walking. This kind of robot should handle the payload of at least 100 kg in order to carry a person easily. To secure a sufficient payload, it is important to reduce the weight of the robot. The weight of the robot is mainly composed of motors, reduction gears, and body frames. Reducing the weight of the body frame is more efficient use of power than reducing the capacities of motors and reduction gears. A disadvantage is that the leg structures become flexible, so serious structural vibrations are generated during walking. We solved this problem by using simple theoretical models and experiments based on sensory feedback. This control strategy is very effective for the weight reduction of biped robots.

The high penetration of renewable generation raises great concerns in grid operation on whether system will have sufficient flexibility for balancing the intermittent variation of renewable generation. With the development of smart grid, technologies like demand response, distribution generation, electric vehicle and energy storage become more popular. It is foreseen that with the increasing participation of these flexible load resources and high penetration of renewable generation, the system operations of the future interconnected power grid will become more complicated. This paper discusses the system operational challenges, analyzes the potentials of load flexibility, then proposes a multi-agent system control framework to support the interactive operations of “Source-Grid-Load”. An interactive leading control process is introduced to lead the flexible resources ramping with a sequence of advisory dispatches, reduce the balancing needs from the frequency control generators.

In this paper, an experimental vehicle with an active suspension system is regarded as a control object. First, a full-vehicle model representing this experimental vehicle was derived, then a control system was designed for this model using the H∞ control theory. The main purpose of this control system is to achieve robust performance. This control theory has been implemented in an experimental vehicle, and evaluated for robust performance in a four-wheel shaker and during actual driving. It has been confirmed that the desired robust performance is achieved in this closed-loop system.

This paper presents a speed planning method for mobile robots. The method is applied to a planned path and produces a speed profile which will be used for path execution. This goal is achieved by applying to stages: speed planning and speed profile generation. The first step computes a set of control speed points according to speed limitations of the vehicle, obtained from its kinematic and dynamic behaviour. Moreover, this stage considers the movile obstacles avoidance, which is included as a vehicle's motion constraint. The second step uses the information provided by the previous step to build a smooth speed profile.

In this paper, some basic considerations concerning the design and use of hand-arm mechanical systems for dexterous manipulation tasks are presented. The UB robotic hand project is referred to as paradigm of this kind of manipulation systems.

A dynamic system is given with a transfer function of third order (one real pole, two complex poles, and two zeroes). It is desired to design a contactor control which yields a near-optimum follow-up of a given input. For zero-seeking systems and for step-inputs an "optimum" control problem can be defined easily; however, a general solution of the optimum problem is not yet available. The known particular cases yield switching surfaces in the phase space which depend on the particular pole and zero locations (parameter set). The realization of such surfaces is rather difficult and usually demands digital computer equipment. The author and her associates suggest in this paper switching functions which can be realized easily and which give good response for different parameter sets. Particular attention is given to the occurrence of discontinuities in linear switching functions and their advantages and disadvantages; to different types of chatter, which may or may not improve the system performance; to discontinuities in the switching function which can be avoided by feeding the output of the contactor back into the switching function. Analog computer tests show the performance of systems with linear switching functions. The choice of the coefficients in this linear switching function is discussed. The influence of imperfections of the control system on its performance is investigated. Comparison to linear feedback control systems are included. This paper is to be published in the Proceedings of the First IFAC Moscow Congress by Butterworth Scientific Publications in 1960.

Modern control systems are complex and must meet stringent performance requirements. There is an obvious need in such systems for development of design procedures for computer-controlled systems which make use of the highly developed computer art. This paper presents an attempt to apply computers in the solution of one class of such systems. The realization of the novel computer circuits required is outlined, and the overall design logic is presented. The designer versed in the art will have no difficulty integrating the individual circuits. It appears that analog circuits interconnected by means of switching devices will be useful in the realization of the required computing circuits. The required computer facility seems to be reasonable, and commensurate with the control problem. (Author)

Need for adaptive control systems is explained, and results obtainable with two forms are discussed. Recognized approaches to achieving self-adaptive action are indicated; integrating and nonintegrating techniques are compared. One non-integrating form, the model-bistable system, is taken as an example, and analysis of its operation is developed. Its application to flight control is described, and its limitations in this and other applications are discussed. Effects of system performance requirements, including nature of input signals and disturbances, on the choice of adaptive control type are considered. Relations of mechanistic adaptive control systems to those found in the biological organism are discussed. This paper is to be published in the Proceedings of the First IFAC Moscow Congress by Butterworth Scientific Publications in 1960.

Automatic tracking systems are conventionally analysed and optimized on the basis of assumed linear operation, deterministic inputs, and the use of the minimum mean square error criterion in the presence of noise. This approach is limited by (a) the fact that the error detector is linear for only a small range of error signals, and (b) the mean square error criterion is not pertinent for a large class of applications. This paper reports an analysis of automatic tracking systems which overcomes in part these two limitations. The Fokker-Planck diffusion equation is used to find the probability distribution of the output of the tracking system and from this the probability of loss is found as a function of various system parameters. A digital computer was used to obtain numerical results for non-linear error detector characteristics.

In the paper an effective way of investigation of dynamical systems by means of their converted model is proposed. The reconstruction of a dynamical model and its total orientation for a task relies on expressing the relation between investigated characteristics of a system and its parameters in the form of a regression or approximating polynomial. Such a model is obtained on a data basis of few object or its dynamical model investigations, which are planned using the mathematical apparatus of the experimental design theory. It is most comfortable to carry over the active experiment on a simulation model of a system. The paper presents a mathematical apparatus and capabilities of the method. It is possible to use the offered way for the solution of selected problems at the stage of simulation model creation as well as of the system analysis and design. The method capabilities have been illustrated by examples of verification of permissible simplifications of simulation models, evaluation of model parameters, analysis of the influence of parameters on output characteristic and of optimum synthesis.

Facing the defect in CRI method in logical semantics and the problem in its application to longer reasoning chaining in expert system, this paper, based on triple I method in literature (Wang, 1999a), proposes a characteristic expansion algorithm of fuzzy reasoning. The algorithm is then used in the fuzzy reasoning modes of multidimension and multi-implication, from which the models' characteristic expansion algorithms are deducted. As a result, a new way-out is found in the application of fuzzy reasoning in the intelligent systems

Summary With the exception of a passing reference in an early note by Zadeh1, little or no attention appears to have been paid to the inverse describing function (IDF) problem. In essence this problem is concerned with extracting a description of a non-linear element given only its describing function. The problem is important as the final link in the nonlinear synthesis problem for automatic control systems, for various experimental determinations, and finally for itself. In this paper an analytic solution to the problem which results in expressions in the form of Volterra integral equations is provided. The conditions under which the representation for the non-linear element is unique are discussed and additional requirements for the unique definition of non-single-valued non-linear elements are given. As might be anticipated the describing function of a memory-type non-linear element is not sufficient to obtain a unique representation for the element. Practical computational techniques are mentioned for the machine solution of the IDF and several examples are given.

Summary This paper studies the optimum control of multi-variable systems by considering the behaviour of the two-variable on-off system described by the equation x ¨ + A x ˙ = u where u1, u2 = ± 1. By the application of Pontryagin's maximum principle, it is shown how the number of switchings and the drive ratio u1/u2, for an optimum trajectory (minimum settling time criterion), depend on the nature of the matrix A. For the case when the interaction terms a12 and a21 have the same sign, the maximum number of switchings for an optimum trajectory is three, and the drive ratio u1/u2 near the origin of the error phase space has the same sign as a12 and a21. A predictive controller described in this paper finds the three switching times by an iterative process which involves the application of logical rules to the predicted behaviour of the system, computed in a fast analogue model. This realizable controller is optimum when the two-by-two matrix A has a12 a21 ≥ 0; and will also control systems where a12 a21

Summary The purpose of this paper is to investigate the optimum design of predictor control systems subject to statistical or deterministic inputs, under appropriate constraints on the control signal. The control signal constraints treated in this paper are: (a) the magnitude of the control signal equal to a constant (this is the bang-bang control problem), and (b) the magnitude of the control signal less than or equal to some constant. The basic optimization problem is viewed, in very general terms, as a problem in decision theory. Based on available information, the decision must be as to which of the allowable control signals should be applied to the plant in order to achieve the optimum performance. A sum of squared error criterion is used to define the optimum in order to reduce the problem to a problem in linear decision theory. A piecewise-linear control boundary is found which can be used to generate the desired control signal. The realization of this control boundary is shown to be straightforward and inexpensive. This technique can be applied to linear time invariant plants of arbitrary order. Experimental results verifying the techniques which are developed are presented. Included in these is the control of the step response of a system with a saturation-limited unstable second order plant in the presence of noise.