Papers by Keyword: Adaptive Control

Abstract: An active noise-canceling casing is very attractive for reduction of sound generated bydevices. Such casing can provide good noise reduction for low frequencies, where a passive barrierwould be too thick for practical use. The classical active noise control approach, where the goal is tominimize the sound pressure level around multiple microphones outside the casing can be used. However,it requires placing external microphones, what makes the overall technical solution not acceptedfor many applications. The active vibration control, where the goal is to minimize vibrations of allplates, requires only sensors on the plates. However, in this solution, in turn, noise reduction resultsare worse. This paper presents employment of the idea of the virtual microphone-based approach toimprove results from the system based on vibration sensors only, which are used to estimate acousticpressure at specific locations in the acoustic field. By using a two-stage structure, the system is tunedto reconstruct the same vibrations of the plates, which were present when the acoustic pressure wereminimized directly in the square sense. A laboratory active noise-canceling casing used for experimentsis made of 5 actively controlled aluminum plates mounted on a steel frame. It is passivelyisolated from the floor. On each plate, three electrodynamical actuators are installed. The controlsystem is experimentally verified and obtained results are reported.

Abstract: The idea of active casing is an approach to reduce device and machinery noise by controlling vibration of casing walls. The sound insulation efficiency of this technique for a single-plate casing was confirmed by the authors in previous publications. However, under specific circumstances, a dedicated double-panel structure can yield even higher noise reduction. The aim of this paper is to propose and evaluate by means of laboratory experiments the performance of a double-panel casing in comparison with a single-panel casing. An adaptive control strategy based on the Least Mean Square (LMS) algorithm is used to update control filter parameters. A low-frequency noise in the range up to 250 Hz is considered. Obtained results are reported, discussed, and conclusions for future research are drawn.

Abstract: An active casing made of appropriately controlled vibrating plates can be used to reduce noise propagating from the mechanism enclosed in the casing. Since a practical vibrating casing can behave in a nonlinear way, the performance quality strongly depends on the ability of control filters to compensate for the nonlinearity. The classical approach to nonlinear active control, e.g. based on the Volterra filters, can deal with harmonics generated by the nonlinearity. However, when a complex structure is considered, neural networks have a higher potential. Although, they are much more computationally demanding, for some cases they can be simplified and still provide acceptable performance.In this paper, results of control obtained for a real casing with multiple actuators exciting each wall are presented and discussed.

Abstract: Shape memory alloy (SMA) actuators are promising for miniature applications. They accomplish the shape memorization via a temperature dependent phase transformation process. Control of SMA actuators is challenging because the actuators exhibit highly hysteresis behavior. This paper presents a fuzzy-based position control scheme for a SMA actuated mass system. The control system consists of an outer-and an inner-control loop. The inner loop controls the temperature of the SMA actuators using a PI controller, whereas the outer loop, which is affected by the hysteresis of the SMA actuators, controls the position. To deal with the hysteresis in the position control loop, an adaptive fuzzy sliding-mode control method is adopted. Experimental results illustrate the success of the proposed control scheme.

Abstract: It is necessary to change the parameters of PID controller if the parameters of plants change or there are disturbances. Particle swarm optimization algorithm is a powerful optimization algorithm to find the global optimal values in the problem space. In this paper, the particle swarm optimization algorithm is used to identify the model of the plant and the parameter of digital PID controller online. The model of the plant is identified online according to the absolute error of the real system output and the identified model output. The digital PID parameters are tuned based on the identified model and they are adaptive if the model is changed. Simulations are done to validate the proposed method comparing with the classical PID controller.

Abstract: The problem of a control system efficiency increasing for nonlinear plant control is considered. It is shown that proposed neural tuner based on neural networks is an efficient approach to solve the problem of PID-controller parameters online tuning. The backpropagation method is used to train the network. This method is modified by adding a rule base containing conditions on choosing learning rate for neurons. Experiments are made for plant models with various parameters values (with a time constant about 10³ seconds and 10¹ seconds). The required quality for each transient is determined. The system with the neural tuner allows to achieve 10% decreasing of the amount of time and 9% of energy-savings in comparison with the conventional PID-controller.

Abstract: In this paper, we demonstrate an application of unfalsified control to the nonlinear control of a pH neutralization in continuous stirred tank reactors under noisy measurements. The adaptation of controllers can be performed by two mechanisms: 1) The switching of an active controller in a current controller set and 2) An adaptive controller set generated by an evolutionary algorithm (EA) and a diversity operator. This leads to an automatic controller tuning for PI controller structure. Finally, we show that the proposed algorithm can handle highly nonlinear dynamics of the neutralization process with noisy measurements well.

Abstract: This paper develops an Adaptive fuzzy sliding-mode control system algorithm for active heat dissipation system. In the proposed intelligent controller, The adaptive laws adjust the parameters of the fuzzy logic system on-line based on a Lyapunov function, so that the stability of the system can be guaranteed. Additionally, an error estimation mechanism is investigated to estimate the bound of the approximation error. Based on NI-PXI system, this research combined the (TEC) with a duct heater. It designed a smart control system featured by the new active heat dissipation system. It has been proved that this research proposes the ideas of the active heat dissipation adaptive fuzzy sliding-mode control system which may reach a good condition provided with correct temperature control function. To be more precisely, that can be easily adaptive to any environment. It is equipped with a good capability of tracking and searching.

Abstract: The study proposed adaptive wavelet neural network controller can achieve good and precise welding control performance and use synchrotron radiation research center developed multi-gun group automatic welding system to verify the validity of the research method. Multi-gun group welding system is applied in Taiwan Photon Source (TPS). Storage ring aluminum alloy vacuum chamber of Taiwan Photon Source .In the past aluminum alloy vacuum chamber welding, it all depends on the empirical welding rule of operator to give appropriate welding current, argon flow, wire feed speed and welding speed for control. Therefore, the paper uses automatic welding skill, which takes National Instruments PXI-8180 system as basic structure, and adaptive wavelet neural network controlled four optimized parameters, I.E. welding current, wire feed speed, flow rate of argon gas and welding speed, The vacuum chamber pressure value is also up to 6.2X10-10Torr/mA. It is successfully applied to the TPS system. Therefore, it can prove the effectiveness and practicality of the method proposed in this study.

Abstract: Problem of a mobile object positioning in the presence of determinate disturbances is considered in this paper. A mobile object is described by kinematics and dynamics equations of a solid body in three dimensional space. The control inputs of the mobile object are forces and torques. Design of adaptive control is based on position-path control method for mobile objects. In this article two algorithms of the adaptive position-path control are developed. The first algorithm is adaptive position-path control with integration component and a reference model. The second algorithm is adaptive position-path control with a reference model and an extended mobile robot model. Block diagram of the direct adaptive position-path control system with a reference model is suggested. Design procedures of the adaptive position-path control systems and stability analysis of the closed-loop systems are presented. Computer simulation results of the designed adaptive closed-loop systems with both constant and variable disturbances are presented. On base of the analysis and modeling results conclusions are provided.