Modeling and Simulation for Motion Synchronization Control of Jacket Leveling Tool

Location of poles on the right hand side of s-plane for a process provides unstable behaviour. Obtaining desired output from an unstable process is truly a difficult task especially for processes with considerable dead time. Processes like combustion chamber, distillation column, and chemical reactors are well-known unstable processes with considerable time delay. Smith predictor based control technique is a well-known methodology for controlling such processes with considerable dead time. But, this technique fails to perform satisfactorily during transient as well as steady state operating phases for delay dominated unstable processes. To ensure improved close-loop response for delay dominated processes, Majhi and Atherton proposed modified Smith predictor technique. However, its performance is not found to be adequate, in addition tuning of more than one controller is quite complicated for delay dominated processes with pole located on right half plane. To overcome this limitation, here we propose a unified tuning methodology with simple modified Smith predictor scheme which is capable to provide an overall improved performance in terms of enhanced load recovery. Effectiveness of the proposed scheme is verified through simulation study with the well-known delay dominated unstable process models representing the behavior of chemical reactor and distillation column in comparison with conventional and modified Smith predictor methodologies.

Smith Predictor is very sensitive to uncertain system with variable time-delay. Using dual-locus diagram method, we first analyse the essence of Smith Predictor's sensitivity and present a proposition to illustrate the system stability criteria with relation to system gain and time-delay variation. Then a new modified Smith Predictor is proposed to compensate the variable time-delay system with uncertain model for set-point tracking. After that, we discuss the system internal stability and give two-degree freedom controller self-adaptive to eliminate the impact of system uncertainty with varying time-delay. Examples show the improved performance compared to previous Modified Smith Predictor structures.

Set point weighted modified Smith predictor for integrating and double integrating processes with time delay

The modified Smith predictor is well known as an effective time-delay compensator for a plant with large time delays, and several papers on the modified Smith predictor have been published. The parametrization of all stabilizing modified Smith predictors for minimum-phase time-delay plants is obtained by Yamada and Matsushima. In addition, Yamada et al. expanded the result by Yamada and Matsushima and proposed the parametrization of all stabilizing modified Smith predictors for non-minimum-phase time delay plants. However, no paper examines the parametrization of all stabilizing 2-degree-of-freedom modified Smith predictors that can specify the input-output characteristic and the feedback characteristic separately. From the practical point of view, it is desirable that the input-output characteristic and the feedback characteristic are specified separately. In this paper, we propose the parametrization of all stabilizing 2-degree-of-freedom modified Smith predictors for time-delay plants that can specify the input-output characteristic and the feedback characteristic separately.

Aiming at the problem of large overshoot and long response time of bidirectional DC/DC in the energy storage part of DC micro-grid, a fuzzy self-tuning PI controller is designed in this paper to realize online setting of control parameters and achieve the purpose of optimizing traditional PI control. The results show that fuzzy self-tuning PI control can effectively solve the problem of slow tracking voltage and fluctuation in dc micro-grid.

Three factors that complicate the position and orientation control of unmanned autonomous vehicles are the hardware-induced delays, delays caused by teleoperated modes of operation, and persistent disturbances such as wind. In this article, we study how to overcome these challenges by controlling a twin rotor multi-input, multi-output system. This nonlinear system has two degrees of freedom and significant cross-coupling, making its control particularly challenging. Time delay and external disturbances contribute to system instability and complicate flight control. The effects of time delay can be mitigated using the standard Smith predictor controller. However, this approach performs poorly when persistent disturbances are present. Our contribution is a modified Smith predictor that effectively mitigates disturbances. Additionally, a decoupler is employed to transform the system into two single-input, single-output models, enabling precise control of both the horizontal and vertical planes. The proposed method is implemented on a prototype and compared with the original Smith predictor-based control scheme. Experimental results validate the effectiveness of the proposed approach, showing that our approach reduces the steady-state tracking error to less than 2%, decreases settling time from 30 s to 20 s, and improves disturbance rejection under wind disturbance conditions by 35% compared to the standard Smith predictor. These results demonstrate the superior set-point tracking performance and enhanced disturbance rejection of the proposed approach.

EHL system does not need conventional hydraulic equipment. This is possible to save space and energy.EHL press machine is consisted of five components, such as master cylinder, slave cylinder, servomotor, ball screw, etc. Master cylinder and slave cylinder are coupled by fluid line. Master cylinder reciprocalmotion is made possible by suitable choice of area ratio of both cylinders. Slave cylinder is driven bymaster cylinder and the former force is amplified by the area ratio of the former and the latter. Accumulator is used for compensation of fluid expansion due to temperature change. Semi-closedcontrol of EHL press machine is simple but positioning accuracy is not sufficient due to compression offl uid. Therefore full closed control is required for good position accuracy. We tried application of thissystem to the clamping device of 10-ton load. By this combination, tact time becomes as small as 3second.

Generalized Pattern Search Methods for control of stable, unstable and integrating systems with unknown delay under step input

In order to effectively restrain the impact of network delays for wireless networked control systems (WNCS), aiming to time-variant, random and uncertain network delays and controlled plant might be time-variant or nonlinear, as well as Smith predictor models might be imprecise, we propose a novel approach that modified Smith predictor combined with fuzzy immune self-regulating PID control for the WNCS. Because modified Smith predictor does not include network delay models, therefore, it is no need for measuring on line, identifying or estimating network delays, thus it is applicable to some occasions that network delays are larger than one, even tens of sampling periods. Based on IEEE 802.11 b/g (WLAN), the results of simulation experiment show validity of the control scheme and improvement in dynamic performance and robustness of the WNCS.

In this paper, we develop a multimodel adaptive control strategy to be applied to delay compensation schemes for unstable systems. The strategy is based on intelligent control and the only requirement about the system is that the delay is unknown but bounded. The proposed approach can be used on any delay compensation scheme increasing the robustness of the system with respect to delay uncertainty. In particular, this paper considers the modified Smith Predictor (SP) for unstable and integrating systems with time-delay proposed by S. Majhi and D. P. Atherton. Simulation examples show the usefulness of implementing this strategy when the delay is unknown, showing that the scheme is capable of stabilizing the system with large delay and the good results obtained in the identification of the delay.

Active queue management (AQM) at routers can effectively control the queue length while keeping high throughput of routers. In this paper, a new AQM algorithm called Hang algorithm based on a modified Smith predictor is proposed. Theoretic analysis and extensive simulation shows that the developed control scheme is effective in dealing with transmission delay and other uncertainties. Comparison with traditional PI control and PI-Smith Predictor control is also conducted via NS2 simulation, and the results confirm the effectiveness of the proposed method in accounting for load disturbance and delay variation.

A number of tuning rules have been reported in literature for unstable first order plus time delay processes. However, at least to the author knowledge most of the reported methods fail to give robust performance for process models with time delay equal to or greater than the process time constant. In this work, a robust tuning method based on the modified Smith predictor is proposed for unstable first order plus time delay process models. Set point tracking controller is designed using direct synthesis approach. The PD controller which is used for load disturbance rejection is designed so as to satisfy the Routh Hurwitz's stability criterion. Suitable value of the tuning parameter is recommended after studying its effect on the system performance and robustness. This is also an advantage of the present work over the other recently reported strategies where suitable ranges of the tuning parameters' values are provided.

Flow-mediated interaction between a vibrating cylinder and an elastically-mounted cylinder

Optimal dead-time compensator design for stable and integrating processes with time delay

A new recurrent neural-network predictive feedback control structure for a class of uncertain nonlinear dynamic time-delay systems in canonical form is developed and analyzed. The dynamic system has constant input and feedback time delays due to a communications channel. The proposed control structure consists of a linearized subsystem local to the controlled plant and a remote predictive controller located at the master command station. In the local linearized subsystem, a recurrent neural network with on-line weight tuning algorithm is employed to approximate the dynamics of the time-delay-free nonlinear plant. No linearity in the unknown parameters is required. No preliminary off-line weight learning is needed. The remote controller is a modified Smith predictor that provides prediction and maintains the desired tracking performance; an extra robustifying term is needed to guarantee stability. Rigorous stability proofs are given using Lyapunov analysis. The result is an adaptive neural net compensation scheme for unknown nonlinear systems with time delays. A simulation example is provided to demonstrate the effectiveness of the proposed control strategy.