An experimental application of time delay compensation techniques to distillation column control

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.

The kinetics of bioreactions often involve some uncertainties and the dynamics of the process vary during the course of fermentation. For such processes, conventional control schemes may not provide satisfactory control performance and demands extra effort to design advanced control schemes. In this study, a dynamic fuzzy model based predictive controller (DFMBPC) is presented for the control of a biochemical reactor. The DFMBPC incorporates an adaptive fuzzy modeling framework into a model based predictive control scheme to derive analytical controller output. The DFMBPC has the flexibility to opt with various types of fuzzy models whose choice also lead to improve the control performance. The performance of DFMBPC is evaluated by comparing with a fuzzy model based predictive controller (FMBPC) with no model adaptation and a conventional PI controller. The results show that DFMBPC provides better performance for tracking setpoint changes and rejecting unmeasured disturbances in the biochemical reactor.

Design of a Robust Fractional Order Controller for Burning Zone Temperature Control in an Industrial Cement Rotary Kiln

This paper presents a novel predictive control scheme with an enhanced Smith predictor for a networked control system with random time delays and system uncertainties. In the scheme, time axis is partitioned into equidistant small intervals to limit the continuous time varying delays into several discrete values. The stability of the networked control system is achieved by establishing an offline database and an online update strategy for Smith predictor, which reduces the reliance on the determined model of delay and system uncertainties in comparison with conventional Smith predictor. In this way, a sequence of finite forward predictive control signals of all possible time delays can be generated in advance and the actual delays will be compensated in real time when achieving the real delay information. Illustrative examples are given to demonstrate the effectiveness and robustness of the proposed predictive methods towards the random transmission delays and system uncertainties integrated in the networked control system.

A new simplified adaptive control scheme for multi-terminal HVDC transmission systems

In this work, a PI-P control strategy based on the coefficient diagram method (CDM) is proposed. The proposed CDM–PI-P control strategy is tested with the pH neutralization system. The system is modeled as first order plus time delay (FOPTD) transfer function using the experimental step test method. Closed loop simulations are carried out at two different critical operating points and the servo performance of the CDM–PI-P controller in terms of integral square error (ISE), integral absolute error (IAE), total variation (TV), and time domain specifications are reported. The results of the proposed control strategy are compared with other conventional PI control techniques.

Many issues can degrade the electrical drive performance such as cross-coupling, time delay, external disturbances, and parameter variation. The Synchronous Reference Frame (SRF) PI Current Controller (CC) is the most popular control scheme for the motor drive current control due to its simplicity. However, the PI controller does not have an optimal dynamic response due to the reasonably low transient response of the integral parts. Furthermore, the tuning of the PI controller depends heavily on the machine’s parameters. Recently, alternative control schemes such as Model Predictive Control (MPC) and Active Disturbance Rejection Control (ADRC) are studied due to their dynamic performance and disturbance rejection capability, respectively. This paper presents a comparative study between the conventional PI, ADRC, and MPC control schemes applied for Permanent Magnet Synchronous Motor (PMSM) taking into consideration the operational issues of electrical drives.

In industry or any area increasing load is a vast problem for power generation plants due to increase in demand for power. So making balance between generation and demand is the operating principle of load frequency control (LFC). The reliable operation of a large interconnected power system necessarily requires an Automatic Generation Control (AGC). The objective of AGC is to regulate the power output of Generators within a specified area in response to change in the system frequency, tie line power or relation of the two to each other, so as to maintain the scheduled system frequency and power interchange in the other are within the prescribed limits. This paper presents the use of conventional PI controller and artificial intelligence to study the load frequency control of interconnected power system. In the proposed scheme, a control methodology is developed using conventional PI controller and Fuzzy Logic controller (FLC) for interconnected hydro-thermal power system. The control strategies guarantees that the steady state error of frequencies and inadvertent interchange of tie-lines power are maintained in a given tolerance limitations. The performances of the controllers are simulated using MATLAB/SIMULINK package. A comparison of Fuzzy controller and PI controller based approaches shows the superiority of proposed Fuzzy logic controller for step change in loading conditions. The simulation results also tabulated as a comparative performance in view of settling time and peak over shoot.

In this paper, an optimal PID (proportional-integral-derivative) controller is designed for controlling the non-minimum phase system with time delay and performed greater than the conventional control approaches. When there is an increment in time delay then complications related to NMP system determines the undershoot response due to presence of zeros in the right half plane. Furthermore, Ziegler-Nichols, Internal Model Control (IMC) and Chien-Hrones & Reswick tuning approaches are developed for the conventional PID controller. The time-domain characteristics obtained are unable to persuade the requirements of the system. In order to improve the performance criteria, Smith’s predictor is used for controlling the NMP system. Smith’s predictor is better than the conventional PID controller techniques for tuning the parameters but has the incapability to achieve all the design requirements. For improving the performance requirements, the optimal PID controller is designed with the employment of Linear Quadratic Regulator (LQR). The tuning parameters of PID controller are optimal values using popular technique that is Linear Quadratic Regulator (LQR). In order to minimize integral time absolute error (ITAE) and integral time square error (ITSE), the tuning parameters are optimal and give precise values of rising time, peak time, % overshoot and settling time. The simulation results are obtained and according to that LQR gives better results than Smith Predictor and other conventional PID controller techniques.KeywordsNon-minimum phase systemPID controllerSmith predictorConventional tuning methodsLinear quadratic regulator

Cooperative adaptive cruise control (CACC) employs intervehicle wireless communications to safely drive at short intervehicle distances, which improves road throughput. The underlying technical requirement to achieve this benefit is formulated by the notion of string stability, requiring the attenuation of the effects of disturbances in upstream direction. The wireless communication delay, however, significantly compromises string stability. In order to compensate for time delays and thus reduce the minimum string-stable time gap, a Smith predictor can be applied. For application of a Smith predictor, the time delay needs to be in a series connection with the plant to be controlled, which is realized by introducing a master-slave architecture for CACC. As a result, information exchange appears to become bidirectional, while the control scheme still follows the one-vehicle look-ahead strategy. Feasibility of both the master-slave CACC strategy and the Smith predictor is explicitly analyzed. With the proposed control scheme, the minimum string-stable time gap can be significantly decreased, even considering communication delay uncertainty. The results are validated using simulations with a platoon of CACC-equipped vehicles.

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.

In speed control systems, which is desirable is that the speed of a controlled object should track the reference speed as fast as possible and at the same time should provide good robustness to load variations. As far as conventional PI controllers are concerned, once their parameters are tuned for solely one operating condition, they remain constant during the whole operational cycle and therefore, a poor controller performance may arise unexpectedly when the operating condition is changed. To overcome this problem, a PI controller incorporated by fuzzy logic controller (FLC) is introduced in this paper for the speed control of a permanent magnet synchronous motor (PMSM). In the proposed control schema, the parameters of the PI controller are determined online based on the error signal and its time derivative by means of a PD-type FLC, which has separate two rule bases, the former of which is responsible for P gain and the latter is for I gain. According to the computer simulations performed under the same conditions, the obtained results based on the proposed method are more promising than those obtained by the conventional PI controller with fixed parameters.

In order to improve the dynamic response and disturbance rejection performance of electric machines, a deadbeat predictive speed control (DPSC) scheme for a permanent magnet synchronous motor (PMSM) is proposed. To begin with, a DPSC controller was proposed with the purpose of achieving precise control for the next control cycle, and the control parameters were determined based on the optimal parameter design method. For better application, performance comparisons were made with a conventional PI control, and the mismatch effects of inertia and torque were analyzed. In order to improve the disturbance rejection performance of the system, an extended sliding mode observer (ESMO) was constructed to compensate for disturbances. Experimental verification with a conventional PI control indicates that the proposed DPSC control can reduce the speed response time from 0.675 s to 0.650 s. When the electric machine operates stably and is applied to a torque disturbance of 0.4 Nm, the speed fluctuation and settling time can be reduced from 9 rpm and 1.7 s to 6 rpm and 0.5 s, respectively. This proposed method effectively enhances the speed control performance of PMSM and can be applied to high-performance electric machine applications.

Optimal power extraction control schemes for five-phase PMSG based wind generation systems

Power conditioning system (PCS) is an interface between distributed generation and utility grid. It regulates voltage, current and power transmitted from the hybrid direct fuel-cell/turbine (DFC/T) power plant to utility grid. This paper presents a self-adaptive fuzzy PI controller of three phase inverter in PCS for the DFC/T power plant. One of the main tasks of PCS for distributed generations is power flow control. Traditionally, the control scheme for grid connected inverters is PI controller. However, PI control scheme would lead to large overshoot and long response time when the load increases sharply. Thus, a hybrid fuzzy PI control scheme is proposed in this paper in order to improve the power flow control. The fuzzy controllers can adjust the PI parameters according to the voltage error and the derivative of voltage error. The overall self-adaptive tuning fuzzy PI controller can update the PI parameters in real time, which makes the power flow control much more accurate than conventional PI controllers. Analysis and design methodologies of hybrid fuzzy PI controllers are presented in this paper. The model was developed in Matlab/Simulink environment. Simulation results show that the proposed control scheme can effectively reduce the overshoot and response time compared to the conventional PI controllers.