Minimal Control Synthesis Algorithm Research Articles

Modeling and disturbance suppression for spacecraft solar array systems subject to drive fluctuation

The vibration of flexible solar array during sun-tracking drive has been one of the challenging problems in modern space technology. In this work, the vibration disturbance of the drive induced solar array vibration (DISAV) to spacecraft platform is studied. A vibration disturbance model considering both the effect of rigid-flexible coupling and the drive unstable excitation is established for a typical solar array system. It extends the traditional dynamic model of the solar array system in terms of an explicit description for the vibration disturbance. Then, an external torque compensation scheme considering both vibration suppressing and driving reliability is proposed based on a failure-protection magnetorheological actuator. The extended minimal control synthesis algorithm is adopted to achieve the compensatory torque for vibration suppression. The numerical results indicate that the energy of the vibration disturbing the spacecraft is mainly provided by the unstable drive while the flexible vibration diffuses the disturbance. And the vibration disturbance suppression should be a main task for the vibration control during the sun-tracking drive. The reliability and effectiveness of the DISAV control with a magnetorheological actuator are theoretically demonstrated from the aspect of the failure protection and active control. The maximum disturbance torque is reduced up to 68.75% during the normal sun-tracking, which demonstrates the good suppression of DISAV by the proposed torque compensation scheme.

Experimental validation of a continuous-time MCSI algorithm with bounded adaptive gains

Model reference adaptive control algorithms with minimal controller synthesis have proven to be an effective solution to tame the behaviour of linear systems subject to unknown or time-varying parameters, unmodelled dynamics and disturbances. However, a major drawback of the technique is that the adaptive control gains might exhibit an unbounded behaviour when facing bounded disturbances. Recently, a minimal controller synthesis algorithm with an integral part and either parameter projection or σ-modification strategies was proposed to guarantee boundedness of the adaptive gains. In this article, these controllers are experimentally validated for the first time by using an electro-mechanical system subject to significant rapidly varying disturbances and parametric uncertainty. Experimental results confirm the effectiveness of the modified minimal controller synthesis methods to keep the adaptive control gains bounded while providing, at the same time, tracking performances similar to that of the original algorithm.

Simulation and experimental tests on active mass damper control system based on Model Reference Adaptive Control algorithm

In the process of sudden natural disasters (such as earthquake or typhoon), the active mass damper (AMD) system can reduce the structural vibration response optimally, which serves as a frequently applied but less mature vibration-reducing technology in wind and earthquake resistance of high-rise buildings. As the core of this technology, the selection of control algorithm is extremely challenging due to the uncertainty of structural parameters and the randomness of external loads. It is not necessary for the Model Reference Adaptive Control (MRAC) based on the Minimal Controller Synthesis (MCS) algorithm to know in advance the structural parameters, which produces special advantages in conditions of real-time change of system parameters, uncertain external disturbance, and the nonlinear dynamic system. This paper studies the application of the MRAC into the AMD active control system. The principle of MRAC algorithm is recommended and the dynamic model and the motion differential equation of AMD system based on MRAC is established under seismic excitation. The simulation analysis for linear and nonlinear structures when the structural stiffness is degenerated is performed under AMD system controlled by MRAC algorithm. To verify the validity of the MRAC over the AMD system, experimental tests are carried out on a linear structure and a structure with variable stiffness with the AMD system under seismic excitation on the shake table, and the experimental results are compared with those of the traditional pole assignment control algorithm.

Minimal Control Synthesis Algorithm for Panel Vibration Control

Minimal control synthesis (MCS) algorithm with good compensation ability for fast disturbances is used to suppress the vibration of piezoelectric panel. The first two modes model of controlled piezoelectric panel are set up by experiment. LQR method is selected as the reference model. Simulation results show that this method have good stability, faster convergence performance and strong anti-interference ability under transient disturbances or persistent disturbances excitation.

Adaptive Tracking Control of a Common Rail Injection System for Gasoline Engines: A Discrete-Time Integral Minimal Control Synthesis Approach

Over the last decade, gasoline direct injection engines have proven to be a promising solution to reduce both emission and fuel consumption. The achievement of superior performance strongly relies on its fuel injection system based on the common rail (CR) device. In order to tame the CR pressure dynamics without any a priori knowledge of the plant parameters, we design a novel model reference adaptive control strategy that extends the discrete-time minimal control synthesis algorithm. Indeed, an explicit discrete-time adaptive integral action is added to improve closed-loop performance. Experimental results support the analytical proof of stability, and confirm the effectiveness of the novel algorithm to solve both the regulation and the tracking control problem in a wide range of working conditions. The closed-loop performance is quantitatively evaluated via engineering indices.

Experimental validation of the discrete-time MCS adaptive strategy

This paper is concerned with the implementation and experimental validation of a discrete-time model reference adaptive control strategy, known as Minimal Control Synthesis (MCS) algorithm. After discussing the proof of stability of the algorithm when applied to discretized models of continuous-time plants, the problem of controlling a highly nonlinear electro-mechanical device is taken as a representative case of study. It is shown that the discrete-time MCS is an effective strategy to solve the problem while guaranteeing robustness to unmodeled nonlinear dynamics over a wide range of test manoeuvres.

Minimal controller synthesis algorithms with output feedback and their generalization

This paper proposes several improvements in the minimal controller synthesis algorithms, which were developed for a class of nonlinear systems with uncertainties. The major proposition is that only the output feedback is enough to control some nonlinear systems without an observer while the existing algorithms require the complete state feedback. Next, the extended version and the parameter identication technique of the minimal controller synthesis algorithm are combined in a single method estimating some more parameters for some known forms of nonlinearities. This is applicable with or without the improvement of removing the need for using the complete state feedback. It is proven that the scaling factors in the algorithms can be variable and dierent for each component. The algorithms are applicable to some noncanonical forms of systems. All the propositions and some of the existing algorithms are generalized in a single form with some options. A speed-sensorless DC motor control simulation is also included with quite exaggerated noisy conditions and the results verify that the proposed modications make the minimal controller synthesis algorithms much more ecient model reference adaptive control algorithms for certain types of systems. The

Experimental implementation and validation of a novel minimal control synthesis adaptive controller for continuous bimodal piecewise affine systems

This paper presents the first digital implementation of a novel model reference adaptive scheme for the control of continuous bimodal piecewise affine systems. The algorithm is based on the minimal control synthesis algorithm, originally developed as a MRAC for smooth systems. The resulting adaptive algorithm is a switched feedback controller able to cope with uncertain continuous PWA systems. The analogue continuous-time control law is implemented by using a digital low-cost commercial microcontroller. The aim is to control a piecewise-linear electrical circuit. The experimental validation process is made challenging by the presence of measure uncertainties, noise, quantization errors, unmodeled nonlinear dynamics and computational delays. Experiments confirm the effectiveness of the controller to cope with switching in the circuit dynamics, establishing the strategy as a viable control tool. Nevertheless, the experimental analysis provides a first insight into the robustness of the algorithm.

Implementation of electrohydraulic shaking table controllers with a combined adaptive inverse control and minimal control synthesis algorithm

This study presents a combined control strategy for electrohydraulic shaking table (EST) systems. The position frequency bandwidth of the EST system is so low that it results in a worse tracking accuracy during seismic tests, particularly when the frequency bandwidth of the desired position signal exceeds the frequency bandwidth of the EST position closed-loop system. In order to improve the position tracking accuracy, a combined control strategy is proposed, which utilises a recursive extended least square (RELS) algorithm to offline or online estimate the position closed-loop transfer function of the EST system, then uses the estimated transfer function to offline or online yield a feedforward inverse controller for extending the position frequency bandwidth, finally, employs a minimal control synthesis (MCS) algorithm to further improve the tracking performance of the EST position system. The proposed control strategy combines the merits of offline or online feedforward inverse compensation and adaptive control. The procedure of the proposed control strategy is programmed in MATLAB/Simulink, and is then compiled to a real-time PC with Microsoft Visual Studio.NET for implementation. A better tracking performance for the proposed control strategy is achieved in experiments by using actual EST.

Discrete-Time MRAC with Minimal Controller Synthesis of an Electronic Throttle Body

AbstractHyperstability-based model reference adaptive controllers that use a Minimal Controller Synthesis (MCS) algorithm are known in the literature as MCS controllers. The adaptation gains that arise in the continuous-time MCS algorithm are nonlinear and, as a consequence, practical implementations have to be carried out in a digital fashion. However, the discrete-time versions of the MCS that have been used so far for implementation purposes are not proved to be asymptotically stable for plants from second order up. Recently, some of the authors have developed a hyperstable, discrete-time MCS algorithm with a formal proof of asymptotic stability for generic n-dimensional plants that can be used to control discretized continuous-time plants. This paper deals with the implementation and performance analysis of this algorithm to the problem of controlling an electronic throttle body in automotive engineering.

Discrete-time minimal control synthesis adaptive algorithm

This article proposes a discrete-time Minimal Control Synthesis (MCS) algorithm for a class of single-input single-output discrete-time systems written in controllable canonical form. As it happens with the continuous-time MCS strategy, the algorithm arises from the family of hyperstability-based discrete-time model reference adaptive controllers introduced in (Landau, Y. (1979), Adaptive Control: The Model Reference Approach, New York: Marcel Dekker, Inc.) and is able to ensure tracking of the states of a given reference model with minimal knowledge about the plant. The control design shows robustness to parameter uncertainties, slow parameter variation and matched disturbances. Furthermore, it is proved that the proposed discrete-time MCS algorithm can be used to control discretised continuous-time plants with the same performance features. Contrary to previous discrete-time implementations of the continuous-time MCS algorithm, here a formal proof of asymptotic stability is given for generic n-dimensional plants in controllable canonical form. The theoretical approach is validated by means of simulation results.

Stability and accuracy analysis of a discrete model reference adaptive controller without and with time delay

AbstractAdaptive control techniques can be applied to dynamical systems whose parameters are unknown. We propose a technique based on control and numerical analysis approaches to the study of the stability and accuracy of adaptive control algorithms affected by time delay. In particular, we consider the adaptive minimal control synthesis (MCS) algorithm applied to linear time‐invariant plants, due to which, the whole controlled system generated from state and control equations discretized by the zero‐order‐hold (ZOH) sampling is nonlinear. Hence, we propose two linearization procedures for it: the first is via what we term as physical insight and the second is via Taylor series expansion. The physical insight scheme results in useful methods for a priori selection of the controller parameters and of the discrete‐time step. As there is an inherent sampling delay in the process, a fixed one‐step delay in the discrete‐time MCS controller is introduced. This results in a reduction of both the absolute stability regions and the controller performance. Owing to the shortcomings of ZOH sampling in coping with high‐frequency disturbances, a linearly implicit L‐stable integrator is also used within a two degree‐of‐freedom controlled system. The effectiveness of the methodology is confirmed both by simulations and by experimental tests. Copyright © 2009 John Wiley & Sons, Ltd.

Minimal Control Synthesis Adaptive Control of Continuous Bimodal Piecewise Affine Systems

This paper is concerned with the derivation of a model reference adaptive control (MRAC) scheme for bimodal piecewise-affine (PWA) continuous systems. The algorithm is based on an extension of the minimal control synthesis algorithm, originally developed as an MRAC for smooth systems. The resulting adaptive algorithm is a switched feedback controller able to cope with uncertain continuous PWA systems. The proof of stability, based on the newly developed passivity theory for hybrid systems, is provided and the effectiveness of the new proposed control is shown on a representative example.

Adaptive control of rigid body satellite

The minimal controller synthesis (MCS) is an extension of the hyperstable model reference adaptive control algorithm. The aim of minimal controller synthesis is to achieve excellent closed-loop control despite the presence of plant parameter variations, external disturbances, dynamic coupling within the plant and plant nonlinearities. The minimal controller synthesis algorithm was successfully applied to the problem of decentralized adaptive schemes. The decentralized minimal controller synthesis adaptive control strategy for controlling the attitude of a rigid body satellite is adopted in this paper. A model reference adaptive control strategy which uses one single three-axis slew is proposed for the purpose of controlling the attitude of a rigid body satellite. The simulation results are excellent and show that the controlled system is robust against disturbances.

Strain measurement under the minimal controller synthesis algorithm and an extensometer design

In this paper, minimal controller synthesis (MCS) algorithm is used in the case of strain measurement for the first time. The MCS control is an adaptive control method and it can be recommended as a robust controller for the servohydraulic materials testing machine. The algorithm coped with various specimens, which have different materials and diameters. The control accuracy is important in materials testing due to the fact that even smaller overshoots or undershoots can cause undesirable results in cyclic loading. For this reason, the controller parameters needs to adjusted according to the changes in the plant parameters for acceptable plant output responses. In order to measure strain signal a simple LVDT extensometer was designed. In this set tests, two different specimens were used: aluminium alloy specimens of diameter 10 mm and EN24T steel specimens of diameter 7 mm. The MCS control was implemented in two degrees of freedom form and produced very satisfactory plant output responses owing to the fact that the results produced by the control are in the range of actual values. This indicates that the MCS control can be used in strain measurement very effectively. It may also indicate the possibility of using the MCS control other materials testing applications like strain control and temperature cycle tests.

Adaptive Control of Generalised Dynamically Substructured Systems

The use of the dynamically substructured systems (DSS) approach for engineering testing environments is receiving significant global interest. DSS enables a full-size, critical component to be physically tested within a laboratory environment, whilst the remaining part(s) of the entire system are modelled as a real-time numerical simulation. This paper will present a generalised substructuring framework, using a practical example for illustration. Correspondingly, a linear substructuring control (LSC) strategy is presented, together with a development of the adaptive minimal control synthesis (MCS) algorithm. Comparative simulation results of the two DSS control strategies are also included.

Application of Minimal Control Synthesis Algorithm to Pneumatic Positioning Control System

Application of Minimal Control Synthesis Algorithm to Pneumatic Positioning Control System

Adaptive Control Strategy for Dynamic Substructuring Tests

Real-time dynamic substructuring, or hybrid testing, is a technique that enables experimental testing of critical elements of a complete structure. The structure in question is decomposed into at least two parts: the critical element, which is physically tested, and the remainder of the structure, which is modeled numerically. For accurate replication of the system to be emulated, the two parts must interact, via a controller to compensate for the actuator dynamics, in real-time, and with minimal errors at their interfaces. During development, the adaptive minimal controller synthesis (MCS) algorithm controller has previously been implemented for substructuring of a one-degree-of-freedom mass-spring-damper system. The potential advantage that MCS has over a traditional linear controller is its lack of reliance on detailed knowledge of the experimental specimen dynamics. This paper presents the MCSmd control strategy, an improved MCS-based strategy for substructure testing, using a modified demand (md) signal. Experimental and simulation studies of the MCSmd controller applied to a two-degree-of-freedom mass spring damper system are presented along with an analysis of the transient gain behavior.

Comparative implementation studies of the minimal controller synthesis algorithm on an electrohydraulic actuator plant

Electrohydraulic servosystems have large extent of model uncertainties and generally difficult to control. The current paper studies the application of the direct adaptive minimal controller synthesis (MCS) algorithm to an electrohydraulic positioning system. Comparative implementation studies are presented of a typical servohydraulic positioning system, as used in aerospace applications. The performance of the MCS controller is evaluated through experimental and analytical studies. In order to investigate the robustness of the MCS control, the system is operated away from nominal working condition (by changing the supply pressure and/or accumulators settings) and the performances of both the MCS control and the proportional plus derivative feedback (P + DFB) controller were compared. The results show that MCS is fairly insensitive to parameter variations, unmodelled dynamics and external disturbances, yielding much better response characteristics, compared with those of a conventional P + DFB controller.

The feedforward minimal control synthesis algorithm and its application to the control of shaking-tables

Since the early 1990s, research in Europe, the Far East, and America on the control of shaking-tables for seismic investigations has been made all the more urgent, following a series of catastrophic earthquakes across the globe. The fidelity of the results from shaking-table tests, on which many designs of earthquake-proof systems depend, is largely governed by the accuracy of the controlled motion of the table and the test structure. Coincident with these events has been the development of more advanced, adaptive, control systems that provide an opportunity for high-precision motion control in the face of dynamic interaction, non-linearity, and parameter variation within the test system. This paper discusses a new adaptive control algorithm, called the feedforward minimal control synthesis (FFMCS) algorithm, which offers improved shaking-table control, when used in conjunction with a more conventional fixed-gain controller. FFMCS has been developed as part of a joint Japan-UK initiative, motivated by prior testing of shaking-tables located in both Japan and Europe. This paper describes the dynamic modelling of a typical shaking-table, in order to emphasize the key features required of its controller. Also detailed are the three-variable control (TVC) strategy, a conventional algorithm that is widely used within shaking-table test facilities, together with the development and stability proof of the FFMCS algorithm. A motivating and comparative implementation study of FFMCS on the control of a simple single-axis servohydraulic rig is also included, as well as comparative simulation studies on the previously modelled shaking-table.