Combined Feedback-feedforward Control Research Articles

Combined Feedback Feedforward Control of a 3-Link Musculoskeletal System Based on the Iterative Training Method.

The investigation and study of the limbs, especially the human arm, have inspired a wide range of humanoid robots, such as movement and muscle redundancy, as a human motor system. One of the main issues related to musculoskeletal systems is the joint redundancy that causes no unique answer for each angle in return for an arm's end effector's arbitrary trajectory. As a result, there are many architectures like the torques applied to the joints. In this study, an iterative learning controller was applied to control the 3-link musculoskeletal system's motion with 6 muscles. In this controller, the robot's task space was assumed as the feedforward of the controller and muscle space as the controller feedback. In both task and muscle spaces, some noises cause the system to be unstable, so a forgetting factor was used to a convergence task space output in the neighborhood of the desired trajectories. The results show that the controller performance has improved gradually by iterating the learning steps, and the error rate has decreased so that the trajectory passed by the end effector has practically matched the desired trajectory after 1000 iterations.

Combined feedback–feedforward control of Ćuk CCM converter for achieving fast transient response

The Ćuk converters operating in continuous conduction mode (CCM) can be preferred in applications such as microprocessor power delivery and pulsed load because these circuits have advantages of being able to step up/down, a small number of power components, and low input/output current ripples. However, they show poor transient performance due to right-half-plane-zeros (RHPZs) in the closed-loop transfer function of the Ćuk CCM converter. To enhance the transient response, a combined feedback–feedforward control for the Ćuk CCM converter is proposed. The proposed control scheme comprises a feedback control signal based on a Lyapunov function and a duty-ratio feedforward control signal. A Lyapunov-function-based controller (LBC) achieves fast dynamic response even under large-signal variations from the operating point. The duty ratio feedforward controller (DFFC) is developed to predict the effect of the disturbances and compensate it, while alleviating the burden of LBC. The proposed control logic makes the closed-loop system of the Ćuk CCM converter globally exponentially stable and thus provides a fast transient response even under large-signal variations. To construct the proposed controller, the authors make use of the large-signal averaged model of the Ćuk CCM converter, and consider the parasitic elements. To verify the proposed control scheme, numerical simulations and experimental tests are conducted.

Triiodothyronine secretion in early thyroid failure: The adaptive response of central feedforward control.

Defined by thyroid-pituitary feedback control, clinical diagnosis of hypothyroidism and hyperthyroidism has become synonymous with TSH measurement. We combined in silico analysis and in vivo data to explore the central influences on thyroidal T3 production. A system of five coupled first-order nonlinear parameterised ordinary differential equations (ODEs) is used to model the feedback control of TSH and TRH by thyroid hormones together with the feedforward control of thyroidal T3 secretion and enzymatic T4-T3 conversion. Dependencies of the stable equilibrium solutions of this ODE system, that is the homeostasis of the underlying physiological process, on the system parameters were investigated whether they accounted for clinical observations. During the modelled transition to hypothyroidism, central control imposed an increasing influence in maintaining serum FT3 levels, compared to peripheral conversion efficiency. Numerical continuation analysis revealed dependencies of T3 production on different elements of TSH feedforward control. While T4-T3 conversion provided the main T3 source in euthyroidism, this was overtaken by increasing glandular T3 secretion when thyroid reserve declined. The computational results were in good agreement with data from untreated patients with autoimmune thyroiditis. Dependencies revealed in the expression of control differ in thyroid health and disease, using a physiologically based mathematical model of combined feedback-feedforward control of the hypothalamic-pituitary-thyroid regulation. Strong T3-protective mechanisms of the control system emerge with declining thyroid function, when glandular T3 secretion becomes increasingly influential over conversion efficiency. This has wide-ranging implications for the utility of TSH in clinical decision-making.

Robust μ-Synthesis With Dahl Model Based Feedforward Compensator Design for Piezo-Actuated Micropositioning Stage

In this article, a combined feedback-feedforward control design scheme is presented to enhance the tracking performance of a piezo-actuated micropositioning stage by compensating the nonlinear hysteretic behavior of the piezoelectric actuator and model uncertainties of the system. Detailed investigation of the presented control scheme is performed not only in simulation by analyzing the robust stability and robust performance but also in real-time with motion trajectories of multiple frequencies. To design the presented control scheme, first of all, the dynamic model of the system is identified from the real-time experimental data by using the recursive least squares parameter adaptation algorithm. Then, Dahl hysteresis model is considered to represent the nonlinear hysteretic behavior of the piezoelectric actuator. To deal with this hysteresis nonlinearity, Dahl feedforward compensator is designed without involving inverse model calculations to avoid any computational complexity. This feedforward compensator is then combined with $\mu $ -synthesis robust feedback controller which is designed in the presence of model uncertainties of the system. The presented control scheme ensures the boundedness of the closed-loop signals and the desired tracking performance of the considered micropositioning stage. Finally, experimental tests are conducted with motion trajectories of multiple frequencies for the validation of the control scheme. An average improvement of 95% in compensating the hysteresis nonlinearity and 80% in reducing the tracking error is achieved which demonstrates the efficacy of the presented control scheme.

Performance evaluation of a blade-mounted LiDAR with dynamic versus fixed parameters through feedback-feedforward individual pitch and trailing edge flap control

This paper investigates combined feedback-feedforward control of a wind turbine using a blade-mounted telescope LiDAR sensor to measure the inflow wind speed. The objective of this paper is to evaluate the controller performance with fixed telescope parameters compared to the wind speed dependent dynamically changing telescope parameters. First the telescope parameters for both cases are determined, then the robust feedback controllers are extended with an inverse-based feedforward individual pitch and trailing edge flap controller to alleviate the 1P and 2P loads of the flapwise blade root bending moments. A minor performance degradation is observed with the fixed telescope parameters in comparison to the dynamic telescope parameters.

A unified design for feedback-feedforward control system to improve regulatory control performance

The PID controller is widely used in industries because of its simplicity and robustness. A simple approach to improve regulatory control performance is to combine both feedback PID and feedforward controllers. The feedforward controller enables early compensation of a measured disturbance before it can seriously affect the process. The conventionally derived non-ideal feedforward controllers are not often used in practice. The reason is that an ideal feedforward controller based on direct inversion of process model is often not physically realizable. Several non-ideal feedforward control designs have been proposed where some of them involve rather intensive tuning procedure to obtain good disturbance rejection. In this paper, we present a new systematic method for designing a combined feedback-feedforward control system. The proposed design method is easy to use and applicable to stable, unstable and integrating deadtime processes where the ideal feedforward controller is physically not realizable.

Counteracting the accidental pollutant propagation in a section of the River Someş by automatic control

Real-time response to accidental pollution in rivers is a challenging mission that requires efficient on-line monitoring and rapid mitigating systems and calls for automatic control for diminishing or eliminating the pollutant effect. Remediation measures are addressed for cases in which the pollutant concentration can be measured and a neutralising agent can be identified and added to react with the pollutant and transform it by a chemical reaction into less harmful or non-harmful products. Pollution in a section of the River Someş is presented as a case study. Based on the advection-dispersion-reaction processes, a 2D dynamic simulator is developed to investigate and provide accurate predictions of the pollutant distribution. The complex river section geometry, the single and multiple points or spatially distributed sources, and a constant or time-varying release of the pollutant may be handled by the simulator. Furthermore, two control systems are designed and tested. One system involves implementing a feedback control approach, while the other involves applying a feedforward-feedback control structure. System identification of the disturbance and the manipulated variable paths is carried out, and a suitable allocation of the measuring points for both the disturbance and the controlled variable is addressed and demonstrated. The control structures prove to help the proposed polluting counteracting measures by bringing the concentration of the pollutant down to the safe setpoint value. The predictive action of the feedforward-feedback control structure reveals complementary benefits, as the pollutant concentration is promptly forced and maintained below the maximum allowed limit all the time and all over the river region of interest.

Combined Feedback–Feedforward Control of Wind Turbines Using State-Constrained Model Predictive Control

An application of model predictive control (MPC) to the wind turbine collective pitch and torque control problem in full-load operation is presented. The applied controller is able to include upstream wind speed information, e.g., from light detection and ranging measurements. Furthermore, a method is presented to include constraints on the turbine states in the problem formulation, such as on rotor speed, even in the presence of unmeasured disturbances. In a simulation study, the effects of both preview control and state constraints are evaluated for three different scenarios: normal operation, gusts, and grid-loss load cases. It is found that preview control provides significant benefits in normal operation and under gust conditions. It is further found that including state constraints in the MPC formulation can be used to avoid unnecessary shutdowns due to the violation of the overspeed limit or to control the turbine effectively when the turbine needs to run at a reduced level of generator torque.

A low density, high stiffness flat loudspeaker with combined feedback-feedforward response correction

This paper presents a novel perforated flat loudspeaker with improved sound frequency response by applying velocity feedback control. Flat loudspeakers provide advantages of compact dimensions and high durability. Known flat loudspeaker technology is based on high model density. However, the resonances in the panel are complex and difficult to control, which often leads to complicated computations and insufficient low frequency response. The flat loudspeaker in this paper comprises a novel panel structure, which offers low density, high stiffness, and efficient space utilization. Direct velocity feedback control provides a simple and stable control loop. We apply the multiple direct velocity feedback control method to obtain flat sound frequency response. Furthermore, a Linkwitz filter is applied to our system to increase response at very low frequencies. Experimental results show that a multiple combined feedback-feedforward control method effectively improves the performance of the flat loudspeaker with extended low-frequency response.

Theory and application of a combined feedback–feedforward control and disturbance observer in linear motor drive wire-EDM machines

This paper presents a combined two-degree-of-freedom controller and disturbance observer design for a direct drive motion control system actuated by permanent-magnet linear synchronous motors (PMLSM). A feedback controller based on pole-placement design method is proposed to achieve desired tracking performance as well as stabilize the closed-loop system. A newly designed feedforward controller is proposed to reduce tracking errors based on an inverse model of the direct drive system. A digital disturbance observer is implemented to be included in the proposed feedback–feedforward control structure to compensate for nonlinear friction, cogging effects, and external load disturbance. Furthermore, the proposed control scheme has been verified as being internally stable. Experimental results indicate that the proposed controller can achieve a high contouring accuracy of ±0.3 μm as well as provide disturbance rejection and robustness. The maximum contour error of circular trajectory was reduced from 8.5 to 3.2 μm in comparison with proportional-integral-derivative (PID) controller.

Adaptive Feedback–Feedforward Control of Building Structures

This paper proposes a combined feedback–feedforward control algorithm for reducing structural response of buildings to seismic excitations. The controller contains both feedback and feedforward components. The feedback component is assumed to be the same as that found from traditional linear quadratic regulator design. The feedforward component is obtained by estimating the external excitation as a series of step functions at each time increment. This feedforward gain varies with the duration of the step function used for estimation and converges as the time duration increases. Thus, a finite number of precalculated gains can be used to represent the potential feedforward gain profile. At any instant in time, the excitation is measured and by using the past measurements, the most effective feedforward gain for the recorded excitation values can be selected from the set of precalculated gains. This value is used as the feedforward gain for the current time step. Numerical examples are presented to show the effectiveness of this adaptive control scheme. The effects of varying the control objectives, the updating time for the feedforward gain, and the number and location of actuators are studied.

A Model Predictive Control framework for robust management of multi-product, multi-echelon demand networks

Model Predictive Control (MPC) is presented as a robust, flexible decision framework for dynamically managing inventories and meeting customer requirements in demand networks (a.k.a. supply chains). As a control-oriented framework, an MPC-based planning scheme has the advantage that it can be tuned to provide acceptable performance in the presence of significant uncertainty, forecast error, and constraints on inventory levels, production and shipping capacity. The translation of the supply chain problem into a formulation amenable to MPC implementation is initially developed for a single-product, two-node example. Insights gained from this problem are used to develop a partially decentralized MPC implementation for a six-node, two-product, three-echelon demand network problem developed by Intel Corporation that consists of interconnected assembly/test, warehouse, and retailer entities. Results demonstrating the effectiveness of this Model Predictive Control solution under conditions of demand forecast error, constraints on capacity, shipping and release, and discrepancies between actual and reported production throughput times (i.e. plant-model mismatch) are presented. The Intel demand network problem is furthermore used to evaluate the relative merits of various information sharing strategies between controllers in the network. Both the two-node and Intel problems show the potential of Model Predictive Control as an integral component of a hierarchical, enterprise-wide planning tool that functions on a real-time basis, supports varying levels of information sharing and centralization/decentralization, and relies on combined feedback–feedforward control action to enhance the performance and robustness of demand networks. These capabilities ultimately mitigate the “bullwhip effect” in the supply chain while reducing safety stocks to profitable levels and improving customer satisfaction.

Cross-coupling design of generalized predictive control with reference models

In this paper, a cross-coupled generalized predictive control algorithm is proposed with reference models on inputs and outputs of the process. It is shown that such an algorithm provides a combined feedback-feedforward control resulting in pole-zero cancellation of poles which do not correspond to the reference models. Hence, the system behaves asymptotically as the reference model provided that the cancelled poles are stable. In addition, the cross-coupling control action introduced in an optimal way will effectively reduce the synchronization deviations of processes with multiple motion axes. The proposed algorithm is applied to the control of a servo-system with two motion axes, and simulation results show that the control algorithm gives improved performance.

On a generalized predictive control algorithm

Generalized predictive control algorithms with reference models on imputs and outputs of the process have been proposed recently in the literature. Thise algorithms are extended by introducing suitable weighting factors in the performance index and it is shown that such algorithms provide a combined feedback feedforward control resulting in pole-zero cancellation of poles which do not correspond to the reference model. Hence, the system behaves asymptotically as the reference model provided the cancelled poles are stable. Therefore, a careful analysis of the stability of those poles in still needed.