• Kyungpook Mathematical Journal
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• v.61 no.2
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• pp.353-369
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• 2021

In this paper, we examine and analyze the concept of different non-integer chaotic systems with external disturbances, uncertainties, and input non-linearities. We consider both drive and response systems with external bounded disturbances and uncertainties. We also consider non-linear control inputs. For synchronization, we introduce the adaptive sliding mode technique, in which we establish the stability of the controlled system by a control which estimates uncertainties and disturbances, and then applies a suitable sliding surface to control them. We use computer simulations to established the efficacy and adeptness of the prospective scheme.

• Journal of the Earthquake Engineering Society of Korea
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• v.6 no.2
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• pp.63-71
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• 2002

This paper examines the ASCE first generation benchmark problem for a seismically excited cable-stayed bridge, and proposes a new semi-active control strategy focusing on inclusion of effects of control-structure interaction. This benchmark problem focuses on a cable-stayed bridge in Cope Girardeau, Missouri, USA, for which construction is expected to be completed in 2003. Seismic considerations were strongly considered in the design of this bridge due to the location of the bridge in the New Madrid seismic zone and its critical role as a principal crossing of the Mississippi River. In this paper, magnetorheological(MR) fluid dampers are proposed as the supplemental damping devices, and a clipped-optimal control algorithm is employed. Several types of dynamic models for MR fluid dampers, such as a Bingham model, a Bouc-Wen model, and a modified Bouc-Wen model, are considered, which are obtained from data based on experimental results for full-scale dampers. Because the MR fluid damper is a controllable energy-dissipation device that cannot add mechanical energy to the structural system, the proposed control strategy is fail-safe in that bounded-input, bounded-output stability of the controlled structure is guaranteed. Numerical simulation results show that the performance of the proposed semi-active control strategy using MR fluid dampers is quite effective.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.3
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• pp.210-218
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• 2006

Traditional statistical process control (SPC) applied to discrete part industry in the form of control charts can look for and eliminate assignable causes by process monitoring. On the other hand, engineering process control (EPC) applied to the process industry in the form of feedback control can maintain the process output on the target by continual adjustment of input variable. This study presents controlling and monitoring rules adopted by variable sampling interval (VSI) to change sampling intervals in a predetermined fashion on the predicted process levels under integrated EPC and SPC systems. Twelve rules classified by EPC schemes(MMSE, constrained PI, bounded or deadband adjustment policy) and type of sampling interval combined with EWMA chart of SPC are proposed under IMA (1,1) disturbance model and zero-order (responsive) dynamic system. Properties of twelve control rules under three patterns of process change (sudden shift, drift and random shift) are evaluated and discussed through simulation and control rules for integrated VSI EPC and SPC systems are recommended.

• International Journal of Control, Automation, and Systems
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• v.2 no.3
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• pp.374-383
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• 2004

This paper presents a neural network adaptive controller for autonomous diving control of an autonomous underwater vehicle (AUV) using adaptive backstepping method. In general, the dynamics of underwater robotics vehicles (URVs) are highly nonlinear and the hydrodynamic coefficients of vehicles are difficult to be accurately determined a priori because of variations of these coefficients with different operating conditions. In this paper, the smooth unknown dynamics of a vehicle is approximated by a neural network, and the remaining unstructured uncertainties, such as disturbances and unmodeled dynamics, are assumed to be unbounded, although they still satisfy certain growth conditions characterized by 'bounding functions' composed of known functions multiplied by unknown constants. Under certain relaxed assumptions pertaining to the control gain functions, the proposed control scheme can guarantee that all the signals in the closed-loop system satisfy to be uniformly ultimately bounded (UUB). Simulation studies are included to illustrate the effectiveness of the proposed control scheme, and some practical features of the control laws are also discussed.

• International Journal of Control, Automation, and Systems
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• v.5 no.5
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• pp.526-538
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• 2007

This paper presents a neural network based decentralized excitation controller design for large-scale power systems. The proposed controller design considers not only the dynamics of generators but also the algebraic constraints of the power flow equations. The control signals are calculated using only local signals. The transient stability and the coordination of the subsystem control activities are guaranteed through rigorous stability analysis. Neural networks in the controller design are used to approximate the unknown/imprecise dynamics of the local power system and the interconnections. All signals in the closed loop system are guaranteed to be uniformly ultimately bounded. To evaluate its performance, the proposed controller design is compared with conventional controllers optimized using particle swarm optimization. Simulations with a three-machine power system under different disturbances demonstrate the effectiveness of the proposed controller design.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.88-94
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• 2008

In this paper, a design method of a missile guidance command is presented considering the dynamics of missile control systems. The design of a new guidance command is based on the well-known PNG(propotional navigation guidance) laws. The missile control system dynamics cause the time-delays of the PN guidance command and degrade the performance of original guidance laws which are designed under the assumption of the ideal missile control systems. Using a backstepping method, these time-delay effects can be compensated. In order to implement the guidance command developed by the backstepping procedure, it is required to measure or calculate the successive time-derivatives of the original guidance command, PNG and other kinematic variables such as the relative distance. Instead of directly using the measurements of these variables and their successive derivatives, a simple disturbance observer technique is employed to estimate a guidance command described by them. Using Lyapunov method, the performance of a newly developed guidance command is analyzed against a target maneuvering with a bounded and time-varying acceleration.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.24-34
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• 2008

A novel neural network model, termed the standard neural network model (SNNM), similar to the nominal model in linear robust control theory, is suggested to facilitate the synthesis of controllers for delayed (or non-delayed) nonlinear systems composed of neural networks. The model is composed of a linear dynamic system and a bounded static delayed (or non-delayed) nonlinear operator. Based on the global asymptotic stability analysis of SNNMs, Static state-feedback controller and dynamic output feedback controller are designed for the SNNMs to stabilize the closed-loop systems, respectively. The control design equations are shown to be a set of linear matrix inequalities (LMIs) which can be easily solved by various convex optimization algorithms to determine the control signals. Most neural-network-based nonlinear systems with time delays or without time delays can be transformed into the SNNMs for controller synthesis in a unified way. Two application examples are given where the SNNMs are employed to synthesize the feedback stabilizing controllers for an SISO nonlinear system modeled by the neural network, and for a chaotic neural network, respectively. Through these examples, it is demonstrated that the SNNM not only makes controller synthesis of neural-network-based systems much easier, but also provides a new approach to the synthesis of the controllers for the other type of nonlinear systems.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.4
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• pp.137-143
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• 2021

We propose an adaptive non-singular terminal sliding-mode control for the fast finite-time convergence (FANTSMC) in robot manipulator. The proposed FANTSMC approach is developed to be applied without singularity in robot manipulator, which has a new pole-placement control with the non-singular terminal sliding variable while generating the desirable control torque. Moreover, the switching gain is designed to suppress the time-delayed estimation error appropriately, which aims at providing the high robust tracking performance. Also, the proposed one employs one-sample delayed information to cancel out the system uncertainties and disturbances. For these reasons, it offers strong attraction within the finite time. It is shown that the tracking performance of the proposed FANTSMC approach is guaranteed to be uniformly ultimately bounded through the Lyapunov stability. The effectiveness of the proposed FANTSMC approach is illustrated in simulations, which is compared with that of the up-to-date control approach.

• Journal of applied mathematics & informatics
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• v.40 no.1_2
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• pp.47-59
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• 2022

This paper concerns the problem of simultaneous fault detection and disturbance reject control(SFDDRC) for a class of linear time-invariant system. In the framework of fault detection, residual generators are required to be robust to disturbances existing in the system. Different from most of the existing simultaneous fault and control(SFDC) methods, SFDDRC rejects the influences of disturbances on residual generators by disturbance observer-based control(DOBC). This not only effectively improves the accuracy of fault detection, but also solves the problem that most of the existing SFDC methods require that the disturbance must be bounded. Finally, a numerical example is given to verify the validity of the method.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.163-169
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• 2014

Using the classical cascade voltage control strategy, this paper proposes an analytical solution to an MPC (Model Predictive Control) problem with a hexagonal input constraint set for the inner-loop to regulate the output voltage of the UPS (Uninterruptible Power Supply). Focus is placed on how to deal with the hexagonal input constraint set without any approximation. Following the conventional cascade voltage control strategy, the PI (Proportional-Integral) controller is used in the outer-loop in order to regulate the output voltage. The simulation results illustrate that the capacitor voltage rapidly goes to its reference in a satisfactory manner while keeping other state variables bounded under an unexpected load changes.