This paper proposes a reconfigurable controller design method for multivariable systems, which is capable of dealing with order-change problems that may occurs in an after-fault system. A new method is proposed to rec...
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One of the main challenges of any related paradigms in systems engineering is being able to handle complex systems under unforeseen uncertainties. A system may be called complex if its dimension (order) is too high an...
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ISBN:
(纸本)0780397886
One of the main challenges of any related paradigms in systems engineering is being able to handle complex systems under unforeseen uncertainties. A system may be called complex if its dimension (order) is too high and its model (if available) is nonlinear, interconnected, and information on the system is so uncertain that classical techniques cannot easily handle the problem. A system of systems (SoS) is a "super system," or an integration of complex systems coordinated together in such a way as to achieve a wider set of goals with possible higher significance such as global warming, Mars missions, air traffic control, global earth observation system, etc. computational Intelligence or Soft Computing, a consortium of fuzzy logic (approximate reasoning), neuro-computing (learning), genetic algorithms and genetic programming (optimization), has proven to be a powerful set of tools for adding autonomy and semi-autonomy to many complex systems. For such systems the size of soft computing control architecture will be nearly infinite. In this presentation, paradigms using soft computing approaches are utilized to design autonomous controller with controller reuse for a number of space applications. The notion of adaptation in autonomous controller reuse can be handled via intelligent tools to add on additional capabilities in real-time scenarios. Learning from past experience is but one such scenario for the reuse of autonomous controllers. These applications include satellite array formations, robotic agents and the Virtual Laboratory (V-LAB®) for multi-physics modeling and simulation. A view of the future activities of the NASA JPL for space exploration will also be given. SoS concepts will be described and a few testbed cases will be introduced, including a robotic swarm with dynamic sensor networks for homeland security at UTSA ACE center. Some animated and experimental implementation movies will be shown.
In this paper, we propose an embedded multi-task scheduling system to make the wireless brain computer interface to real-time receive electroencephalogram signal more accurate. This method we propose also can increase...
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This paper proposes a reconfigurable control system design methodology using the sliding-mode control. The advantage of the proposed sliding-mode reconfigurable control methodology is that it is more robust than the s...
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Dear editor,How to deal with uncertainties and/or disturbances is a central issue pushing the development of both control science and control technology. Among various approaches, the active disturbance rejection cont...
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Dear editor,How to deal with uncertainties and/or disturbances is a central issue pushing the development of both control science and control technology. Among various approaches, the active disturbance rejection control (ADRC) has been successfully implemented in various industrial practices because of its uniqueness in concepts, simplicity
This paper presents an effective adaptive controller for revolute joints robot manipulator where the control input is accompanied with a random disturbance (with unknown PSD). It is clear that, disturbance can comprom...
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In this paper we present a design scheme for output tracking of nonlinear systems that are subject to regular perturbations. We show that applications of singular perturbation theory to the input-output feedback linea...
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In this paper we present a design scheme for output tracking of nonlinear systems that are subject to regular perturbations. We show that applications of singular perturbation theory to the input-output feedback linearization technique provides a systematic method to identify the slow "dominant" states and fast "negligible" states. Similar to the backstepping design technique, a suitable state variable is converted into a "control like" variable which in the steady state is forced to approach the desired tracking control law for the reduced order system. We show that this design achieves stable approximate tracking of reasonable reference trajectories for nonlinear systems that are "dominantly" minimum phase. The order of approximation can be arbitrarily improved by addition of correction terms in the control law. The main advantage of this approach is that the design is often performed for a much simpler model which is linear in the new control variable and describes the dominant part of the original system by ignoring some of the fast states that are forced to have little effect on the steady state performance.< >
We present a control strategy that combines local state feedback laws and open-loop schedules to robustly globally asymptotically stabilize a compact subset (typically a point) of the state space for a nonlinear syste...
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We present a control strategy that combines local state feedback laws and open-loop schedules to robustly globally asymptotically stabilize a compact subset (typically a point) of the state space for a nonlinear system. The control algorithm is illustrated on the problem of global stabilization of the upright position of the pendubot and implemented in a hybrid controller containing logic variables and logic rules with hysteresis. We also present the design procedure of the hybrid controller for general nonlinear systems. Recent results in the literature on robustness of asymptotic stability in hybrid systems are used in establishing that the closed-loop system is robust to measurement noise and other external disturbances.
We present robust stabilization results for constrained, discrete-time, nonlinear systems using a finite-horizon model predictive control (MPC) algorithm that does not require any particular properties for the termina...
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We present robust stabilization results for constrained, discrete-time, nonlinear systems using a finite-horizon model predictive control (MPC) algorithm that does not require any particular properties for the terminal cost. We introduce a property that characterizes the robustness properties of the MPC optimization problem. Assuming the system has this property (for which we give sufficient conditions), we make two further key assumptions. These are that the value function is bounded by a K/sub /spl infin// function of a state measure (related to the distance of the state to some target set) and that this measure is detectable from the stage cost used in the MPC algorithm. We show that these assumptions lead to stability that is robust to sufficiently small disturbances and measurement noise. While in general the results are semiglobal practical, when the detectability and upper bound assumptions are satisfied with linear K/sub /spl infin// functions, the stability and robustness is global with respect to the feasible set. We discuss algorithms employing terminal equality or inequality constraints. We provide two examples, one involving a terminal equality constraint and the other involving a nonrobustness-inducing state constraint.
We review some of the existing results on the Lyapunov design of robustly stabilizing feedback laws for uncertain nonlinear systems. Using the concept of a robust control Lyapunov function, we present robust backstepp...
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We review some of the existing results on the Lyapunov design of robustly stabilizing feedback laws for uncertain nonlinear systems. Using the concept of a robust control Lyapunov function, we present robust backstepping tools and demonstrate how they can be used in systematic design procedures.< >
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