Presence Of Strong Disturbances Research Articles

Simultaneous convergence of position and orientation of wheeled mobile robots using trajectory planning and robust controllers

This article is devoted to the design of robust position-tracking controllers for a perturbed wheeled mobile robot. We address the final objective of pose-regulation in a predefined time, which means that the robot position and orientation must reach desired final values simultaneously in a user-defined time. To do so, we propose the robust tracking of adequate trajectories for position coordinates, enforcing that the robot’s heading evolves tangent to the position trajectory and consequently the robot reaches a desired orientation. The robust tracking is achieved by a proportional–integral action or by a super-twisting sliding mode control. The main contribution of this article is a kinematic control approach for pose-regulation of wheeled mobile robots in which the orientation angle is not directly controlled in the closed-loop, which simplifies the structure of the control system with respect to existing approaches. An offline trajectory planning method based on parabolic and cubic curves is proposed and integrated with robust controllers to achieve good accuracy in the final values of position and orientation. The novelty in the trajectory planning is the generation of a set of candidate trajectories and the selection of one of them that favors the correction of the robot’s final orientation. Realistic simulations and experiments using a real robot show the good performance of the proposed scheme even in the presence of strong disturbances.

Walking Motion Generation and Neuro-Fuzzy Control with Push Recovery for Humanoid Robot

Push recovery is an essential requirement for a humanoid robot with the objective of safely performing tasks within a real dynamic environment. In this environment, the robot is susceptible to external disturbance that in some cases is inevitable, requiring push recovery strategies to avoid possible falls, damage in humans and the environment. In this paper, a novel push recovery approach to counteract disturbance from any direction and any walking phase is developed. It presents a pattern generator with the ability to be modified according to the push recovery strategy. The result is a humanoid robot that can maintain its balance in the presence of strong disturbance taking into account its magnitude and determining the best push recovery strategy. Push recovery experiments with different disturbance directions have been performed using a 20 DOF Darwin-OP robot. The adaptability and low computational cost of the whole scheme allows is incorporation into an embedded system.

Composite disturbance rejection control for hydraulic classification

In the hydraulic classification, precise control for the flow rate of overflow water is vital to guarantee the uniformity and stability of the powder product size. Usually the multiple overflow tanks are supplied by a shared overflow pipeline, which gives rise to large coupling effects in the controls for the flow rates of multiple overflow tanks simultaneously. To solve this issue, it is necessary to keep the water pressure in the shared overflow pipeline accurately constant, which is not easy due to strong disturbances. Several control strategies have been proposed to control the constant water pressure. However, most of them (such as proportional-integral-derivative and model predictive control) reject disturbances just through feedback regulation and do not reject disturbances directly. This may cause poor control performances in the presence of strong disturbances. For improving the disturbance rejection performance, a control scheme based on proportional-integral-derivatives and disturbance observer is put forward in this paper. The scheme employs disturbance observer as feedforward compensation and a proportional-integral-derivative controller as feedback regulation. The disturbance rejection properties under both model mismatches and external disturbances are discussed. The test results illustrate that the proposed method can remarkably improve the disturbance attenuation property compared with the conventional proportional-integral-derivative method in the hydraulic classification process.

Composite control for raymond mill based on model predictive control and disturbance observer

In the raymond mill grinding process, precise control of operating load is vital for the high product quality. However, strong external disturbances, such as variations of ore size and ore hardness, usually cause great performance degradation. It is not easy to control the current of raymond mill constant. Several control strategies have been proposed. However, most of them (such as proportional–integral–derivative and model predictive control) reject disturbances just through feedback regulation, which may lead to poor control performance in the presence of strong disturbances. For improving disturbance rejection, a control method based on model predictive control and disturbance observer is put forward in this article. The scheme employs disturbance observer as feedforward compensation and model predictive control controller as feedback regulation. The test results illustrate that compared with model predictive control method, the proposed disturbance observer–model predictive control method can obtain significant superiority in disturbance rejection, such as shorter settling time and smaller peak overshoot under strong disturbances.

Continuous terminal sliding mode control with extended state observer for PMSM speed regulation system

In this paper, we discuss the speed regulation problem of permanent magnet synchronous motor (PMSM) servo systems. Firstly, a continuous terminal sliding mode control (CTSMC) method is introduced for speed loops to eliminate the chattering phenomenon while still ensuring a strong disturbance rejection ability for the closed-loop system. However, in the presence of strong disturbances, the CTSMC law still needs to select high gain which may result in large steady-state speed fluctuations for the PMSM control system. To this end, an extended state observer (ESO)-based continuous terminal sliding mode control method is proposed. The ESO is employed to estimate system disturbances and the estimation is employed by the speed controller as a feed-forward compensation for disturbances. Compared to the conventional sliding mode control method, the proposed composite sliding control method obtains a faster convergence and better tracking performance. Also, by feed-forward compensating system disturbances and tuning down the gain of the CTSMC law, the fluctuation of steady-state speed of the closed-loop system is reduced while the disturbance rejection capability of the PMSM system is still maintained. Simulation and experimental results are provided to demonstrate the superior properties of the proposed control method.

A High Performance Permanent Magnet Synchronous Motor Servo System Using Predictive Functional Control and Kalman Filter

A predictive functional control (PFC) scheme for permanent magnet synchronous motor (PMSM) servo systems is proposed in this paper. The PFC-based method is first introduced in the control design of speed loop. Since the accuracy of the PFC model is influenced by external disturbances and speed detection quantization errors of the low distinguishability optical encoder in servo systems, it is noted that the standard PFC method does not achieve satisfactory results in the presence of strong disturbances. This paper adopted the Kalman filter to observe the load torque, the rotor position and the rotor angular velocity under the condition of a limited precision encoder. The observations are then fed back into PFC model to rebuild it when considering the influence of perturbation. Therefore, an improved PFC method, called the PFC+Kalman filter method, is presented, and a high performance PMSM servo system was achieved. The validity of the proposed controller was tested via experiments. Excellent results were obtained with respect to the speed trajectory tracking, stability, and disturbance rejection.

A disturbance observer enhanced composite cascade control with experimental studies

The presence of strong disturbances usually causes great performance degradation of industrial process control systems. A disturbance observer (DOB) enhanced composite cascade control consisting of model predictive control (MPC), proportional-integral-derivative (PID) control, and DOB is proposed in this paper. DOB is employed here to estimate the severe disturbances and the estimated values are applied for feed-forward compensation, forming a composite control together with MPC. To evaluate the efficiency and validity of the proposed control structure, the simulation as well as experimental studies have been carried out for a level tank process which represents a typical first-order plus dead-time (FODT) industry process. Both the simulation and experimental results show that the proposed composite control method significantly improves the disturbance attenuation property of the MPC scheme in controlling such a typical industrial process.

Improved Disturbance Observer (DOB) Based Advanced Feedback Control for Optimal Operation of a Mineral Grinding Process

Advanced feedback control for optimal operation of mineral grinding process is usually based on the model predictive control (MPC) dynamic optimization. Since the MPC does not handle disturbances directly by controller design, it cannot achieve satisfactory effects in controlling complex grinding processes in the presence of strong disturbances and large uncertainties. In this paper, an improved disturbance observer (DOB) based MPC advanced feedback control is proposed to control the multivariable grinding operation. The improved DOB is based on the optimal achievable H2 performance and can deal with disturbance observation for the nonminimum-phase delay systems. In this DOB-MPC advanced feedback control, the higher-level optimizer computes the optimal operation points by maximize the profit function and passes them to the MPC level. The MPC acts as a presetting controller and is employed to generate proper pre-setpoint for the lower-level basic feedback control system. The DOB acts as a compensator and improves the operation performance by dynamically compensating the setpoints for the basic control system according to the observed various disturbances and plant uncertainties. Several simulations are performed to demonstrate the proposed control method for grinding process operation.

Speed Control for PMSM Servo System Using Predictive Functional Control and Extended State Observer

The speed regulation problem for permanent magnet synchronous motor (PMSM) servo system is studied in this paper. In order to optimize the control performance of the PMSM servo system, the predictive functional control (PFC) method is introduced in the control design of speed loop. The PFC-based speed control design consists of two steps. A simplified model is employed to predict the future q -axis current of PMSM. Then, an optimal control law is obtained by minimizing a quadratic performance index. However, it is noted that the standard PFC method does not achieve a satisfying effect in the presence of strong disturbances. To this end, an improved PFC method, called the PFC+ESO method, is developed. It introduces extended state observer (ESO) to estimate the lumped disturbances and adds a feedforward compensation item based on the estimated disturbances to the PFC speed controller. Simulation and experiment comparisons are made for these PFC methods and proportional-integral method with antiwindup control method to verify the effectiveness of the proposed methods.

Simulation and experiment on active vibration isolation with an adaptive method

An adaptive controller for active vibration isolation is proposed on the basis of the filtered- x least-mean-squares method and enhanced with an anti-saturation scheme. In this method, vibration responses induced by a multi-tonal disturbance are decomposed into harmonic components with in-parallel tracking filters and attenuated independently. The centre frequencies of the tracking filters are adjusted by the recursively estimated frequencies of signal components. The anti-saturation scheme is derived on the basis of the normalized least-mean-squares algorithm, which is adopted to prevent excessive adaptation of weights in the presence of strong disturbances. Simulation and experiment on an active vibration isolation system consisting of a cylindrical shell and four actuators are conducted to examine the performance of the given adaptive control algorithm. Results have demonstrated that the adaptive method is effective in vibration isolation as well as saturation suppression, and the performance of active vibration isolation is related closely to structural vibration modes when control channels in multi-channel active isolation are strongly coupled.

Disturbance rejection of ball mill grinding circuits using DOB and MPC

Ball mill grinding circuit is essentially a multivariable system with couplings, time delays and strong disturbances. Many advanced control schemes, including model predictive control (MPC), adaptive control, neuro-control, robust control, optimal control, etc., have been reported in the field of grinding process. However, these control schemes including the MPC scheme usually cannot achieve satisfying effects in the presence of strong disturbances. In this paper, disturbance observer (DOB), which is widely used in motion control applications, is introduced to estimate the disturbances in grinding circuit. A compound control scheme, consisting of a feedforward compensation part based on DOB and a feedback regulation part based on MPC (DOB–MPC), is thus developed. A rigorous analysis of disturbance rejection performance is given with the considerations of both model mismatches and external disturbances. Simulation results demonstrate that when controlling the ball mill grinding circuit, the DOB–MPC method possesses a better performance in disturbance rejection than that of the MPC method.

Disturbance observer based multi-variable control of ball mill grinding circuits

Ball mill grinding circuits are essentially multi-variable systems characterized with couplings, time-varying parameters and time delays. The control schemes in previous literatures, including detuned multi-loop PID control, model predictive control (MPC), robust control, adaptive control, and so on, demonstrate limited abilities in control ball mill grinding process in the presence of strong disturbances. The reason is that they do not handle the disturbances directly by controller design. To this end, a disturbance observer based multi-variable control (DOMC) scheme is developed to control a two-input-two-output ball mill grinding circuit. The systems considered here are with lumped disturbances which include external disturbances, such as the variations of ore hardness and feed particle size, and internal disturbances, such as model mismatches and coupling effects. The proposed control scheme consists of two compound controllers, one for the loop of product particle size and the other for the loop of circulating load. Each controller includes a PI feedback part and a feed-forward compensation part for the disturbances by using a disturbance observer (DOB). A rigorous analysis is also given to show the reason why the DOB can effectively suppress the disturbances. Performance of the proposed scheme is compared with those of the MPC and multi-loop PI schemes in the cases of model mismatches and strong external disturbances, respectively. The simulation results demonstrate that the proposed method has a better disturbance rejection property than those of the MPC and PI methods in controlling ball mill grinding circuits.

ROBUST PID/BACKSTEPPING CONTROL DESIGN FOR PERMANENT MAGNET SYNCHRONOUS MOTOR DRIVE

This paper presents a new control design procedure for permanent magnet synchronous motor (PMSM) speed drive in the case of unknown load torque. The control law is based on the combination of nonlinear proportional integral derivative (PID) regulators and the backstepping methodology. More precisely, we determine the controllers imposing the current-speed tracking in two recursive steps and by using appropriate PID gains that are nonlinear functions of the system state. Moreover, a frequency domain analysis is done to derive under what conditions PID controllers fulfil the robust mixed sensitivity performance condition when applied to PMSM. A comparative study between the proposed PID/backstepping approach and the feedback linearizing control is made by realistic simulation including load torque change, parametric variations, and measurement noise. The results of current-speed tracking show the effectiveness of the proposed method in the presence of strong disturbances. Finally, a virtual experimental setup is simulated to show the feasibility of our control algorithm in practice.

Regulation of the Emulsion Particle Size Distribution to an Optimal Trajectory Using Partial Least Squares Model-Based Predictive Control

This paper describes a statistical model-based control strategy for the regulation of the particle size distribution in emulsion copolymerization. A database is generated using both a mechanistic model and experimental data. A partial least squares method is applied at each sample time to generate the prediction model to be used in a predictive control algorithm. The proposed strategy is implemented in an experimental reactor in which the copolymerization of vinyl acetate/butyl acrylate is carried out. The controller is effective in updating the input trajectories to regulate the controlled distribution to a desired target in the presence of strong disturbances.

Commande non linéaire en cascade par modes glissants de la machine asynchrone

In this paper is developed cascaded non-linear sliding mode control (SMC) to ensure the flux-speed tracking regime of voltage fed induction machine. The control law is derived in two steps by exploiting backstepping methodology. In the first the virtual SMC, based on Lyapunov function, is derived in view to enforce the flux-speed tracking. Thereafter, is deduced the real sliding mode control imposing the virtual SMC law. Further, a robust control law is proposed to cope with parametric uncertainty and perturbations. The simulation results of flux-speed tracking of induction machine show the validity of the proposed method in presence of strong disturbances.

Prediction of Temperature in Vacuum Arc Remelting in the Presence of Strong Disturbances

A system for predictive, noninvasive temperature measurement in a broad class of manufacturing processes is presented. The system employs a comprehensive, three-tier signal processing algorithm to achieve high accuracy and reliability in the presence of strong disturbances. Temperature estimates are generated by ‘unstructured, shallow knowledge’ based algorithms. The estimation process employs a set of robust features obtained by signal processing that involves constitutive models representing ‘deep knowledge’ about the process dealt with. The application of these models is combined with ‘structured, shallow knowledge’ based techniques. Results obtained in application to the investment casting of titanium, which employs the vacuum arc remelting (VAR) process, are presented.

A Fault Tolerant and Jitter Free Dual Ring Fieldbus System with GPS Based Time Synchronization

A field bus architecture particularly designed for real time applications is described, in which the runtime performance cannot only be determined a priori, but also controlled during the entire process duration. Basically, it consists of a dual ring bus, in which two telegrams are transmitted on both channels in opposite directions, thus making delay measurements feasible. An ASIC timer module with an accuracy of 100μs is used for time synchronisation, which is fed by a GPS receiver. Only one GPS receiver is required in a system, because the timers of the bus nodes are synchronised via the field bus. By additional Hamming encoding of the telegrams, in each receiver errors can be corrected without requiring repetition of transfer. Additionally, the transfer of short data nibbles ensures high flexibility at different terminal equipment. Even in the presence of strong disturbances on the transmission channel, the Signal encoding by a modified "Frequency Shift Keying" method enables the receivers to securely recognise the input signals.

Industrial implementation of a real-time optimization strategy for maximizing production of LPG in a FCC unit

This paper describes the implementation of a new non-conventional real-time optimization strategy applied to the maximization of LPG production in a fluid catalytic cracking (FCC) converter in the refinery of São José dos Campos in Brazil. Focus is given on the difficulties of integrating optimization to existing controllers. The first commissioning tests are described in detail. They show that the benefits from optimization are not restricted to economic values. Implementation of the strategy gives directions on how to change the operating mentality of the plant operators. The implemented optimization strategy is shown to be able to maintain control of the plant even in the loss of several manipulated variables and in the presence of strong disturbances. Furthermore, we show that the optimization strategy is able to drive the process to new operational points.

Stabilization of Holographic Recording Systems with Intermittent Exposure Control

A new passive hologram stabilization method has been devised in which intermittent exposure control is used to ``stop'' the motion of the fringe field to be recorded. This system can be effectively employed as the sole stabilization method, or coupled with other known techniques to upgrade performance. The effectiveness of intermittent exposure control in the presence of strong disturbances is demonstrated by experimental results. Efforts concerning implementation options are also presented.