An approach to robust control design

A robust stability test is formulated and the methodology of its use in the robust control system design is presented. The paper makes a contribution to the existing approaches to solution of this class of problems.     

An optimal control approach to robust control design

We propose an optimal control approach to robust control design. Our goal is to design a state feedback to stabilize a system under uncertainty. We translate this robust control problem into an optimal control problem of minimizing a cost. Because the uncertainty bound is reflected in the cost, the solution to the optimal control problem is a solution to the robust control problem. Our approach can deal with both linear and non-linear systems. Furthermore it can handle both matched and unmatched uncertainties. It can also handle uncertainty in the control input matrix.     

An approach to multivariable combustion control design

In this paper, an approach to multivariable combustion control design within the Individual Channel Design (ICD) framework for analysis and control design is presented. ICD is a framework which involves an interplay between customer specification, uncertain plant characteristics, and the multivariable feed-back design itself. Established multivariable methods and process engineering knowledge can be incorporated or evaluated within the ICD framework. The combustion control has been designed and evaluated with a computer simulation of both a linearized model and a nonlinear model of the closed-loop system. The ICD multivariable framework shows in a highly transparent manner, by way of simple graphical frequency response indicators, what the main possibilities and difficulties posed by a combustion process for multivariable control are, and how much trade-off between control specifications is possible. Solutions are also presented for problems such as: integrity of closed-loop control, balance of input-output channels, simple and transparent controller structure, and robustness.     

An approach to multicriterion optimization problems for engineering design

Optimization problems in mechanical engineering design are often modelled as nonlinear programming problems. A multicriterion optimization approach to this problem is developed in this work. The problem formulation is given, and the min-max principle for this problem is discussed. Next, an algorithm is provided for comparing solutions using this principle.The solution which is defined by the min-max principle of optimality may be called the best compromise considering all the criteria simultaneously and on equal terms of importance. This principle is fully formalized mathematically and used to obtain the optimal solution automatically. The algorithm for comparing solutions gives us, from any set of solutions, the one which is optimal in the min-max sense.Seeking the optimal solution in the min-max sense can be carried out in many different ways. Some methods based upon the Monte Carlo method and trade-off studies are proposed.The approach as discussed here is applied to the design of machine tool gearboxes. The problem is formulated as finding the basic constructional parameters (modules, numbers of teeth etc.) of a gearbox which minimizes simultaneously four objective functions: volume of elements, peripheral velocity between gears, width of gearbox and distance between axes of input and output shafts. A detailed example considering a lathe gearbox optimization problem is also presented. This example indicates that for some mechanical engineering optimization problems, using this approach, we can automatically obtain a solution which is optimal and acceptable to the designer.     

An approach for reverse engineering of design patterns

For the maintenance of software systems, developers have to completely understand the existing system. The usage of design patterns leads to benefits for new and young developers by enabling them to reuse the knowledge of their experienced colleagues. Design patterns can support a faster and better understanding of software systems. There are different approaches for supporting pattern recognition in existing systems by tools. They are evaluated by the Information Retrieval criteria precision and recall. An automated search based on structures has a highly positive influence on the manual validation of the results by developers. This validation of graphical structures is the most intuitive technique. In this paper a new approach for automated pattern search based on minimal key structures is presented. It is able to detect all patterns described by the GOF [15]. This approach is based on positive and negative search criteria for structures and is prototypically implemented using Rational Rose and Together.     

An approach to design of control systems with parametric-coordinatefeedback

A method of control design for linear systems and some nonlinear systems is considered. The class of systems is characterized by the presence of coordinate and parametric feedback control signals. The system can be presented as consisting of two control channels: one controlling the system in a specified domain and the other to drive the system into this domain. The proposed method for binary system design is based on the solution of the Lyapunov-Bellman equations. The Lyapunov-Bellman function (or the optimal Lyapunov function, namely, the solution of the correspondent equation) is used to design the second channel of control. The analytical design problem of this channel is formulated as an optimal control problem under a cost functional of special type     

An MPC approach to the design of two-layer hierarchical control systems

A methodology for the design of two-layer hierarchical control systems is presented. The high layer corresponds to a system with slow dynamics, whose control inputs must be provided by subsystems with faster dynamics placed at the low layer. Model Predictive Control laws are synthesized for both layers and overall convergence properties are established. The use of different control configurations is also considered by allowing the switching on/off of the subsystems at the low layer. A simulation example is reported to witness the potentialities of the proposed solution.     

An iterative optimization approach to design of control Lyapunov function

This paper presents a fractional programming formulation and its solution strategy for design of control Lyapunov function (CLF) to guarantee the closed-loop stability of a control affine system for the states in a specified region. Without restrictive assumptions found in previous approaches, the fractional programming problem is reformulated as a recursive optimization problem to solve for a CLF with basis functions. A computationally effective derivative-free coordinate search method is proposed to find the solution, where the search space is confined by a piecewise linear function that approximates the lower bound of objective function. A CLF-based controller design is also proposed to handle infinity-norm input constraints. Two examples with actuator saturation and state constraints demonstrate the efficacy of the proposed approach.     

An energy-shaping approach to the design of excitation control of synchronous generators

In this paper we discuss the estimation of the domain of attraction of equilibria in power systems and propose a new passivity-based controller design methodology for excitation control of synchronous generators. The methodology goes beyond the widely popular damping injection (L_gV) schemes, to actually shape the total energy function via modification of the energy transfer between the mechanical and electrical components of the system. Applying the procedure it is shown that a, properly tuned, linear state feedback enlarges both the estimates and the actual domain of attraction, thus increasing critical clearing time for faults. This is illustrated in two case studies, including a benchmark comparison with the classical control scheme.     

An interpretive approach for interactive real-time control through a network

The CERN Super Proton Synchrotron (SPS) accelerator represents a large industrial control problem, with the additional complication that the control strategies are not fixed. Right from the beginning, it was decided to use an interpretive language for the control process. The main goal of this approach was to reduce the amount of programming effort needed for a proper control of the accelerator, by allowing the actual users — physicists, engineers and technicians — to write the control programs they needed. It very quickly appeared that this method was ideal for providing interactive tools for a control system based on a network.The requirement for interactive network control has been implemented by leaving to the user the choice of those parts of the network best suited for the execution of sections of his program. For that reason interpreter instructions have been defined, allowing the user to define where in the network a logical unit of his algorithm should be executed, and where individual items of the data should be stored.This strategy allows easy access to all the hardware through a distributed data-base. The interpreter being basically a string handler, equipment control can be packed into a module which is called from the program through a name with a standard input-output scheme. All this allows algorithm exportation, while network transfers are minimized.Such a system has been in operation since 1976. Many non-professional programmers are regularly writing or modifying ‘network procedures’ for everchanging control purposes. The simplicity and flexibility of the interpretive method has enabled many technical innovations to be installed over the years, and some of these are described.     

针对无线网络的入侵检测系统设计方法研究

从实际应用出发,提出了一种针对无线网络的入侵检测方法,给出了入侵检测系统的设计方案,扩展了系统管理员的安全管理能力(包括安全审计、监视、攻击识别和响应),具有较强的经济效益和借鉴意义.     

An H-minimax approach to the design of robust control systems

A realistic feedback design problem is posed based on the minimization of a weighted combination of the sensitivity and complementary sensitivity matrices. A solution is obtained which makes use of the recently proposed methods for minimizing the sensitivity function alone.     

An optimal control approach to the design of vibrating elastic-viscoelastic sandwich beams

This work features the application of an optimal control algorithm to a new class of continuous one-dimensional structural design problems. A sandwich beam of rectangular cross-section is considered. It has a variable-thickness core and two equal variable-thickness cover layers and is subjected to harmonic forced vibrations. The objective is to distribute both the core and layer mass so as to minimize a measure of dynamic compliance for forced steady-state vibration and fixed material volumes. Either or both materials may be viscoelastic. Any constitutive relation may be used provided it is linear and time-invariant.The design problem is formulated as an optimal control problem. The resulting problem contains ten state variables, two control functions, four control parameters, and six terminal state constraints. Simple transformations are used to treat the minimum-gage constraints. A conjugate gradient/gradient projection optimal control algorithm is then used to obtain numerical solutions. Several optimal beam designs are presented and compared for a variety of problem parameter values.     

A bi-level approach for the design of event-triggered control systems over a shared network

An efficient usage of available resources is a substantial requirement for the successful design of networked control systems. Recent results indicate major benefits of event-based control compared to conventional designs, when resources such as communication, energy, and computation, are sparse. This paper considers multiple entities of heterogeneous control systems whose feedback loops are coupled through a common communication medium. The design of the decentralized event-triggering control system is formulated as an average-cost problem that aims at the minimization of a social cost criterion. A state aggregation technique is used to develop a bi-level design method, which divides into a local average-cost problem within every subsystem and a global resource allocation problem assigning optimal transmission rates to every subsystem. Stability conditions are derived that guarantee stochastic stability of the aggregate system. Under these conditions, it is shown that the design approach is asymptotically optimal as the number of subsystems increases.     

An engineering approach to sociable robots

Robotics researchers and cognitive scientists are becoming more and more interested in so-called sociable robots. These machines normally have expressive power (facial features, voice,?…) as well as abilities for locating, paying attention to, and addressing people. The design objective is to make robots which are able to sustain natural interactions with people. This capacity falls within the range classed as social intelligence in humans. This position paper argues that the reproduction of social intelligence, as opposed to other types of human ability, may lead to fragile performance, in the sense that tested cases may produce rather different performances to future (untested) cases and situations. This limitation stems from the fact that our social abilities, which appear early in life, are mainly unconscious in origin. This is in contrast with other human abilities that we carry out using conscious effort, and for which we can easily conceive algorithms and representations. This novel perspective is deemed useful for defining the obstacles and limitations of a field that is generating increasing interest. Taking into account the mentioned issues, a development approach suited to the problem is proposed. The use of this approach is demonstrated in the development of CASIMIRO, a robotic head with basic interaction abilities.     

An MDA approach to knowledge engineering

This paper proposes an MDA approach to knowledge engineering, centered on the CommonKADS knowledge model. The latter corresponds to the CIM level of MDA whereas PRR, which represents production rules and rulesets, corresponds to the PIM level. The paper explores the mapping between CommonKADS knowledge models and production rules and rulesets based on PRR. Mapping CommonKADS knowledge models into PRR is very useful, due to the fact that the CIM level remains relatively unexplored, despite its key role in MDA. This motivates our choice to focus on the CIM and PIM levels. Furthermore, the mapping between PIM and PSM (i.e. the implementation of production rules in specific rule-based systems) constitutes less of an issue. To map CommonKADS knowledge models into PRR production rules and rulesets, we propose and illustrate a set of transformations. To ease these transformations, we start by grouping elements of the CommonKADS knowledge models into so-called “inference groups”. We propose and illustrate an algorithm that defines these inference groups automatically. The definition of transformations between models (CIM to PIM levels) requires a specific metamodel for CommonKADS as well as a dedicated metamodel for PRR. Unlike PRR, there is no published CommonKADS metamodel. This paper proposes a comprehensive CommonKADS knowledge metamodel. We describe and discuss an example, applying the whole approach.     

An adaptive control approach to the attitude control of a flexible rocket

An adaptive notch filter design that considers the body-bending vibration associated with the attitude control of a two-stage sounding rocket is discussed in this paper. The algorithm adapts the parameters while keeping the poles of the notch filter inside the unit circle on the z-plane, and it satisfies the stability conditions of the filter at all times. Only a single parameter of the filter is adapted to simplify the algorithm to speed up the convergence rate. Applying this adaptive notch filter to the two-stage sounding rocket results in stable response characteristics of the attitude control system, which is unstable without adaptation.