Controller Design with Dead Time Compensation for Distillation Column

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.

Distillation columns are the key units of several chemical refineries. It splits-up the constituents of liquid mixtures. Due to differences in volatilities, the vaporization of more volatile component takes place much quickly whereas the less volatile component remains behind in the solution. In this research article, control systems are designed for the considered transfer function model of the distillation column unit. Controllers are developed here using three different approaches viz. Ziegler-Nichols (Z-N) based PI controller, Fuzzy controller, and IMC controller, in MATLAB.

This study presents the development of dead-time compensator with Proportional Integral-Derivative (PID) controller and their implementation in real-time using the Programmable Logic Controller (PLC) on a heater-furnace system that constitute the temperature process. Though PID controller is effective to most of the processes, it has draw backs when used to control the processes with significant dead time. Therefore to eliminate the effects of long dead time, the dead-time compensator combined with PID is proposed. The control equation for the proposed dead time compensator is developed using the mathematical model of heater-furnace system and ladder logic program is created in GE Fanuc Versamax PLC. The PID controller is tuned using process reaction curve method and programmed in PLC. The proposed controller has an outer loop control mechanism with dead time compensator which feeds the inner loop PID controller. The effects of dead time on the performance of PID controller are eliminated through the outer loop control mechanism whose output does not contain modelling errors. The results of the proposed dead-time compensator with PID are compared with the results of the conventional PID controller without dead time compensation for both steady state response and servo-regulatory response. The results of the proposed controller show better improvement in the time domain specifications compared to conventional PID controller.

A simple relay feedback auto‐tuning method is proposed for the Smith predictor, an advanced controller for processes with long dead time. the relay feedback control gives information on one point of the Nyquist curve in terms of ultimate gain and frequency. With an additional measurement of the static gain, a reduced order process model in terms of a first‐ or second‐order dynamics plus dead time could be computed and used to auto‐tune the Smith predictor. When the process dynamics changes more frequently, a self‐tuning controller is required. In this case the Fast Fourier Transform technique can be further employed to track the points on the Nyquist curve by estimating the process frequency response and then used to update the Smith predictor. Excellent performance of the auto‐tuned and self‐tuned Smith predictor has been substantiated by simulations.

In networked control system, such as WirelessHART that is characterized by stochastic delay, the use of proportional integral and differential (PID) controllers is inadequate. This is because PID performs poorly in handling time-delay processes. The main reason for this poor performance is the limitation in the range of stable gain of the controller. Time delay causes oscillatory response of the PID with large gain. Likewise, sluggish response is experienced with small gain of the PID. Also, dead time compensators like smith predictor and internal model controller are difficult to be implemented practically since they require exact model of the process to be controlled. Therefore, this paper proposes the application of setpoint weighting strategy to be used alongside PID controller in a WirelessHART network. This method extends significantly the range of the PID gain, while providing good set point tracking and load regulation. From the simulation and experimental results obtained, the capability of the approach to load regulation and tracking can be seen in its fast recovery from effect of disturbance with minimal overshoot. Thus, a two degree of freedom control is achieved. Results also showed that the method is robust to real-time random variable network delay and model mismatches.

A novel manufacturing strategy based on continuous processing, integrated with online/inline monitoring tools, coupled with an advanced automatic feedback control system is highly desired for efficient Quality by Design (QbD)-based manufacturing of the next generation of pharmaceutical products with optimal consumption of time, space and resources. In this work, an advanced hybrid MPC-PID control system as well as a simpler PID controller for a direct compaction continuous tablet manufacturing process has been designed and implemented for a pilot-scale pharmaceutical process. An NIR sensor, an online NIR prediction tool, a PAT data management tool, an OPC communication protocol, a standard control platform and control hardware have been used to close the control loop. A systematic methodology to design and implement the control system has been also proposed. A control framework with features such as the option to run the plant in open-loop as well as in a closed-loop scenario has been developed. Furthermore, within the closed-loop scenario, options for a simpler PID, a dead time compensator (Smith predictor) as well as an advanced model predictive controller have been included. The feature to run the control strategy in simulation mode has been added to the control platform to facilitate virtual control system design and performance evaluation. Two case studies involving a direct compaction continuous tablet manufacturing process have been considered to demonstrate the closed-loop operation. Case Study 1 was completed at Rutgers University and constituted the use of a continuous cylindrical blender with a rotating screw. Case Study 2 was based on a continuous tumble mixer and was completed at the University of Puerto Rico—Mayaguez Campus (UPRM).

The Smith predictor, known as a dead time compensator, is extended to the control of a class of nonminimum phase processes called inverse response processes. An analytical design procedure is developed based on modern H/sub /spl infin// control theory. The resulting controller can provide not only the suboptimal frequency domain performance, but also the quantitative time domain specifications for step response. The performance and robustness of the closed loop system are discussed. For illustration, an example is also given to compare the proposed controller previous ones.

Intrinsic characteristics of distillation such as dead time and high nonlinearities do not allow the complete elimination of transient times when any external disturbance or set‐point change occurs. Thus, aiming at the use of easy‐tuning systems, a distributed‐action control in trays of a diabatic distillation unit with Smith's predictor was implemented in the Simulink environment to further reduce transient times and out‐of‐specification product. The distributed‐action strategy with Smith's predictor led to a reduction of 33.3 min (33 %) in the transient time of the top temperature control loop and 66 % in out‐of‐specification product, when compared with the conventional strategy, and thus is shown to be an efficient approach to increasing the productivity of distillation plants.

In this paper, a new modified Smith predictor using a rapid load estimator scheme is proposed. The advantage of the design is that the load estimator does not involve the solution of a closed-loop equation that contains dead time, and this can achieve a better load disturbance response. This scheme can be easily extended to the case of double integrators. Robust stability of the proposed method is analyzed, and a simple and effective robust controller design rule is derived. It is demonstrated by simulations that the new controller provides a similar or better setpoint response and a faster load disturbance rejection than the dead-time compensator in other papers.

Model based control algorithms are implemented when traditional control algorithms are inappropriate and fails to produce effective results. Smith predictor is an effective control structure to control process with high dead time. In this work, real time Smith Predictor algorithm is implemented to control a high dead time interacting tank process using LabVIEW. It requires a good knowledge about the process to extract the mathematical model. The model requires to capture the entire dynamics of the process so as to make the control algorithm more effective. In this work, open loop analysis is carried out to understand the dynamics of the plant and the model is extracted using empirical method. A first order plus dead time model (FOPDT) is considered and Smith Predictor structure is implemented to control the process. It is observed that the traditional PID control produces a sustained oscillation because of high dead time and Smith Predictor based control for the same PID parameters produces an effective control of the process.

This study introduces a reduced-order leg dynamic model to simplify the controller design and enhance robustness. The proposed multi-loop control scheme tackles tracking control issues in legged robots, including joint angle and contact-force regulation, disturbance suppression, measurement delay, and motor saturation avoidance. Firstly, model predictive control (MPC) and sliding mode control (SMC) schemes are developed using a simplified model, and their stability is analyzed using the Lyapunov method. Numerical simulations under two disturbances validate the superior tracking performance of the SMC scheme. Secondly, an Nth-order linear active disturbance rejection control (LADRC) is designed based on a simplified model and optimization problems. The second-order LADRC-SMC scheme reduces the contact-force control error in the SMC scheme by ten times. Finally, a fourth-order LADRC-SMC with a Smith Predictor (LADRC-SMC-SP) scheme is formulated, employing each loop controller independently. This scheme simplifies the design and enhances performance. Compared to numerical simulations of the above and existing schemes, the LADRC-SMC-SP scheme eliminates delay oscillations, shortens convergence time, and demonstrates fast force-position tracking responses, minimal overshoot, and strong disturbance rejection. The peak contact-force error in the LADRC-SMC-SP scheme was ten times smaller than that in the LADRC-SMC scheme. The integral square error (ISE) values for the tracking errors of joint angles θ1 and θ2, and contact force f, are 1.6636×10−28 rad2⋅s, 1.7983×10−28 rad2⋅s, and 1.8062×10−30 N2⋅s, respectively. These significant improvements in control performance address the challenges in single-leg dynamic systems, effectively handling disturbances, delays, and motor saturation.

A Dead Time Compensator Based on Linear Algebra (DTCLA)

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

Paralleled inverters are widely employed in permanent magnet synchronous machine (PMSM) drives to increase system capacity and reliability. Due to the discrepancy of paralleled inverters, the differential-mode circulating current (DMCC) is a major concern in paralleled inverters fed PMSM drives. The DMCC would result in current unbalance and efficiency reduction. To address this issue, a low-frequency DMCC suppression considering dead time compensation is proposed in this paper, which can be effective in the suppression of both DMCC and zero-sequence circulating current. In detail, the DMCC due to the discrepancy of control settings such as dead time and switching period, is eliminated by a proposed dead time compensation. Besides, the DMCC owing to the hardware differences including device voltage drops, device turn-on/off delays and filter inductances etc., is suppressed by a proposed regulation of phase conduction time, being free of disturbing the command voltage of drive system. Finally, the effectiveness of the proposed method is experimentally validated under both two-level and three-level space vector modulations.

In most of the industrial process plants, PI/PID controllers have been widely used because of its simple design, easy tuning, and operational advantages. However, the performance of these controllers degrades for the processes with long dead-time and variation in set-point. Up next, a PPI controller is designed based on the Smith predictor to handle dead-time processes by compensation technique, but it failed to achieve adequate performance in the presence of external noise, large disturbances, and higher-order systems. Furthermore, the model-based controllers structure is complex in nature and requires the exact model of the process with more tunable parameters. Therefore, in this research, a fractional-order predictive PI controller has been proposed for dead-time processes with added filtering abilities. The controller uses the dead-time compensation characteristics of the Smith predictor and the fractional-order controller's robustness nature. For the high peak overshoot, external noise, and disturbance problems, a new set-point and noise filtering technique is proposed, and later it is compared with different conventional methods. In servo and regulatory operations, the proposed controller and filtering techniques produced optimal performance. Multiple real-time industrial process models are simulated with long dead-time to evaluate the proposed technique's flexibility, set-point tracking, disturbance rejection, signal smoothing, and dead-time compensation capabilities.