This paper presents an active noise control (ANC) algorithm using genetic algorithm with infinite impulse response (IIR) filter structure. Stochastic gradient algorithms such as least mean square (LMS) algorithm are c...
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This paper presents an active noise control (ANC) algorithm using genetic algorithm with infinite impulse response (IIR) filter structure. Stochastic gradient algorithms such as least mean square (LMS) algorithm are conventionally used for their simplicity and stability. But these algorithms have disadvantages of local minimum and large eigenvalue disparity of input signal's autocorrelation matrix. To solve those problems, several researches has been made to adaptive filtering schemes based on genetic algorithm. But their application is limited to the system that is able to know desired signal directly. In general active noise and vibration controlsystems are not be able to sense desired signal directly, so they have some difficulties or problems such that learning sample set is proportional to population size. Proposed active controller is composed of genetic controllers that can learn by one sample set per one generation. This structure can be properly applied to active controlsystem. computer simulations show that proposed genetic structured IIR active controller has more optimal result to feedforward active noise controlsystems.
This paper presents analysis of the effect of actuation on the combustor dynamics. Two different categories of actuators are studied: flow sources, e.g., acoustic speakers, and heat sources, e.g., fuel injectors. Thes...
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This paper presents analysis of the effect of actuation on the combustor dynamics. Two different categories of actuators are studied: flow sources, e.g., acoustic speakers, and heat sources, e.g., fuel injectors. These sources are modeled in the conservation equations and a finite dimensional model is obtained. Two methods of analysis are used to gain insight into the physics of actuation, and its stabilizing/destabilizing effect on the combustor through feedback control. The first is the energy method which is used here in a novel way to explain intricate work exchanges between the different dynamic components of the system: the acoustics, the flame, and the actuator. The energy analysis is used also to quantify the `useful' and `wasted' work generated by actuators. A more revealing method of analysis is the dynamic representation of the combustor as an oscillator, and is shown to be the basis of any optimal control analysis.
One of the typical nonlinear system is a pendulum. Cause of difficulties of controlling a pendulum is miss-matching of number between inputs and outputs , that is to say, single input, and double outputs. The feature ...
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One of the typical nonlinear system is a pendulum. Cause of difficulties of controlling a pendulum is miss-matching of number between inputs and outputs , that is to say, single input, and double outputs. The feature of a pendulum is nonlinear as to angle and linear as to cart position. Another point, is that state equations do not have terms of position of a cart. In addition, the angle of a pendulum must satisfy the dynamic equation at horizontal line. In order to swing up a pendulum of these properties, first, we define a reference angle of a pendulum which satisfies the dynamic equation at horizontal line. After the pendulum goes up around upright position, we change the curve of reference angle so that the pendulum standstill at the origin. In other word, when the pendulum system becomes a linear time-invariant system, we define the ideal curves of both angle and position which will converge to the origin. The angle of the pendulum is controlled by SFC (Simulator-based Foresight control) all the way which can be applicable for a non-affine nonlinear system.
Fault detection, diagnosis, and accommodation play an important role in the operation of autonomous robotic systems. Incipient faults in the actuators, sensors or in the dynamics of a robotic manipulator can lead to d...
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Fault detection, diagnosis, and accommodation play an important role in the operation of autonomous robotic systems. Incipient faults in the actuators, sensors or in the dynamics of a robotic manipulator can lead to deterioration in performance and unsafe operating conditions. This paper presents a robust nonlinear fault diagnosis scheme for detecting and approximating faults occurring in a class of nonlinear multi-input multi-output systems. The proposed approach utilizes on-line approximators and adaptive nonlinear filtering techniques to obtain estimates of the fault functions. Performance of the nonlinear fault diagnosis scheme is analyzed by investigating its robustness and fault sensitivity properties in the presence of slowly developing or abrupt faults. A simulation example is presented to illustrate the ability of the fault diagnosis scheme to detect faults in a single link robotic manipulator with a revolute elastic joint.
Consistent demands on semiconductor manufacturers to produce circuits with increased density and complexity have made stringent process control an issue of growing importance in the industry. Recent work has shown tha...
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Consistent demands on semiconductor manufacturers to produce circuits with increased density and complexity have made stringent process control an issue of growing importance in the industry. Recent work has shown that neural networks offer great promise in modeling complex fabrication processes such as reactive ion etching (RIE). Motivated by these results, this paper explores the use of neural networks for real-time, model-based feedback control of RIE. This objective is accomplished in part by constructing a predictive model for the system, which can be inverted (or approximately inverted) to achieve the desired control. The efficacy of this approach is demonstrated using experimental data from a SiO2 etch process to simulate real-time control of etch rate, uniformity, selectivity, and anisotropy. In addition, using a residual gas analysis system as a sensor, the approach is further demonstrated using actual experimental data acquired during the etch of a GaAs/AlGaAs metal-semiconductor-metal structure. In the latter case, real-time control of the etch rate of the constituent materials is investigated.
Conceptually, Fuzzy Logic, which has drawn a great deal of attention recently, possesses the quality of simplicity. However, its early applications relied on trial and error in selecting either the fuzzy membership fu...
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Conceptually, Fuzzy Logic, which has drawn a great deal of attention recently, possesses the quality of simplicity. However, its early applications relied on trial and error in selecting either the fuzzy membership functions or the fuzzy rules. This made it depend rather too heavily on expert knowledge which may not always be available. Hence, a self-tuning or an adaptive Fuzzy Logic controller (FLC) such as Adaptive Neuro-Fuzzy Inference system (ANFIS) removes this stringent requirement. This paper demonstrates the application of ANFIS to a 160 Mw nonlinear Multi-Input Multi-Output (MIMO) steam boiler-turbine unit. The space of operating conditions of the plant is partitioned into five regions. For each of the regions an optimal controller is designed. The resulting five linear controllers are used to train the ANFIS. Simulation results showed that the fuzzy controller closely reproduced the optimal performance in each of the design points and surpassed any single linear controller in these operating regions. These results also revealed the robustness of the FLC to parameter variations.
This paper describes an innovative adaptive fuzzy control (AFC) algorithm for regulating the room temperature in a hydronic heating system. The hydronic heating system consists of a boiler that provides central heatin...
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This paper describes an innovative adaptive fuzzy control (AFC) algorithm for regulating the room temperature in a hydronic heating system. The hydronic heating system consists of a boiler that provides central heating water to a radiator or radiators in a home or apartment. Room temperature is regulated with a motor that drives a variable-position valve on each radiator that controls the flow of hot water through the radiator. The AFC automatically learns the steady-state radiator valve positions for five operating set points and uses this information in a fuzzy controller that commands the radiator valve position. Laboratory tests under typical operating conditions show that the AFC simultaneously improves the control quality while reducing the battery consumption when compared with a conventional proportional-integral (PI) feedback controller. For a 70-hour laboratory test with typical operating set points, the control quality increased 32% while the estimated battery consumption decreased 36%. The AFC's memory and processing requirements are suitable for embedded microprocessors, so it is a realistic replacement for a conventional PID algorithm.
Longitudinal and lateral control of heavy duty trucks for vehicle following is presented. A manually driven leading truck is followed at a very small distance by another truck automatically. No additional road infrast...
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Longitudinal and lateral control of heavy duty trucks for vehicle following is presented. A manually driven leading truck is followed at a very small distance by another truck automatically. No additional road infrastructure is necessary. For longitudinal and lateral control, information about the relative position of the leading and following truck is determined by an onboard image processing system. Additionally, a vehicle to vehicle communication system gives information about the state of the leading truck. Longitudinal control has a two layered structure. In the inner control loop, a model based nonlinear acceleration controller linearizes the essential nonlinearities of the drive train. Based on this linearization, the outer control loop (a linear state space controller) controls a small and safe distance to the leading truck. Lateral control is done by an electronic tow bar approach where the rear truck follows the same track as the leading truck. Practical results with two 40 tonne semitrailer trucks are given.
The final step in zinc hydrometallurgy is the electrolytic process. The most important parameters to control the process are the concentrations of zinc and sulfuric acid in the electrolyte. This paper proposes an expe...
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The final step in zinc hydrometallurgy is the electrolytic process. The most important parameters to control the process are the concentrations of zinc and sulfuric acid in the electrolyte. This paper proposes an expert control strategy for determining and tracking the optimal concentrations, which uses neural networks, rule models and a single-loop control scheme. First, the process is described and the strategy that features an expert controller and three single-loop controllers is explained. Next, neural networks and rule models are constructed based on statistical data and empirical knowledge on the process. Then, the expert controller for determining the optimal concentrations is designed through a combination of the neural networks and rule models. The three single-loop controllers use the PI algorithm to track the optimal concentrations. Finally, the results of actual runs using the strategy are presented. They show that the strategy provides not only high-purity metallic zinc, but also significant economic benefits.
This paper deals with a walking of a biped robot which has ankle joints without motor. Ankle joints have been built using springs and mechanical constraints, which gives a flexibility of joint within a certain range a...
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This paper deals with a walking of a biped robot which has ankle joints without motor. Ankle joints have been built using springs and mechanical constraints, which gives a flexibility of joint within a certain range and a stiffness beyond the range. The biped with passive ankles proposed here gives a good contact between its sole and the ground and makes foot landing soft. As a result, installing force sensors for measuring the center of gravity of the biped becomes easier. Weight and cost of legs are also reduced. As the cost of the advantages, however, the control problem becomes more difficult because the torque of the ankle joint to put the biped in a desired walking gait cannot be provided from the passive ankle joint. To solve this problem, we proposed a dynamic gait modification method by adjusting the position of a hip joint. Experimental results with the minor modification of the SD-2 robot in the Ohio State University are given to show the validity of the proposed controller.
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