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Showing papers in "International Journal of Systems Science in 2004"


Journal ArticleDOI
TL;DR: It is shown that the proposed control scheme ensures the reachability of the sliding surfaces in both the state estimate space and the estimation error space.
Abstract: An observer-based sliding mode control problem is studied for state-delayed systems with unmeasurable states and nonlinear uncertainties. The main advantage of the proposed scheme is that it eliminates the need for state variables to be fully accessible for its control. This is possible through the use of a sliding mode controller, which performs its control by employing state estimates obtained from the sliding mode observer. By means of linear matrix inequalities, a sufficient condition is then given to ensure the asymptotic stability of the overall closed-loop state-delayed system composed of the observer dynamics and the estimation error dynamics. Furthermore, it is shown that the proposed control scheme ensures the reachability of the sliding surfaces in both the state estimate space and the estimation error space.

133 citations


Journal ArticleDOI
TL;DR: In this paper, a hierarchical genetic algorithm (HGA) is introduced to identify the number of coasting points required according to the traffic conditions, and Minimum-Allele-Reserve-Keeper (MARK) is adopted as a genetic operator to achieve fitter solutions.
Abstract: The railway service is now the major transportation means in most of the countries around the world. With the increasing population and expanding commercial and industrial activities, a high quality of railway service is the most desirable. Train service usually varies with the population activities throughout a day and train coordination and service regulation are then expected to meet the daily passengers' demand. Dwell time control at stations and fixed coasting point in an inter-station run are the current practices to regulate train service in most metro railway systems. However, a flexible and efficient train control and operation is not always possible. To minimize energy consumption of train operation and make certain compromises on the train schedule, coast control is an economical approach to balance run-time and energy consumption in railway operation if time is not an important issue, particularly at off-peak hours. The capability to identify the starting point for coasting according to the current traffic conditions provides the necessary flexibility for train operation. This paper presents an application of genetic algorithms (GA) to search for the appropriate coasting point(s) and investigates the possible improvement on fitness of genes. Single and multiple coasting point control with simple GA are developed to attain the solutions and their corresponding train movement is examined. Further, a hierarchical genetic algorithm (HGA) is introduced here to identify the number of coasting points required according to the traffic conditions, and Minimum-Allele-Reserve-Keeper (MARK) is adopted as a genetic operator to achieve fitter solutions.

92 citations


Journal ArticleDOI
TL;DR: This paper considers a general production lot size inventory model with deteriorated and imperfect products taking into account inflation and time value of money and proves that such a minimal solution is unique and global-optimal.
Abstract: This paper considers a general production lot size inventory model with deteriorated and imperfect products taking into account inflation and time value of money. The production, demand, and deterioration rates are known, continuous, and differentiable functions of time. Shortages are allowed, but only a fraction of the stock out is backordered, and the rest is lost. Under these general assumptions, the inventory model is formulated, and a closed form of the total relevant costs of the underlying inventory system is obtained. Sufficient conditions which lead to a minimal solution of the considered problem are derived. Then, a rigorous mathematical analysis is used to prove that such a minimal solution is unique and global-optimal. A numerical verification of the proposed model is also given.

60 citations


Journal ArticleDOI
TL;DR: An inventory model for deteriorating items with a shortage occurring at the supplier involving a supply chain between the producer and buyer is developed and it is demonstrated that integrated decisions are more cost-effective compared with independent decisions from the supplier, producer or buyer.
Abstract: The aim of this paper is to develop an inventory model for deteriorating items with a shortage occurring at the supplier involving a supply chain between the producer and buyer. A numerical example is used to illustrate the model and demonstrate that integrated decisions are more cost-effective compared with independent decisions from the supplier, producer or buyer. The optimal number of deliveries is derived with the minimal joint total cost from the integrated viewpoint. This study compares cases with and without shortages. A sensitivity analysis is given to explore the effect from a supplier shortage.

50 citations


Journal ArticleDOI
TL;DR: An integrated model for the joint determination of both economic production quantity and level of preventive maintenance (PM) for an imperfect production process that has a general deterioration distribution with increasing hazard rate is developed.
Abstract: In this paper, we develop an integrated model for the joint determination of both economic production quantity and level of preventive maintenance (PM) for an imperfect production process This process has a general deterioration distribution with increasing hazard rate The effect of PM activities on the deterioration pattern of the process is modelled using the imperfect maintenance concept In this concept, it is assumed that after performing PM, the ageing of the system is reduced in proportion to the PM level After a period of time in production, the process may shift to out-of-control states, either type I or type II A minimal repair will remove the type I out-of-control state If a type II out-of-control state occurs, the production process has to stop, and then restoration work is carried out Examples of Weibull shock models are given to show that the use of PM reduces costs

43 citations


Journal ArticleDOI
Ju H. Park1
TL;DR: Sufficient conditions for the existence of such controllers are derived based on the linear matrix inequality (LMI) approach combined with the Lyapunov method, which is given in terms of the feasible solutions to a certain LMI.
Abstract: In this paper, the robust non-fragile guaranteed cost-control problem is studied for a class of uncertain linear large-scale systems with time-delays in subsystem interconnections and given quadratic cost functions. The uncertainty in the system is assumed to be norm-bounded and time-varying. Also, the state-feedback gains for subsystems of the large-scale system are assumed to have norm-bounded controller gain variations. The problem is to design a state feedback control law such that the closed-loop system is asymptotically stable, and the closed-loop cost function value is not more than a specified upper bound for all admissible uncertainties. Sufficient conditions for the existence of such controllers are derived based on the linear matrix inequality (LMI) approach combined with the Lyapunov method. A parameterized characterization of the robust non-fragile guaranteed cost controllers is given in terms of the feasible solutions to a certain LMI. A numerical example is given to illustrate the proposed method.

42 citations


Journal ArticleDOI
TL;DR: A linear matrix inequality approach to compute 2 guaranteed costs by means of parameter-dependent Lyapunov functions is proposed, and both continuous- and discrete-time systems are investigated.
Abstract: A linear matrix inequality approach to compute H 2 guaranteed costs by means of parameter-dependent Lyapunov functions is proposed. The uncertain linear systems are supposed to belong to convex-bounded domains (polytope type uncertainty). Both continuous- and discrete-time systems are investigated and the results are illustrated by means of numerical examples.

39 citations


Journal ArticleDOI
TL;DR: It is shown that probability p not only determines the topological transition of the N-W small-world network model, but also dominates the stability of the local equilibria and bifurcating periodic solutions, and can be further applied to stabilize a periodic spreading behaviour onto a stable equilibrium over the network.
Abstract: A general nonlinear model of disease spreading is proposed, describing the effect of the new link-adding probability p in the topological transition of the N-W small-world network model. The new nonlinear model covers both limiting cases of regular lattices and random networks, and presents a more flexible internal nonlinear interaction than a previous model. Hopf bifurcation is proved to exist during disease spreading in all typical cases of regular lattices, small-world networks, and random networks described by this model. It is shown that probability p not only determines the topological transition of the N-W small-world network model, but also dominates the stability of the local equilibria and bifurcating periodic solutions, and moreover can be further applied to stabilize a periodic spreading behaviour onto a stable equilibrium over the network.

34 citations


Journal ArticleDOI
TL;DR: Multi-objective economic lot size models of deteriorating items for both the buyer and the seller are developed in crisp and fuzzy environments and the impreciseness in the above objectives and constraint has been expressed by fuzzy linear membership functions.
Abstract: Multi-objective economic lot size models of deteriorating items for both the buyer and the seller are developed in crisp and fuzzy environments A buyer tries to minimize total average cost and at the same time the seller maximizes the total average revenue allowing discount on bulk purchase with the restricted material cost of the buyer Here, the total average expenditure for the buyer, the estimated total average revenue for the seller and the resource for the material purchase are assumed to be crisp (Model 1) and fuzzy (Model 2) in nature The impreciseness in the above objectives and constraint have been expressed by fuzzy linear membership functions It has been solved by the additive goal and fuzzy additive goal programming methods with different weights Also, to ensure the achievement level, thresholds are considered in crisp and fuzzy models All the models are illustrated with numerical examples and the results are compared

28 citations


Journal ArticleDOI
TL;DR: In this paper, a pole-placement-based adaptive controller synthesized from a multi-estimation scheme is designed for linear single-input single-output time-invariant plants.
Abstract: A pole-placement-based adaptive controller synthesized from a multi-estimation scheme is designed for linear single-input single-output time-invariant plants. A higher level switching structure between the various estimation schemes is used to supervise the reparameterization of the adaptive controller in real time. The basic usefulness of the proposed scheme is to improve the transient behaviour while guaranteeing closed loop stability. The scheme becomes specifically useful when extended to linear plants whose parameters are piecewise constants while changing abruptly to new constant parameterizations or in the case when the parameters are slowly time varying rather than constant. Thus, the scheme becomes attractive from a modelling point of view since the plant, while being potentially time varying, or in particular, possessing several operation points, is modelled as a set of time-invariant plant unknown parameterizations each possessing its own estimation scheme. In that way, the model description becomes conceptually simple and easy to implement concerned with both estimation and control issues. A description of the controller architecture with multiple parameterizations, together with its associated multi-estimation scheme is given. In addition, the proofs of boundedness of all the relevant signals are given so that the closed-loop system is proved to be stable.

26 citations


Journal ArticleDOI
TL;DR: Fractional Order Control methods were applied to a three-axis reaction wheels satellite attitude control system to establish an efficient control law which satisfies a given specification and maintains sufficient stability and accuracy even under the strong effects of intrinsic parameters uncertainties, and also external perturbations.
Abstract: Fractional Order Control methods were applied to a three-axis reaction wheels satellite attitude control system To show the advantages of this method, a comparative study between a Linear Quadratic Regulator and a Fractional Order Control was established through two principal fractional control laws The aim is to establish an efficient control law which satisfies a given specification and maintains sufficient stability and accuracy even under the strong effects of intrinsic parameters uncertainties, and also external perturbations

Journal ArticleDOI
TL;DR: This paper addresses the problem of decentralized implementation of a global state feedback controller for multi-agent systems through the construction of low-order decentralized functional observers with the purpose of generating the required corresponding control signal for each local control station.
Abstract: This paper addresses the problem of decentralized implementation of a global state feedback controller for multi-agent systems. The system is assumed to be under the constraint of a complete decentralized information structure. The decentralization of the control task is achieved through the construction of low-order decentralized functional observers with the purpose of generating the required corresponding control signal for each local control station. A design procedure is developed for obtaining an approximate solution to the design of the observers. Stability analysis is provided for the global system using the proposed observer-based approach. A numerical example is given to illustrate the design procedure and cases when the observers' order increases from the lowest value.

Journal ArticleDOI
TL;DR: Some verifiable conditions that are applicable to sets with finite number of elements, to corroborate or falsify the hypothesis of the elements of that set being samples of the Pareto set are proposed.
Abstract: Multiobjective design problems give rise to a well-defined object: the Pareto-set. This paper proposes some verifiable conditions that are applicable to sets with finite number of elements, to corroborate or falsify the hypothesis of the elements of that set being samples of the Pareto set. These conditions lead to several generic criteria that can be employed in the evaluation of algorithms as multiobjective optimization mechanisms. A conceptual multiobjective genetic algorithm is proposed, exploiting the group properties of the intermediate Pareto-set estimates to generate a consistent final estimate. The methodology is applied to the case of a mixed H2/H∞ control design. Recent dedicated multiobjective algorithms are evaluated under the proposed methodology, and it is shown that they can generate sub-optimal or non-consistent solution sets. It is shown that the proposed synthesis methodology can lead to both enhanced objectives and enhanced consistency in the Pareto-set estimate.

Journal ArticleDOI
TL;DR: This paper proposes the simpler and less conservative criteria, based on the Convex combination property, Lyapunov criterion and Razumikhin theorem, under which the parallel-distributed fuzzy control can stabilize the whole uncertain fuzzy time-delay systems asymptotically.
Abstract: In this paper, non-linear systems with time-varying delays and parametric uncertainties are represented by an equivalent Takagi–Sugeno-type fuzzy model. Based on the Convex combination property, Lyapunov criterion and Razumikhin theorem, some sufficient conditions are derived under which the parallel-distributed fuzzy control can stabilize the whole uncertain fuzzy time-delay systems asymptotically. On the other hand, if the states are not all available, the fuzzy state observers are proposed to estimate all states of the fuzzy systems for fuzzy control. By satisfying some criteria, the stabilization, estimation and robustness of the fuzzy time-delay systems are also guaranteed. Moreover, if all the time-delays τ i ( t ) of the fuzzy systems are the same for all the rules (i.e. τ i (t) = τ j (t) = τ for all i ≠ j), this paper proposes the simpler and less conservative criteria. The practical example based on the continuous stirred tank reactor model and a numerical example are given to illustrate the ...

Journal ArticleDOI
TL;DR: Qualitative model validation is used to compare the multiresolution wavelet models and it is shown that the dynamical features of chaotic systems can be captured by the identified models providing the wavelet basis functions are properly selected.
Abstract: A new modelling framework for identifying and reconstructing chaotic systems is developed based on multiresolution wavelet decompositions. Qualitative model validation is used to compare the multiresolution wavelet models and it is shown that the dynamical features of chaotic systems can be captured by the identified models providing the wavelet basis functions are properly selected. Two basis selection algorithms, orthogonal least squares and a new matching pursuit orthogonal least squares, are considered and compared. Several examples are included to illustrate the results.

Journal ArticleDOI
TL;DR: The paper studies the effects of an imperfect production process on the optimal production run length when capital investment in process quality improvement is adopted and the optimal lot sizing and capital investment are appropriately determined.
Abstract: The paper studies the effects of an imperfect production process on the optimal production run length when capital investment in process quality improvement is adopted. The mathematical model is derived to determine the optimal production run length and capital investment under the assumption of logarithmic investment function such that the total annual cost is minimized. In addition, an efficient algorithm is provided to find both the optimal production run length and the optimal process quality. Therefore, the optimal lot sizing and capital investment are appropriately determined. A numerical example is provided to illustrate the results and to assess the cost savings realized by adopting capital investment. Furthermore, some managerial implications are also included.

Journal ArticleDOI
TL;DR: Novel trading strategies based on the machine learning methods of genetic algorithms and reinforcement learning are presented that effectively emulates the trading process in the deregulated Foreign Exchange Market.
Abstract: Foreign exchange trading has emerged recently as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process will be very helpful. A major issue for traders in the deregulated Foreign Exchange Market is when to sell and when to buy a particular currency in order to maximize profit. This paper presents novel trading strategies based on the machine learning methods of genetic algorithms and reinforcement learning.

Journal ArticleDOI
TL;DR: Two approaches are introduced for the identification of linear time-invariant systems when only output data are available and the input sequences are independent and must be non-Gaussian.
Abstract: Two approaches are introduced for the identification of linear time-invariant systems when only output data are available. The input sequences are independent and must be non-Gaussian. To estimate the parameters of the system, we use only the fourth-order cumulants of the output, which may be contaminated by an additive, zero mean, Gaussian noise of unknown variance. To measure the performance of the proposed algorithms against existing methods, we compared them with the Zhang's algorithm. Simulations verify an apparent performance of the second algorithm, compared with the first and Zhang's algorithms, in a low signal-to-noise ratio and for small data. The simulation results show that the first algorithm has the same performance compared with Zhang's one. But the second algorithm achieves better performance compared with the first and Zhang is algorithm. For validation purposes, the second algorithm is used to search for a model able to describe and simulate the data set representing the wind speed.

Journal ArticleDOI
TL;DR: In this paper, the effects of auxiliary input signals on detecting changes in ARMAX processes via statistical tests are discussed and two extensions to the Cumulative sum test are considered when the direction of the change in the parameter space is known but its magnitude is unknown.
Abstract: The effects of auxiliary input signals on detecting changes in ARMAX processes via statistical tests are discussed. Two extensions to the Cumulative Sum Test are considered. The first is applicable when the direction of the change in the parameter space is known but its magnitude is unknown. The second is applicable when neither is known. The performance criteria for the design of stationary stochastic inputs are based on the asymptotic properties of the tests. It is shown that power-constrained optimal inputs have discrete spectra and a suitably chosen input can greatly improve the detection performance.

Journal ArticleDOI
TL;DR: Modified algebraic Riccati inequalities are developed and observer-based feedback control laws are designed that guarantee closed-loop asymptotic stability and reduction of the effect of an augmented disturbance input on the controlled output of a prescribed level, not only when the system is operating properly, but also under actuator and sensor failures.
Abstract: This paper is concerned with the reliable H∞ control design problem for linear state-delayed system using observed-based output feedback. It proposes a reliable control design scheme for the case of possibly a simultaneous presence of actuator failures and sensor failures. Modified algebraic Riccati inequalities are developed to solve the problem addressed. Based on this approach, observer-based feedback control laws are designed that guarantee closed-loop asymptotic stability and reduction of the effect of an augmented disturbance input on the controlled output of a prescribed level, not only when the system is operating properly, but also under actuator and sensor failures. A numerical example is presented to demonstrate the applicability and effectiveness of the proposed approach.

Journal ArticleDOI
TL;DR: This paper introduces an approach for modelling and designing multi-agent control architectures for agile manufacturing using a generic formalism based on a system-theoretic discrete event approach and introduces a mechanism based on evolutionary algorithms adapting the agents' decision laws that are encapsulated in agents’ states.
Abstract: This paper introduces an approach for modelling and designing multi-agent control architectures for agile manufacturing using a generic formalism based on a system-theoretic discrete event approach. To describe the details of the modelling strategy, we apply the proposed approach to a multi-agent network for job flow control in a manufacturing plant. Two interacting types of autonomous controllers, Part Agents and Machine Agents, are in charge of controlling the part flow and the machine processing sequences. both type of agents are first modelled as atomic discrete event systems and subsequently integrated in the model of the entire network of autonomous controllers. To improve the performance of the network of agents, we introduce a mechanism based on evolutionary algorithms adapting thew agents' decision laws that are encapsulated in agents' states. Through network simulation, the algorithm continuously searches for effective decision laws, consequently adapting agent's behaviour to the current operational conditions of the manufacturing floor. Simulation results show the potentialities of the approach.

Journal ArticleDOI
TL;DR: A new and simple estimation scheme for the variances of the white input and output measurement noises is presented, which is only based on expanding the denominator polynomial of the system transfer function and makes no use of the average least-squares errors.
Abstract: This paper addresses the problem of parameter estimation of stochastic liner systems with noisy input-output measurements. A new and simple estimation scheme jor the variances of the white input and output measurement noises is presented, which is only based on expanding the denominator polynomial of the system transfer function and makes no use of the average least-squares errors. The attractive feature of the iterative least-square based parametric algorithm thus developed is its improved convergence property. The effectiveness of the developed identification algorithm is demonstrated through numerical illustrations.

Journal ArticleDOI
TL;DR: A new market dispatching mechanism has been developed to minimize the ISO's total payment while ensuring system security and genetic algorithms are used in the finding of the global optimal solutions.
Abstract: Power systems rely greatly on ancillary services in maintaining operation security. As one of the most important ancillary services, spinning reserve must be provided effectively in the deregulated market environment. This paper focuses on the design of an integrated market for both electricity and spinning reserve service with particular emphasis on coordinated dispatch of bulk power and spinning reserve services. A new market dispatching mechanism has been developed to minimize the ISO's total payment while ensuring system security. Genetic algorithms are used in the finding of the global optimal solutions for this dispatching problem. Case studies and corresponding analyses have been carried out to demonstrate and discuss the efficiency and usefulness of the proposed market.

Journal ArticleDOI
TL;DR: An aim of the proposed information systems theory (IST) is to build a bridge between the general systems theory's formalism and the world of information and information technologies, dealing with transformation of information as a common non-material substance, whose models in forms of computer algorithms and programs could be implemented to different material objects.
Abstract: An aim of the proposed information systems theory (IST) is to build a bridge between the general systems theory's formalism and the world of information and information technologies, dealing with transformation of information as a common nonmaterial substance, whose models in forms of computer algorithms and programs could be implemented to different material objects, including a human's thoughts and languages. A new approach to IST is based on a single concept and follows mathematical formalism that uses an information variation principle to build an information systemic model of a specific object. The problem's solution, procedure and methodology modelling are illustrated by the application of the information macrodynamics (IMD), which reveals the system model's main layers: microlevel stochastics, macrolevel dynamics, hierarchical dynamic network (IN) of information structures, its minimal logic, and optimal code of communication language, generated by the IN hierarchy, dynamics and geometry. The systems's complex dynamics originate information geometry and evolution with the functional information mechanisms of ordering, cooperation, mutation, stability, diversity, adaptation, self-organization, the double spiral's genetics, the system's generation, decaying, and transfering information to other systems along with the information mechanisms heredity and replication. The developed IMD's theoretical computer-based methodology and software have been applied to such areas as technology, communications, computer science, intelligent processes, biology, economy, management, and other non-physical and physical subjects with their mutual interactions, informational superimposition, and the information transferred between interactions.

Journal ArticleDOI
TL;DR: The mathematical representation chosen is NARMAX (Nonlinear AutoRegressive Moving Average with eXogenous inputs) due to its capability in modelling nonlinear systems and in using prior information.
Abstract: This paper deals with multiobjective nonlinear system identification applied when modelling the relation of firing angle and equivalent reactance of a thyristor controlled series capacitor (TCSC). The mathematical representation chosen is NARMAX (Nonlinear AutoRegressive Moving Average with eXogenous inputs) due to its capability in modelling nonlinear systems and in using prior information. The methodology for incorporation of prior knowledge is presented, and particular attention is given to the case of using information about resonant static response.

Journal ArticleDOI
TL;DR: In this article, the authors considered the problem of robust adaptive output feedback stabilization for a class of interconnected systems with static and dynamic interconnections, and unmodelled dynamics by using MT filters and the back-stepping design method.
Abstract: This paper considers the problem of robust decentralized adaptive output feedback stabilization for a class of interconnected systems with static and dynamic interconnections, and unmodelled dynamics by using MT filters and the back-stepping design method. It is shown that the closed-loop system is globally, stable, and the asymptotic convergence of all the signals except for the parameter estimates can be guaranteed. The result is better than those obtained in other related papers. The effectiveness of the proposed scheme is demonstrated by simulation.

Journal ArticleDOI
TL;DR: This paper examines a functioning policy of a parallel system that assumes availability of n non-identical, non-repairable units for replacement or support and the reliability of the system is evaluated by recursive relations.
Abstract: This paper examines a functioning policy of a parallel system. We assume availability of n non-identical, non-repairable units for replacement or support. Two units start their operation simultaneously at times S1 = S2 = 0, and any one of them is replaced instantaneously upon its failure by one of the (n - 2) standby units at random starting times Si (i = 3, ..., n). Thus, with probability one, the system is functioning with two units up till the failure of the (n - 1)th unit. Unit lifetimes Ti (i = 1,..., n) have a general joint distribution function F(t). The system has to operate for a fixed period of time, c, and it stops functioning when all available units fail before c. The probability that the system is functioning for the required period of time c depends on the distribution of the unit lifetimes. The reliability of the system is evaluated by recursive relations. Independent unit lifetimes are considered as special cases.

Journal ArticleDOI
TL;DR: From the control theory point of view, this work solves a non-linear model matching problem and produces a policy instrument that shapes the income Yt within a desired family of behaviours.
Abstract: Under the assumption that the income Y t follows a Samuelson-Hicks type of model, we calculate a policy variable G t , in closed form, so that Y t satisfies an ideal law Y t = F(U t *), U t * being an influence variable. The approach uses some recently developed tools of non-linear feedback design; it is fully parameterized and allows the dynamic change of the influence variable U t *. From the control theory point of view, we solve a non-linear model matching problem and produce a policy instrument that shapes the income Y t within a desired family of behaviours.

Journal ArticleDOI
TL;DR: A decision support system (DSS) that enables logistics planners of a well-known hank to design intra-city safe delivery routes, using an intelligent metaheuristic method and exploiting risk methodologies and spatial data information is presented.
Abstract: This paper presents a decision support system (DSS) that enables logistics planners of a well-known bank to design intra-city safe delivery routes, using an intelligent metaheuristic method and exploiting risk methodologies and spatial data information. The DSS routes minimize the probability of successful vehicle robbery at a certain point of the road network and satisfy all operational constraints of the distribution problem examined. The proposed DSS was implemented to an actual banking environment and the results obtained by this real-life, application are reported.

Journal ArticleDOI
TL;DR: In this paper, the output feedback disturbance attenuation problem for a class of uncertain nonlinear systems in the normal form and of relative degree one is studied based on output feedback passification.
Abstract: The problem of output feedback disturbance attenuation for a class of uncertain non-linear systems is studied based on output feedback passification. Previous work on output feedback disturbance attenuation is extended to the case where (1) the nominal system is not transformable into the normal form and (2) the uncertainty is parameterized nonlinearly. An adaptive output feedback controller is also provided that makes a nonlinear system passive. The paper then considers the output feedback disturbance attenuation problem for a class of uncertain nonlinear systems in the normal form and of relative degree one. The difference is that the result is applicable to nonlinear systems that include the uncertainty in the input matrix and do not satisfy the matching condition.