Many vehicle manufacturers have lately introduced advance driver support in some of their automobiles. One of those new features is Adaptive Cruise Control DACCE, which extends the conventional cruise control system to control of relative speed and distance to other vehicles. In order to design an ACC controller it is suitable to have a model of driver behavior. The approach in the thesis is to use system identification methodology to obtain dynamic models of driver behavior useful for ACC ap...
Full Text Available This paper describes the Adaptive Cruise Control system (ACC, a system which reduces the driving burden on the driver. The ACC system primarily supports four driving modes on the road and controls the acceleration and deceleration of the vehicle in order to maintain a set speed or to avoid a crash. This paper proposes more accurate methods of detecting the preceding vehicle by radar while cornering, with consideration for the vehicle sideslip angle, and also of controlling the distance between vehicles. By making full use of the proposed identification logic for preceding vehicles and path estimation logic, an improvement in driving stability was achieved.
Larsen, Kim Guldstrand; Mikučionis, Marius; Taankvist, Jakob Haahr
In a series of contributions Olderog et al. have formulated and verified safety controllers for a number of lane-maneuvers on multilane roads. Their work is characterized by great clarity and elegance partly due to the introduction of a special-purpose Multi-Lane Spatial Logic. In this paper, we...... want to illustrate the potential of current modelchecking technology for automatic synthesis of optimal yet safe (collision-free) controllers. We demonstrate this potential on an Adaptive Cruise Control problem, being a small part of the overall safety problem considered by Olderog....
Willigen, W.H. van; Schut, M.C.; Kester, L.J.H.M.
This paper is concerned with safety in (cooperative) adaptive cruise control systems. In these systems, the speed of the cars is maintained automatically, based on the preferred speed of the driver and the speed of the preceding car. Technologies that are used in these systems, such as radar and rad
Ahn, Dae Ryong; Yang, Ji Hyun; Lee, Sang Hun [Kookmin University, Seoul (Korea, Republic of)
Recent development in science and technology has enabled vehicles to be equipped with advanced autonomous functions. ADAS (Advanced Driver Assistance Systems) are examples of such advanced autonomous systems added. Advanced systems have several operational modes and it has been observed that drivers could be unaware of the mode they are in during vehicle operation, which can be a contributing factor of traffic accidents. In this study, possible mode confusions in a simulated environment when vehicles are equipped with an adaptive cruise control system were investigated. The mental model of the system was designed and verified using the formal analysis method. Then, the user interface was designed on the basis of those of the current cruise control systems. A set of human-in-loop experiments was conducted to observe possible mode confusions and redesign the user interface to reduce them. In conclusion, the clarity and transparency of the user interface was proved to be as important as the correctness and compactness of the mental model when reducing mode confusions.
Corona, D.; De Schutter, B.
The design of an adaptive cruise controller for a SMART car, a type of small car, is proposed as a benchmark setup for several model predictive control methods for nonlinear and piecewise affine systems. Each of these methods has been already applied to specific case studies, different from method t
Klunder, G.; Li, M.; Minderhoud, M.
In 2006 in the Netherlands, a field operational test was carried out to study the effect of adaptive cruise control (ACC) and lane departure warning on driver behavior and traffic flow in real traffic. To estimate the effect for larger penetration rates, simulations were needed. For a reliable impac
Full Text Available The beginning of the 21st century sees auto makers pursuing research in advanced features like collision warning and avoidance system into their product. Automotive cruise control system has been undergoing development in EU since the PROMETHEUS programme in the late 1980’s, and has currently metamorphous into Adaptive Cruise Control (ACC technology which is presently emerging in the automotive market as a convenience function intended to reduce driver workload. Adaptive cruise control is the first of the new generation of advanced driver’s assistance devices to reach the market, which partially automates the driver’s task and bringing the drivers comfort into perspective. It allows the host vehicle to maintain a set speed and distance from preceding vehicles by a forward object detection sensor. The forward object detection sensor is the focal point of the ACC system, which determines and regulates vehicle acceleration and deceleration through a powertrain torque control system and an automatic brake control system. This study presents overview of adaptive cruise control system, operation principles and the advantages of integrating ACC system in automobiles. Also, the system must be stable for optimum performance, and stability of a close loop system which the cruise system is an example, was determined by calculating the controller gain (K1, K2, K3 and substituting into the characteristic equations. The stability of a close loop system for the values of K1, K2 and K3 when substituted into the characteristic equation produced a negative real part. To achieve stability in close loop systems, all the poles must have negative real values and this is in line with the values obtain for p1, p2 and p3. From the pole zero plots of 1 = (-7 ± 7.14, 2 = (-7± 11.60 and 3 = (-0.08 and -13.91, stability of the system was achieved
Arem, van, Bart; Driel, van, J.; Visser, Ruben
Cooperative adaptive cruise control (CACC) is an extension of ACC. In addition to measuring the distance to a predecessor, a vehicle can also exchange information with a predecessor by wireless communication. This enables a vehicle to follow its predecessor at a closer distance under tighter control. This paper focuses on the impact of CACC on traffic-flow characteristics. It uses the traffic-flow simulation model MIXIC that was specially designed to study the impact of intelligent vehicles o...
Park, Jong-Yong; Kim, Nakwan
The auto-berthing of a ship requires excellent control for safe accomplishment. Crabbing, which is the pure sway motion of a ship without surge velocity, can be used for this purpose. Crabbing is induced by a peculiar operation procedure known as the push-pull mode. When a ship is in the push-pull mode, an interacting force is induced by complex turbulent flow around the ship generated by the propellers and side thrusters. In this paper, three degrees of freedom equations of the motions of crabbing are derived. The equations are used to apply the adaptive backstepping control method to the auto-berthing controller of a cruise ship. The controller is capable of handling the system nonlinearity and uncertainty of the berthing process. A control allocation algorithm for a ship equipped with two propellers and two side thrusters is also developed, the performance of which is validated by simulation of auto-berthing.
Winter, de Joost C.F.; Happee, Riender; Martens, Marieke H.; Stanton, Neville A.
Adaptive cruise control (ACC), a driver assistance system that controls longitudinal motion, has been introduced in consumer cars in 1995. A next milestone is highly automated driving (HAD), a system that automates both longitudinal and lateral motion. We investigated the effects of ACC and HAD on d
Winter, J.C.F. de; Happee, R.; Martens, M.H.; Stanton, N.A.
Adaptive cruise control (ACC), a driver assistance system that controls longitudinal motion, has been introduced in consumer cars in 1995. A next milestone is highly automated driving (HAD), a system that automates both longitudinal and lateral motion. We investigated the effects of ACC and HAD on d
Wang, Pangwei; Wang, Yunpeng; Yu, Guizhen; Tang, Tieqiao
For the Cooperative Adaptive Cruise Control (CACC) Algorithm, existing research studies mainly focus on how inter-vehicle communication can be used to develop CACC controller, the influence of the communication delays and lags of the actuators to the string stability. However, whether the string stability can be guaranteed when inter-vehicle communication is invalid partially has hardly been considered. This paper presents an improved CACC algorithm based on the sliding mode control theory and analyses the range of CACC controller parameters to maintain string stability. A dynamic model of vehicle spacing deviation in a platoon is then established, and the string stability conditions under improved CACC are analyzed. Unlike the traditional CACC algorithms, the proposed algorithm can ensure the functionality of the CACC system even if inter-vehicle communication is partially invalid. Finally, this paper establishes a platoon of five vehicles to simulate the improved CACC algorithm in MATLAB/Simulink, and the simulation results demonstrate that the improved CACC algorithm can maintain the string stability of a CACC platoon through adjusting the controller parameters and enlarging the spacing to prevent accidents. With guaranteed string stability, the proposed CACC algorithm can prevent oscillation of vehicle spacing and reduce chain collision accidents under real-world circumstances. This research proposes an improved CACC algorithm, which can guarantee the string stability when inter-vehicle communication is invalid.
Davis, L C
Wirelessly connected vehicles that exchange information about traffic conditions can reduce delays caused by congestion. At a 2-to-1 lane reduction, the improvement in flow past a bottleneck due to traffic with a random mixture of 40% connected vehicles is found to be 52%. Control is based on connected-vehicle-reported velocities near the bottleneck. In response to indications of congestion the connected vehicles, which are also adaptive cruise control vehicles, reduce their speed in slowdown regions. Early lane changes of manually driven vehicles from the terminated lane to the continuous lane are induced by the slowing connected vehicles. Self-organized congestion at the bottleneck is thus delayed or eliminated, depending upon the incoming flow magnitude. For the large majority of vehicles, travel times past the bottleneck are substantially reduced. Control is responsible for delaying the onset of congestion as the incoming flow increases. Adaptive cruise control increases the flow out of the congested stat...
Winter, de, R.J.; Happee, Riender; Martens, Marieke H.; Stanton, Neville A.
Adaptive cruise control (ACC), a driver assistance system that controls longitudinal motion, has been introduced in consumer cars in 1995. A next milestone is highly automated driving (HAD), a system that automates both longitudinal and lateral motion. We investigated the effects of ACC and HAD on drivers’ workload and situation awareness through a meta-analysis and narrative review of simulator and on-road studies. Based on a total of 32 studies, the unweighted mean self-reported workload wa...
Davis, L. C.
Mixed traffic flow consisting of vehicles equipped with adaptive cruise control (ACC) and manually driven vehicles is analyzed using car-following simulations. Simulations of merging from an on-ramp onto a freeway reported in the literature have not thus far demonstrated a substantial positive impact of ACC. In this paper cooperative merging for ACC vehicles is proposed to improve throughput and increase distance traveled in a fixed time. In such a system an ACC vehicle senses not only the preceding vehicle in the same lane but also the vehicle immediately in front in the other lane. Prior to reaching the merge region, the ACC vehicle adjusts its velocity to ensure that a safe gap for merging is obtained. If on-ramp demand is moderate, cooperative merging produces significant improvement in throughput (20%) and increases up to 3.6 km in distance traveled in 600 s for 50% ACC mixed flow relative to the flow of all-manual vehicles. For large demand, it is shown that autonomous merging with cooperation in the flow of all ACC vehicles leads to throughput limited only by the downstream capacity, which is determined by speed limit and headway time.
Davis, L. C.
Wirelessly connected vehicles that exchange information about traffic conditions can reduce delays caused by congestion. At a 2-to-1 lane reduction, the improvement in flow past a bottleneck due to traffic with a random mixture of 40% connected vehicles is found to be 52%. Control is based on connected-vehicle-reported velocities near the bottleneck. In response to indications of congestion the connected vehicles, which are also adaptive cruise control vehicles, reduce their speed in slowdown regions. Early lane changes of manually driven vehicles from the terminated lane to the continuous lane are induced by the slowing connected vehicles. Self-organized congestion at the bottleneck is thus delayed or eliminated, depending upon the incoming flow magnitude. For the large majority of vehicles, travel times past the bottleneck are substantially reduced. Control is responsible for delaying the onset of congestion as the incoming flow increases. Adaptive cruise control increases the flow out of the congested state at the bottleneck. The nature of the congested state, when it occurs, appears to be similar under a variety of conditions. Typically 80-100 vehicles are approximately equally distributed between the lanes in the 500 m region prior to the end of the terminated lane. Without the adaptive cruise control capability, connected vehicles can delay the onset of congestion but do not increase the asymptotic flow past the bottleneck. Calculations are done using the Kerner-Klenov three-phase theory, stochastic discrete-time model for manual vehicles. The dynamics of the connected vehicles is given by a conventional adaptive cruise control algorithm plus commanded deceleration. Because time in the model for manual vehicles is discrete (one-second intervals), it is assumed that the acceleration of any vehicle immediately in front of a connected vehicle is constant during the time interval, thereby preserving the computational simplicity and speed of a discrete-time model.
Full Text Available Purpose: In this paper, the impact of Cooperative Adaptive Cruise Control (CACC systems on traffic performance is examined using microscopic agent-based simulation. Using a developed traffic simulation model of a freeway with an on-ramp - created to induce perturbations and to trigger stop-and-go traffic, the CACC system’s effect on the traffic performance is studied. The previously proposed traffic simulation model is extended and validated. By embedding CACC vehicles in different penetration levels, the results show significance and indicate the potential of CACC systems to improve traffic characteristics and therefore can be used to reduce traffic congestion. The study shows that the impact of CACC is positive but is highly dependent on the CACC market penetration. The flow rate of the traffic using CACC is proportional to the market penetration rate of CACC equipped vehicles and the density of the traffic.Design/methodology/approach: This paper uses microscopic simulation experiments followed by a quantitative statistical analysis. Simulation enables researchers manipulating the system variables to straightforwardly predict the outcome on the overall system, giving researchers the unique opportunity to interfere and make improvements to performance. Thus with simulation, changes to variables that might require excessive time, or be unfeasible to carry on real systems, are often completed within seconds.Findings: The findings of this paper are summarized as follow:•\tProvide and validate a platform (agent-based microscopic traffic simulator in which any CACC algorithm (current or future may be evaluated.•\tProvide detailed analysis associated with implementation of CACC vehicles on freeways.•\tInvestigate whether embedding CACC vehicles on freeways has a significant positive impact or not.Research limitations/implications: The main limitation of this research is that it has been conducted solely in a computer laboratory. Laboratory
Davis, L C
The dynamics of a platoon of adaptive cruise control vehicles is analyzed for a general mechanical response of the vehicle's power-train. Effects of acceleration-feedback control that were not previously studied are found. For small acceleration-feedback gain, which produces marginally string-stable behavior, the reduction of a disturbance (with increasing car number n) is found to be faster than for the maximum allowable gain. The asymptotic magnitude of a disturbance is shown to fall off as erf(ct./sq. rt. n) when n goes to infinity. For gain approaching the lower limit of stability, oscillations in acceleration associated with a secondary maximum in the transfer function (as a function of frequency) can occur. A frequency-dependent gain that reduces the secondary maximum, but does not affect the transfer function near zero frequency, is proposed. Performance is thereby improved by elimination of the undesirable oscillations while the rapid disturbance reduction is retained.
Zeeshan Ali Memon
Full Text Available Automotive vehicle following systems are essential for the design of automated highway system. The problem associated with the automatic vehicle following system is the string stability of the platoon of vehicles, i.e. the problem of uniform velocity and spacing errors propagation. Different control algorithm for the longitudinal control of a platoon are discussed based on different spacing policies, communication link among the vehicles of a platoon, and the performance of a platoon have been analysed in the presence of disturbance (noise and parametric uncertainties. This paper presented the PID (Proportional Integral Derivative feedback control algorithm for the longitudinal control of a platoon in the presence of noise signal and investigates the performance of platoon under the influence of sudden acceleration and braking in severe conditions. This model has been applied on 6 vehicles moving in a platoon. The platoon has been analysed to retain the uniform velocity and safe spacing among the vehicles. The limitations of PID control algorithm have been discussed and the alternate methods have been suggested. Model simulations, in comparison with the literature, are also presented.
Urnes, James, Sr.; Nguyen, Nhan; Ippolito, Corey; Totah, Joseph; Trinh, Khanh; Ting, Eric
Boeing and NASA are conducting a joint study program to design a wing flap system that will provide mission-adaptive lift and drag performance for future transport aircraft having light-weight, flexible wings. This Variable Camber Continuous Trailing Edge Flap (VCCTEF) system offers a lighter-weight lift control system having two performance objectives: (1) an efficient high lift capability for take-off and landing, and (2) reduction in cruise drag through control of the twist shape of the flexible wing. This control system during cruise will command varying flap settings along the span of the wing in order to establish an optimum wing twist for the current gross weight and cruise flight condition, and continue to change the wing twist as the aircraft changes gross weight and cruise conditions for each mission segment. Design weight of the flap control system is being minimized through use of light-weight shape memory alloy (SMA) actuation augmented with electric actuators. The VCCTEF program is developing better lift and drag performance of flexible wing transports with the further benefits of lighter-weight actuation and less drag using the variable camber shape of the flap.
Marzbanrad, Javad; Tahbaz-zadeh Moghaddam, Iman
The main purpose of this paper is to design a self-tuning control algorithm for an adaptive cruise control (ACC) system that can adapt its behaviour to variations of vehicle dynamics and uncertain road grade. To this aim, short-time linear quadratic form (STLQF) estimation technique is developed so as to track simultaneously the trend of the time-varying parameters of vehicle longitudinal dynamics with a small delay. These parameters are vehicle mass, road grade and aerodynamic drag-area coefficient. Next, the values of estimated parameters are used to tune the throttle and brake control inputs and to regulate the throttle/brake switching logic that governs the throttle and brake switching. The performance of the designed STLQF-based self-tuning control (STLQF-STC) algorithm for ACC system is compared with the conventional method based on fixed control structure regarding the speed/distance tracking control modes. Simulation results show that the proposed control algorithm improves the performance of throttle and brake controllers, providing more comfort while travelling, enhancing driving safety and giving a satisfactory performance in the presence of different payloads and road grade variations.
Baret, Marc; Bomer, Thierry T.; Calesse, C.; Dudych, L.; L'Hoist, P.
Autonomous intelligent cruise control (AICC) systems are not only controlling vehicles' speed but acting on the throttle and eventually on the brakes they could automatically maintain the relative speed and distance between two vehicles in the same lane. And more than just for comfort it appears that these new systems should improve the safety on highways. By applying a technique issued from the space research carried out by MATRA, a sensor based on a charge coupled device (CCD) was designed to acquire the reflected light on standard-mounted car reflectors of pulsed laser diodes emission. The CCD is working in a unique mode called flash during transfer (FDT) which allows identification of target patterns in severe optical environments. It provides high accuracy for distance and angular position of targets. The absence of moving mechanical parts ensures high reliability for this sensor. The large field of view and the high measurement rate give a global situation assessment and a short reaction time. Then, tracking and filtering algorithms have been developed in order to select the target, on which the equipped vehicle determines its safety distance and speed, taking into account its maneuvering and the behaviors of other vehicles.
To develop cruise control system of an automobile with the metal pushing V-belt type CVT, the dynamic model of automobile travelling longitudinally is established, and the fuzzy controller of control system is designed. Considering uncertainty system parameter and exterior resistance disturbances, the stability of controller is investigated by simulating. The results of its simulation show that the fuzzy controller designed has practicability.
Experiences with Advanced Cruise Control in traffic; a limited experiment. Advanced Cruise Control (ACC) is an ordinary cruise control in which the desired speed is installed manually, but in which the headway time to the vehicle in front is also taken into account. If the headway time becomes less
Jorge, Tiago R.; Lemos, João M; Barão, Miguel
The contribution of this paper consists in a procedure to solve the optimal cruise control problem that consists in transferring the car velocity between two specified values, in a fixed interval of time, with minimum fuel consumption. The solution is obtained by applying a recursive numerical algorithm that provides an approximation to the condition provided by Pontryagin’s Optimum Principle. This solution is compared with the one obtained by using a reduced complexity linear model for the c...
With small profit margins in merchant shipping and more than eighty percent of sailing time being cross ocean voyages, speed control is crucial for vessel profitability......With small profit margins in merchant shipping and more than eighty percent of sailing time being cross ocean voyages, speed control is crucial for vessel profitability...
Experiences with Advanced Cruise Control in traffic; a limited experiment. Advanced Cruise Control (ACC) is an ordinary cruise control in which the desired speed is installed manually, but in which the headway time to the vehicle in front is also taken into account. If the headway time becomes less than the installed critical threshold value, the system brakes the vehicle gradually. If the vehicle in front is no longer there, or the headway time is greater than the threshold value, the instal...
Wei-Ming Li; Rui-Sheng Sun; Hong-Yang Bai; Peng-Yun Liu
In this paper, an adaptive sliding mode method was proposed for BTT autopilot of cruise missiles with variable-swept wings. To realize the whole state feedback, the roll angle, normal overloads and angular rates were considered as state variables of the autopilot, and a parametric sliding mode controller was designed via feedback linearization. A novel parametric adaptation law was put forward to estimate the nonlinear time-varying parameter perturbations in real time based on Lyapunov stability theory. A sliding mode boundary layer theory was adopted to smooth the discontinuity of control variables and eliminate the control chattering. The simulation was presented for the roll angle and overload commands tracking in different configuration schemes. The results indicated that the controlled system has robust dynamic tracking performance in condition of the large-scale aerodynamic parametric variety resulted from variable-swept wings.
Journet, Bernard A.; Bazin, Gaelle
THe purpose of this paper is to show to what kind of application laser range-finders can be used inside Autonomous Intelligent Cruise Control systems. Even if laser systems present good performances the safety and technical considerations are very restrictive. As the system is used in the outside, the emitted average output power must respect the rather low level of 1A class. Obstacle detection or collision avoidance require a 200 meters range. Moreover bad weather conditions, like rain or fog, ar disastrous. We have conducted measurements on laser rangefinder using different targets and at different distances. We can infer that except for cooperative targets low power laser rangefinder are not powerful enough for long distance measurement. Radars, like 77 GHz systems, are better adapted to such cases. But in case of short distances measurement, range around 10 meters, with a minimum distance around twenty centimeters, laser rangefinders are really useful with good resolution and rather low cost. Applications can have the following of white lines on the road, the target being easily cooperative, detection of vehicles in the vicinity, that means car convoy traffic control or parking assistance, the target surface being indifferent at short distances.
Eenennaam, van Emiel Martijn
Over the past two hundred years, automotive technology has evolved from mechanised horse carriage to high-tech systems which pack more computing power than the entire space program that put Neil Armstrong on the moon. Hand-in-hand with this evolution came a proliferation of ownership and use of cars
Connected vehicle systems (CVS) are considered in this paper where vehicles exchange information using wireless vehicle-to-vehicle (V2V) communication. The concept of connected cruise control (CCC) is established that allows control design at the level of individual vehicles while exploiting V2V connectivity. Due to its high level of modularity the proposed design can be applied to large heterogeneous traffic systems. The dynamics of a simple CVS is analysed in detail while taking into account nonlinearities in the vehicle dynamics as well as in the controller. Time delays that arise due to intermittencies and packet drops in the communication channels are also incorporated. The results are summarised using stability charts which allow one to select control gains to maintain stability and ensure disturbance attenuation when the delay is below a critical value.
In this study,an innovative dynamics model of LFS(longitudinal vehicle full-speed cruise system)is developed by lumping the dynamics of a controlled vehicle and an inter-vehicles together.On account of the external disturbance,parameters uncertainty and the nonlinearity within LFS,a DDRC(disturbance decoupling robust control)method is proposed.For this method,the theory of NDD(nonlinear disturbance decoupling)is utilized firstly to separate the external disturbance from certain part of the proposed dynamics model.Then,the invariance over the sliding mode of VSC(variable structure control)is used to eliminate the influence of remaining uncertain part.Finally,the DDRC method is adopted to design an LFS ACC(adaptive cruise control)system,and some numerical simulations are carried out to validate its performance.The simulation results demonstrate that the proposed control system not only exhibits an expected dynamic response,high tracking accuracy and a strong robustness,but also achieves a global optimization by means of a simplified control structure.
熊柯; 夏智勋; 郭振云
An angle of attack control law for air-breathing hypersonic cruise vehicle is presented.Due to the various dynamics and modeling uncertainties among engine cowl closing, engine cowl opening and engine working, an adaptive parameter adjuster control rule is introduced into the sliding mode control.The adaptive law is used to approximate the model perturbation and external disturbances.This method can effectively improve the performance of dynamics and stable characteristics in the pitch channel, and it also has strong adaptability to the changes of aerodynamic parameters and elevator trimming.The simulation results show that the control method has the excellent tracking-point performance and the strong robustness against the disturbances and the uncertainties.%针对吸气式高超声速巡航飞行器发动机进气道关闭、进气道打开、发动机点火工作3个状态下俯仰通道气动系数和配平舵偏角变化大的特点,设计了一种基于参考模型的自适应滑模攻角控制律.在滑模控制中引入了自适应参数调节律来逼近不确定的模型参数变化和外界干扰,有效地改善了飞行器俯仰通道的动态和稳态性能,同时对于气动系数和配平舵偏角的变化具有自适应性.数学仿真结果表明,所设计的控制律具有良好的指令跟踪性能和抗干扰能力.
Narendra, K. S.; Annaswamy, A. M.
Several concepts and results in robust adaptive control are are discussed and is organized in three parts. The first part surveys existing algorithms. Different formulations of the problem and theoretical solutions that have been suggested are reviewed here. The second part contains new results related to the role of persistent excitation in robust adaptive systems and the use of hybrid control to improve robustness. In the third part promising new areas for future research are suggested which combine different approaches currently known.
Yang, Chi-Ming; Beck, James L.
A new robust adaptive structural control design methodology is developed and presented which treats modeling uncertainties and limitations of control devices. Furthermore, no restriction is imposed on the structural models and the nature of the control devices so that the proposed method is very general. A simple linear single degree-of-freedom numerical example is presented to illustrate this approach.
Full Text Available Fuzzy logic systems have been widely used for controlling nonlinear and complex dynamic systems by programming heuristic knowledge. But these systems are computationally complex and resource intensive. This paper presents a technique of development and porting of a fuzzy logic approximation PID controller (FLAC in an automatic cruise control (ACC system. ACC is a highly nonlinear process and its control is trivial due to the large change in parameters. Therefore, a suitable controller based on heuristic knowledge will be easy to develop and provide an effective solution. But the major problem with employing fuzzy logic controller (FLC is its complexity. Moreover, the designing of Rulebase requires efficient heuristic knowledge about the system which is rarely found. Therefore, in this paper, a novel rule extraction process is used to derive a FLAC. This controller is then ported on a C6748 DSP hardware with timing and memory optimization. Later, it is seamlessly connected to a network to support remote reconfigurability. A performance analysis is drawn based on processor-in loop test with Simulink model of a cruise control system for vehicle.
Touran, A; Brackstone, M A; McDonald, M
This paper describes a general framework for safety evaluation of autonomous intelligent cruise control in rear-end collisions. Using data and specifications from prototype devices, two collision models are developed. One model considers a train of four cars, one of which is equipped with autonomous intelligent cruise control. This model considers the car in front and two cars following the equipped car. In the second model, none of the cars is equipped with the device. Each model can predict the possibility of rear-end collision between cars under various conditions by calculating the remaining distance between cars after the front car brakes. Comparing the two collision models allows one to evaluate the effectiveness of autonomous intelligent cruise control in preventing collisions. The models are then subjected to Monte Carlo simulation to calculate the probability of collision. Based on crash probabilities, an expected value is calculated for the number of cars involved in any collision. It is found that given the model assumptions, while equipping a car with autonomous intelligent cruise control can significantly reduce the probability of the collision with the car ahead, it may adversely affect the situation for the following cars.
Volkov, Vasily Y; Zhuravlev, Oleg N; Nukhaev, Marat T; Shchelushkin, Roman V
This article presents the idea and realization for the unique Adaptive Inflow Control System being a part of well completion, able to adjust to the changing in time production conditions. This system allows to limit the flow rate from each interval at a certain level, which solves the problem of water and gas breakthroughs. We present the results of laboratory tests and numerical calculations obtaining the characteristics of the experimental setup with dual-in-position valves as parts of adaptive inflow control system, depending on the operating conditions. The flow distribution in the system was also studied with the help of three-dimensional computer model. The control ranges dependences are determined, an influence of the individual elements on the entire system is revealed.
National Aeronautics and Space Administration — M4 Engineering proposes the development of an adaptive structural mode control system. The adaptive control system will begin from a "baseline" dynamic model of the...
Heddebaut, M.; Rioult, J.; GHYS, JP; GRANSART, C; AMBELLOUIS, S
For several years road vehicle autonomous cruise control (ACC) systems as well as anti-collision radar have been developed. Several manufacturers currently sell this equipment. The current generation of ACC sensors only track the first preceding vehicle to deduce its speed and position. These data are then used to compute, manage and optimize a safety distance between vehicles, thus providing some assistance to car drivers. However, in real conditions, to elaborate and update a real time driv...
M. N. Ab Malek
Full Text Available For long time the optimization of controller parameters uses the well-known classical method such as the Ziegler-Nichols and the Cohen-Coon tuning techniques. Despite its effectiveness, these off-line tuning techniques can be time consuming especially for a case of complex nonlinear system. This paper attempts to show a great deal on how Metamodeling techniques can be utilized to tune the PID controller parameters quickly. Note that the plant use in this study is the cruise control system with 2 different models, which are the linear model and the nonlinear model. The difference between both models is that the disturbances were taken into consideration for the nonlinear model, but in the linear model the disturbances were assumed as zero. The Radial Basis Function Neural Network Metamodel is able to prove that it can minimize the time in tuning process as it is able to give a good approximation to the optimum controller parameters in both models of this system.
Goodwin, Graham C
Preface1. Introduction to Adaptive TechniquesPart 1. Deterministic Systems2. Models for Deterministic Dynamical Systems3. Parameter Estimation for Deterministic Systems4. Deterministic Adaptive Prediction5. Control of Linear Deterministic Systems6. Adaptive Control of Linear Deterministic SystemsPart 2. Stochastic Systems7. Optimal Filtering and Prediction8. Parameter Estimation for Stochastic Dynamic Systems9. Adaptive Filtering and Prediction10. Control of Stochastic Systems11. Adaptive Control of Stochastic SystemsAppendicesA. A Brief Review of Some Results from Systems TheoryB. A Summary o
McDonough, Kevin K.
The dissertation presents contributions to fuel-efficient control of vehicle speed and constrained control with applications to aircraft. In the first part of this dissertation a stochastic approach to fuel-efficient vehicle speed control is developed. This approach encompasses stochastic modeling of road grade and traffic speed, modeling of fuel consumption through the use of a neural network, and the application of stochastic dynamic programming to generate vehicle speed control policies that are optimized for the trade-off between fuel consumption and travel time. The fuel economy improvements with the proposed policies are quantified through simulations and vehicle experiments. It is shown that the policies lead to the emergence of time-varying vehicle speed patterns that are referred to as time-varying cruise. Through simulations and experiments it is confirmed that these time-varying vehicle speed profiles are more fuel-efficient than driving at a comparable constant speed. Motivated by these results, a simpler implementation strategy that is more appealing for practical implementation is also developed. This strategy relies on a finite state machine and state transition threshold optimization, and its benefits are quantified through model-based simulations and vehicle experiments. Several additional contributions are made to approaches for stochastic modeling of road grade and vehicle speed that include the use of Kullback-Liebler divergence and divergence rate and a stochastic jump-like model for the behavior of the road grade. In the second part of the dissertation, contributions to constrained control with applications to aircraft are described. Recoverable sets and integral safe sets of initial states of constrained closed-loop systems are introduced first and computational procedures of such sets based on linear discrete-time models are given. The use of linear discrete-time models is emphasized as they lead to fast computational procedures. Examples of
Dr. P. Vijayakumar; UNNIKRISHNAN P C
In this paper an adaptive stable PID controller is briefly explained and validated by simulations and experimentation. The adaptive PID controller employs almost strict positive realness (ASPR) to ensure stability of the system. The design involves a parallel feedforward compensator (PFC) which guarantees the ASPRness of the controlled system. After a disturbance the dynamical system is assumed to be in one of a finite number of configurations, corresponding to each of which exist a stabilizi...
Russell, M.E.; Crain, A.; Curran, A.; Campbell, R.A.; Drubin, C.A.; Miccioli, W.F. [Raytheon, Tewksbury, MA (United States)
If automotive intelligent cruise-control (ICC) systems are to be successful in the marketplace, they must provide robust performance in a complex roadway environment. Inconveniences caused by reduced performance during inclement weather, interrupted performance due to dropped tracks, and annoying nuisance alarms will not be tolerated by the consumer, and would likely result in the rejection of this technology in the marketplace. An all-weather automotive millimeter-wave (MMW) radar sensor is described that uses a frequency-modulation coplanar-wave (FMCW) radar design capable of acquiring and tracking all obstacles in its field of view. Design tradeoffs are discussed and radar-sensor test results are presented along with the applicability of the radar to collision-warning systems.
This thesis is divided into two parts, i.e., adaptive extremum control and modelling and control of a wind turbine. The rst part of the thesis deals with the design of adaptive extremum controllers for some processes which have the behaviour that process should have as high e ciency as possible...... in parameters, and thus directly lends itself to parameter estimation and adaptive control. The extremum control law is derived based on static optimization of a performance function. For a process with nonlinearity at output the intermediate signal between the linear part and nonlinear part plays an important...... role. If it can be emphasis on control design. The models have beenvalidated by experimental data obtained from an existing wind turbine. The e ective wind speed experienced by the rotor of a wind turbine, which is often required by some control methods, is estimated by using a wind turbine as a wind...
DR. P VIJAYAKUMAR
Full Text Available In this paper an adaptive stable PID controller is briefly explained and validated by simulations and experimentation. The adaptive PID controller employs almost strict positive realness (ASPR to ensure stability of the system. The design involves a parallel feedforward compensator (PFC which guarantees the ASPRness of the controlled system. After a disturbance the dynamical system is assumed to be in one of a finite number of configurations, corresponding to each of which exist a stabilizing controller. The effectiveness of the method is tested and compared using simulations and experiments on a level control experimental setup.
ZHU Liye; FANG Yuan; ZHANG Weidong
According to a type of normal nonlinear system, an indirect adaptive fuzzy (IAF) controller has been applied to those systems where no accurate mathematical models of the systems under control are available. To satisfy with system performance, an indirect accelerated adaptive fuzzy (IAAF) controller is proposed, and its general form is presented. The general form IAAF controller ensures necessary control criteria and system's global stability using Lyapunov Theorem. It has been proved that the close-loop system error converges to a small neighborhood of equilibrium point. The optimal IAAF controller is derived to guarantee the process's shortest settling time. Simulation results indicate the IAAF controller make the system more stable, accurate, and fast.
Robust and adaptive control techniques have a rich history of theoretical development with successful application. Despite the accomplishments made, attempts to combine the best elements of each approach into robust adaptive systems has proven challenging, particularly in the area of application to real world aerospace systems. In this research, we investigate design methods for general classes of systems that may be applied to representative aerospace dynamics. By combining robust baseline control design with augmentation designs, our work aims to leverage the advantages of each approach. This research contributes the development of robust model-based control design for two classes of dynamics: 2nd order cascaded systems, and a more general MIMO framework. We present a theoretically justified method for state limiting via augmentation of a robust baseline control design. Through the development of adaptive augmentation designs, we are able to retain system performance in the presence of uncertainties. We include an extension that combines robust baseline design with both state limiting and adaptive augmentations. In addition we develop an adaptive augmentation design approach for a class of dynamic input uncertainties. We present formal stability proofs and analyses for all proposed designs in the research. Throughout the work, we present real world aerospace applications using relevant flight dynamics and flight test results. We derive robust baseline control designs with application to both piloted and unpiloted aerospace system. Using our developed methods, we add a flight envelope protecting state limiting augmentation for piloted aircraft applications and demonstrate the efficacy of our approach via both simulation and flight test. We illustrate our adaptive augmentation designs via application to relevant fixed-wing aircraft dynamics. Both a piloted example combining the state limiting and adaptive augmentation approaches, and an unpiloted example with
Nguyen, Nhan T.
In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.
Hu, Yonghui; Liang, Jianhong; Wang, Tianmiao
This paper presents mechatronic design and locomotion control of a biomimetic robotic fish that swims using thunniform kinematics for fast cruising. Propulsion of the robotic fish is realized with a parallel four-bar propulsive mechanism that delivers combined translational and rotational motion to a lunate caudal fin. A central pattern generator controller, composed of two unidirectionally coupled Hopf oscillators, is employed to generate robust, smooth and coordinated oscillatory control signals for the tail joints. In order to maintain correct phase relation between joints during fast tail beating, a novel phase adjusting mechanism is proposed and incorporated into the controller. The attitude of the robotic fish in fast swimming is stabilized using an attitude and heading reference system unit and a pair of pitching pectoral fins. The maximum speed of the robotic fish can reach 2.0 m s(-1), which is the fastest speed that robotic fishes have achieved. Its outstanding swimming performance presents possibilities for deployment to real-world exploration, probe and survey missions. PMID:25822708
Baret, Marc; Baillarin, S.; Calesse, C.; Martin, Lionel
In the past few years MATRA and RENAULT have developed an Autonomous Intelligent Cruise Control (AICC) system based on a LIDAR sensor. This sensor incorporating a charge coupled device was designed to acquire pulsed laser diode emission reflected by standard car reflectors. The absence of moving mechanical parts, the large field of view, the high measurement rate and the very good accuracy for distance range and angular position of targets make this sensor very interesting. It provides the equipped car with the distance and the relative speed of other vehicles enabling the safety distance to be controlled by acting on the throttle and the automatic gear box. Experiments in various real traffic situations have shown the limitations of this kind of system especially on bends. All AICC sensors are unable to distinguish between a bend and a change of lane. This is easily understood if we consider a road without lane markings. This fact has led MATRA to improve its AICC system by providing the lane marking information. Also in the scope of the EUREKA PROMETHEUS project, MATRA and RENAULT have developed a lane keeping system in order to warn of the drivers lack of vigilance. Thus, MATRA have spread this system to far field lane marking detection and have coupled it with the AICC system. Experiments will be carried out on roads to estimate the gain in performance and comfort due to this fusion.
Heddebaut, M.; Rioult, J.; Ghys, J. P.; Gransart, Ch; Ambellouis, S.
For several years road vehicle autonomous cruise control (ACC) systems as well as anti-collision radar have been developed. Several manufacturers currently sell this equipment. The current generation of ACC sensors only track the first preceding vehicle to deduce its speed and position. These data are then used to compute, manage and optimize a safety distance between vehicles, thus providing some assistance to car drivers. However, in real conditions, to elaborate and update a real time driving solution, car drivers use information about speed and position of preceding and following vehicles. This information is essentially perceived using the driver's eyes, binocular stereoscopic vision performed through the windscreens and rear-view mirrors. Furthermore, within a line of vehicles, the frontal road perception of the first vehicle is very particular and highly significant. Currently, all these available data remain strictly on-board the vehicle that has captured the perception information and performed these measurements. To get the maximum effectiveness of all these approaches, we propose that this information be shared in real time with the following vehicles, within the convoy. On the basis of these considerations, this paper technically explores a cost-effective solution to extend the basic ACC sensor function in order to simultaneously provide a vehicle-to-vehicle radio link. This millimetre wave radio link transmits relevant broadband perception data (video, localization...) to following vehicles, along the line of vehicles. The propagation path between the vehicles uses essentially grazing angles of incidence of signals over the road surface including millimetre wave paths beneath the cars.
Shenoy, D.M.; DileepKumar, M.; Sarma, V.V.S.S.
et al 1996; Andreae and Crutzen 1997). 2:2 Aerosol measurements Aerosol samples were collected at variable heights above the sea level on board the ship. Polycarbonate Figure 1. Locations of stations occupied during the BOB- MEX-Pilot cruise...
On the simple continuously variable transmission (CVT) driveline model, the design of adaptive fuzzy control system for CVT vehicle is presented. The adaptive fuzzy control system consists of a scaling factor self-tuning fuzzy-PI throttle controller, and a hybrid fuzzy-PID CVT ratio and brake controller. The presented adaptive fuzzy control strategy is vehicle model independent, which depends only on the instantaneous vehicle states, but does not depend on vehicle parameters. So it has good robustness against uncertain vehicle parameters and exogenous load disturbance. Simulation results show that the proposed adaptive fuzzy strategy has good adaptability and practicality value.
Adaptive fuzzy controllers by means of variable universe are proposed based on interpolation forms of fuzzy control. First, monotonicity of control rules is defined, and it is proved that the monotonicity of interpolation functions of fuzzy control is equivalent to the monotonicity of control rules. This means that there is not any contradiction among the control rules under the condition for the control rules being monotonic. Then structure of the contraction-expansion factor is discussed. At last, three models of adaptive fuzzy control based on variable universe are given which are adaptive fuzzy control model with potential heredity, adaptive fuzzy control model with obvious heredity and adaptive fuzzy control model with successively obvious heredity.
徐洪智; 李仁发; 曾理宁
信息物理融合系统( CPS)是计算、通信与控制技术的融合,汽车自适应巡航控制系统是一种典型的CPS,具有广泛的应用前景。通过建立汽车纵向行驶的数学模型,并基于CPS给出自适应巡航控制系统的结构,设计系统的状态机模型。基于Ptolemy分别设计前车、测量距离和本车的计算模型,构建系统的层次模型,在子模型中采用模态模式对基于时间的模型与状态机模型相结合的混合系统行为进行建模。仿真结果表明,该方法能满足自适应巡航控制系统的要求,保证系统的安全性。%Cyber Physical System( CPS) ,as a new topic in research of computer science and technology,is the fusion of computation,communication and control. The Auto Adaptive Cruise Control ( ACC ) system is thought as a typical CPS,which has wide application prospect. This paper builds the mathematical model for the vertical travel of the car,and gives the architecture and the system state machine model of the ACC based on the theory of CPS. It designs the model of vehicle ahead,own vehicle and the distance between the two vehicles based on Ptolemy,and builds the hierarchical model of the system. In the submodel of the system, it constructs the system behavior model which is combined with model based on time and state model with the modal model. Simulation results show that the method can meet the requirements and ensures the security of ACC system.
Pavlock, Kate Maureen; Less, James L.; Larson, David Nils
The National Aeronautics and Space Administration s Dryden Flight Research Center completed flight testing of adaptive controls research on a full-scale F-18 testbed. The validation of adaptive controls has the potential to enhance safety in the presence of adverse conditions such as structural damage or control surface failures. This paper describes the research interface architecture, risk mitigations, flight test approach and lessons learned of adaptive controls research.
Brown, S.K.; Baum, C.C.; Bowling, P.S.; Buescher, K.L.; Hanagandi, V.M.; Hinde, R.F. Jr.; Jones, R.D.; Parkinson, W.J.
One can derive a model for use in a Model Predictive Controller (MPC) from first principles or from experimental data. Until recently, both methods failed for all but the simplest processes. First principles are almost always incomplete and fitting to experimental data fails for dimensions greater than one as well as for non-linear cases. Several authors have suggested the use of a neural network to fit the experimental data to a multi-dimensional and/or non-linear model. Most networks, however, use simple sigmoid functions and backpropagation for fitting. Training of these networks generally requires large amounts of data and, consequently, very long training times. In 1993 we reported on the tuning and optimization of a negative ion source using a special neural network. One of the properties of this network (CNLSnet), a modified radial basis function network, is that it is able to fit data with few basis functions. Another is that its training is linear resulting in guaranteed convergence and rapid training. We found the training to be rapid enough to support real-time control. This work has been extended to incorporate this network into an MPC using the model built by the network for predictive control. This controller has shown some remarkable capabilities in such non-linear applications as continuous stirred exothermic tank reactors and high-purity fractional distillation columns. The controller is able not only to build an appropriate model from operating data but also to thin the network continuously so that the model adapts to changing plant conditions. The controller is discussed as well as its possible use in various of the difficult control problems that face this community.
O. F. Opeiko
Full Text Available A synthesis of adaptive PID controller has been executed for flux linkage and speed channels of a vector control system for an induction short-circuited motor. While using an imitation simulation method results of a synthesized system analysis show that the adaptive PID controller has some advantages under conditions of parametric disturbances affecting the object.
Thawar T. Arif
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.
Full Text Available The paper presents an adaptive method using the controlled grid deformation over an elastic, isotropic and continuous domain. The adaptive process is controlled with the principal strains and principal strain directions and uses the finite elements method. Numerical results are presented for several test cases.
George, V. I.; B. Ganesh Kamath; I. Thirunavukkarasu; Ciji Pearl Kurian
The aim is to develop vibration control of flexible spacecraft by adaptive controller. A case study will be carried out which simulates planar motion of flexible spacecraft as a coupled hybrid dynamics of rigid body motion and the flexible arm vibration. The notch filter and adaptive vibration controller, which updates filter and controller parameters continuously from the sensor measurement, are implemented in the real time control. The least mean square algorithm using the adaptive notch fi...
Inamdar, S. R.
In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.
Pavlock, Kate Maureen; Less, James L.; Larson, David Nils
The National Aeronautics and Space Administration's Dryden Flight Research Center completed flight testing of adaptive controls research on a full-scale F-18 testbed. The testbed served as a full-scale vehicle to test and validate adaptive flight control research addressing technical challenges involved with reducing risk to enable safe flight in the presence of adverse conditions such as structural damage or control surface failures. This paper describes the research interface architecture, risk mitigations, flight test approach and lessons learned of adaptive controls research.
WANG Yi-jing; WANG Long
The problem of adaptive generalized predictive control which consists of output prediction errors for a class of switched systems is studied. The switching law is determined by the output predictive errors of a finite number of subsystems. For the single subsystem and multiple subsystems cases, it is proved that the given direct algorithm of generalized predictive control guarantees the global convergence of the system. This algorithm overcomes the inherent drawbacks of the slow convergence and large transient errors for the conventional adaptive control.
Hartmann, G. L.; Stein, G.
Honeywell has designed a digital self-adaptive flight control system for flight test in the VALT Research Aircraft (a modified CH-47). The final design resulted from a comparison of two different adaptive concepts: one based on explicit parameter estimates from a real-time maximum likelihood estimation algorithm and the other based on an implicit model reference adaptive system. The two designs are compared on the basis of performance and complexity.
Wei, Wei; Wang, Jing; Zuo, Min; Liu, Zaiwen; Du, Junping
In this article, chaos control of satellite attitude motion is considered. Adaptive control based on dynamic compensation is utilised to suppress the chaotic behaviour. Control approaches with three control inputs and with only one control input are proposed. Since the adaptive control employed is based on dynamic compensation, faithful model of the system is of no necessity. Sinusoidal disturbance and parameter uncertainties are considered to evaluate the robustness of the closed-loop system. Both of the approaches are confirmed by theoretical and numerical results.
GUAN Ping; LIU Xiang-dong; CHEN Jia-bin
The adaptive fuzzy control is applied in the attitude stabilization of flexible satellite. The detailed design procedure of the adaptive fuzzy control system is presented. Two T-S models are used as both controller and identifier. The parameters of the controller could be modified according to the information of the identifier. Simulation results show that the method can effectively cope with the uncertainty of flexible satellite by on-line learning and thus posses the good robustness. With the proposed method, the precise attitude control is accomplished.
National Aeronautics and Space Administration — An Adaptive Feedforward and Feedback Control (AFFC) Framework is proposed to suppress the aircraft's structural vibrations and to increase the resilience of the...
Landau, Ioan; Lozano, Rogelio; M'Saad, Mohammed; Karimi, Alireza
Adaptive Control (second edition) shows how a desired level of system performance can be maintained automatically and in real time, even when process or disturbance parameters are unknown and variable. It is a coherent exposition of the many aspects of this field, setting out the problems to be addressed and moving on to solutions, their practical significance and their application. Discrete-time aspects of adaptive control are emphasized to reflect the importance of digital computers in the ...
Battistelli, Giorgio; Mari, Daniele; Selvi, Daniela; Tesi, Alberto; Tesi, Pietro
The problem of adaptive disturbance attenuation is addressed in this paper using a switching control approach. A finite family of stabilizing controllers is pre-designed, with the assumption that, for any possible operating condition, at least one controller is able to achieve a prescribed level of
LIU Xiao-hua; WANG Xiu-hong; FEN En-min
For a class of continuous-time nonlinear system, a novel robust adaptive fuzzy controller is proposed by using of Lyapunov method. It is proven that the control algorithm is globally stable, the output tracking-error can convergence to a domain of zero under the assumptions. As a result, the system controlled has stronger robustness for disturbance and modeling error.
Schmidt, Lasse; Andersen, Torben Ole; Pedersen, Henrik C.;
This paper presents a new adaptive sliding mode controller generally applicable for position tracking control of electro-hydraulic valve-cylinder drives (VCD’s). The proposed control scheme requires limited knowledge on system parameters, and employs only piston- and valve spool position feedback...
Bobtsov, Alexey; Faronov, Maxim; Kolyubin, Sergey; Pyrkin, Anton
The problem of simple adaptive and robust control is studied for the case of parametric and dynamic dimension uncertainties: only the maximum possible relative degree of the plant model is known. The control approach "consecutive compensator" is investigated. To illustrate the efficiency of proposed approach an example with the mobile robot motion control using computer vision system is considered.
Wang Xin; Li Shaoyuan; Wang Zhongjie
When the parameters of the system change abruptly, a new multivariable adaptive feedforward decoupling controller using multiple models is presented to improve the transient response. The system models are composed of multiple fixed models, one free-running adaptive model and one re-initialized adaptive model. The fixed models are used to provide initial control to the process. The re-initialized adaptive model can be reinitialized as the selected model to improve the adaptation speed. The free-running adaptive controller is added to guarantee the overall system stability. At each instant, the best system model is selected according to the switching index and the corresponding controller is designed. During the controller design, the interaction is viewed as the measurable disturbance and eliminated by the choice of the weighting polynomial matrix. It not only eliminates the steady-state error but also decouples the system dynamically. The global convergence is obtained and several simulation examples are presented to illustrate the effectiveness of the proposed controller.
Nguyen, Nhan T.; Krishnakumar, Kalmanje; Boskovic, Jovan
This paper presents a method that can achieve fast adaptation for a class of model-reference adaptive control. It is well-known that standard model-reference adaptive control exhibits high-gain control behaviors when a large adaptive gain is used to achieve fast adaptation in order to reduce tracking error rapidly. High gain control creates high-frequency oscillations that can excite unmodeled dynamics and can lead to instability. The fast adaptation approach is based on the minimization of the squares of the tracking error, which is formulated as an optimal control problem. The necessary condition of optimality is used to derive an adaptive law using the gradient method. This adaptive law is shown to result in uniform boundedness of the tracking error by means of the Lyapunov s direct method. Furthermore, this adaptive law allows a large adaptive gain to be used without causing undesired high-gain control effects. The method is shown to be more robust than standard model-reference adaptive control. Simulations demonstrate the effectiveness of the proposed method.
Alexander, J A
Multidivisional organizations are not concerned with what structure to adopt but with how they should exercise control within the divisional form to achieve economic efficiencies. Using an information-processing framework, I examined control arrangements between the headquarters and operating divisions of such organizations and how managers adapted control practices to accommodate increasing environmental uncertainty. Also considered were the moderating effects of contextual attributes on such adaptive behavior. Analyses of panel data from 97 multihospital systems suggested that organizations generally practice selective decentralization under conditions of increasing uncertainty but that organizational age, dispersion, and initial control arrangements significantly moderate the direction and magnitude of such changes.
Alexander, J A
Multidivisional organizations are not concerned with what structure to adopt but with how they should exercise control within the divisional form to achieve economic efficiencies. Using an information-processing framework, I examined control arrangements between the headquarters and operating divisions of such organizations and how managers adapted control practices to accommodate increasing environmental uncertainty. Also considered were the moderating effects of contextual attributes on such adaptive behavior. Analyses of panel data from 97 multihospital systems suggested that organizations generally practice selective decentralization under conditions of increasing uncertainty but that organizational age, dispersion, and initial control arrangements significantly moderate the direction and magnitude of such changes. PMID:10110017
Butler, H.; Honderd, G.; Amerongen, van, W.E.
This paper introduces the method of reference model decomposition as a way to improve the robustness of model reference adaptive control systems (MRACs) with respect to unmodelled dynamics with a known structure. Such unmodelled dynamics occur when some of the nominal plant dynamics are purposely neglected in the controller design with the aim of keeping the controller order low. One of the effects of such undermodelling of the controller is a violation of the perfect model-matching condition...
Kjems, Erik; Bolet, Lars; Agerholm, Niels;
This study uses theoretical considerations along with computer simulation and driving experiments on a road section to evaluate the possibilities of defining an energy-efficient speed adaptation strategy. The goal of the overall study is to include various external parameters not only the alignme...... and a field experiment using a small vehicle with automatic transmission. The experiment showed promising results....
Full Text Available The aim is to develop vibration control of flexible spacecraft by adaptive controller. A case study will be carried out which simulates planar motion of flexible spacecraft as a coupled hybrid dynamics of rigid body motion and the flexible arm vibration. The notch filter and adaptive vibration controller, which updates filter and controller parameters continuously from the sensor measurement, are implemented in the real time control. The least mean square algorithm using the adaptive notch filter is applied to the flexible spacecraft. This study will show that the adaptive vibration controller successfully stabilizes the uncertain and it will accurately control the vibration of flexible spacecraft. The Least mean square algorithm is applied in flexible spacecraft to attenuate the vibration. The simulation studies are carried out in a Matlab/Simulink environment.
Udink ten Cate, A.J.
The material presented in this thesis can be grouped around four themes, system concepts, modeling, control and adaptive control. In this summary these themes will be treated separately.System conceptsIn Chapters 1 and 2 an overview of the problem formulation is presented. It is suggested that there
Full Text Available The obesity epidemic continues rising as a global health challenge, despite the increasing public awareness and the use of lifestyle and medical interventions. The biomedical community is urged to develop new treatments to obesity. Excess energy is stored as fat in white adipose tissue (WAT, dysfunction of which lie at the core of obesity and associated metabolic disorders. In contrast, brown adipose tissue (BAT burns fat and dissipates chemical energy as heat. The development and activation of brown-like adipocytes, also known as beige cells, result in WAT browning and thermogenesis. The recent discovery of brown and beige adipocytes in adult humans has sparked the exploration of the development, regulation, and function of these thermogenic adipocytes. The central nervous system (CNS drives the sympathetic nerve activity in BAT and WAT to control heat production and energy homeostasis. This review provides an overview of the integration of thermal, hormonal, and nutritional information on hypothalamic circuits in thermoregulation.
The problem of direct adaptive neural network control for a class of uncertain nonlinear systems with unknown constant control gain is studied in this paper. Based on the supervisory control strategy and the approximation capability of multilayer neural networks (MNNs), a novel design scheme of direct adaptive neural network controller is proposed.The adaptive law of the adjustable parameter vector and the matrix of weights in the neural networks and the gain of sliding mode control term to adaptively compensate for the residual and the approximation error of MNNs is determined by using a Lyapunov method. The approach does not require the optimal approximation error to be square-integrable or the supremum of the optimal approximation error to be known. By theoretical analysis, the closed-loop control system is proven to be globally stable in the sense that all signals involved are bounded, with tracking error converging to zero.Simulation results demonstrate the effectiveness of the approach.
Couceiro, Micael S.; Ferreira, Nuno M. F.; Machado, J. A. Tenreiro
Dragonflies show unique and superior flight performances than most of other insect species and birds. They are equipped with two pairs of independently controlled wings granting an unmatchable flying performance and robustness. In this paper, it is presented an adaptive scheme controlling a nonlinear model inspired in a dragonfly-like robot. It is proposed a hybrid adaptive ( HA) law for adjusting the parameters analyzing the tracking error. At the current stage of the project it is considered essential the development of computational simulation models based in the dynamics to test whether strategies or algorithms of control, parts of the system (such as different wing configurations, tail) as well as the complete system. The performance analysis proves the superiority of the HA law over the direct adaptive ( DA) method in terms of faster and improved tracking and parameter convergence.
H.S. Tzou; Bao, Y
Adaptive structures with controllable geometries and shapes are rather useful in many engineering applications, such as adaptive wings, variable focus mirrors, adaptive machines, micro-electromechanical systems, etc. Dynamics and feedback control effectiveness of adaptive shells whose curvatures are actively controlled and continuously changed are evaluated. An adaptive piezoelectric laminated cylindrical shell composite with continuous curvature changes is studied, and its natural frequencie...
Full Text Available Passive vibration control solutions are often limited to working reliably at one design point. Especially applied to lightweight structures, which tend to have unwanted vibration, active vibration control approaches can outperform passive solutions. To generate dynamic forces in a narrow frequency band, passive single-degree-of-freedom oscillators are frequently used as vibration absorbers and neutralizers. In order to respond to changes in system properties and/or the frequency of excitation forces, in this work, adaptive vibration compensation by a tunable piezoelectric vibration absorber is investigated. A special design containing piezoelectric stack actuators is used to cover a large tuning range for the natural frequency of the adaptive vibration absorber, while also the utilization as an active dynamic inertial mass actuator for active control concepts is possible, which can help to implement a broadband vibration control system. An analytical model is set up to derive general design rules for the system. An absorber prototype is set up and validated experimentally for both use cases of an adaptive vibration absorber and inertial mass actuator. Finally, the adaptive vibration control system is installed and tested with a basic truss structure in the laboratory, using both the possibility to adjust the properties of the absorber and active control.
Chowdhary, Girish; Kingravi, Hassan A; How, Jonathan P; Vela, Patricio A
Most current model reference adaptive control (MRAC) methods rely on parametric adaptive elements, in which the number of parameters of the adaptive element are fixed a priori, often through expert judgment. An example of such an adaptive element is radial basis function networks (RBFNs), with RBF centers preallocated based on the expected operating domain. If the system operates outside of the expected operating domain, this adaptive element can become noneffective in capturing and canceling the uncertainty, thus rendering the adaptive controller only semiglobal in nature. This paper investigates a Gaussian process-based Bayesian MRAC architecture (GP-MRAC), which leverages the power and flexibility of GP Bayesian nonparametric models of uncertainty. The GP-MRAC does not require the centers to be preallocated, can inherently handle measurement noise, and enables MRAC to handle a broader set of uncertainties, including those that are defined as distributions over functions. We use stochastic stability arguments to show that GP-MRAC guarantees good closed-loop performance with no prior domain knowledge of the uncertainty. Online implementable GP inference methods are compared in numerical simulations against RBFN-MRAC with preallocated centers and are shown to provide better tracking and improved long-term learning.
Lemos, João M; Igreja, José M
This book describes methods for adaptive control of distributed-collector solar fields: plants that collect solar energy and deliver it in thermal form. Controller design methods are presented that can overcome difficulties found in these type of plants:they are distributed-parameter systems, i.e., systems with dynamics that depend on space as well as time;their dynamics is nonlinear, with a bilinear structure;there is a significant level of uncertainty in plant knowledge.Adaptive methods form the focus of the text because of the degree of uncertainty in the knowledge of plant dynamics. Parts
Thor I. Fossen
Full Text Available The problem of controlling underwater mobile robots in 6 degrees of freedom (DOF is addressed. Uncertainties in the input matrix due to partly known nonlinear thruster characteristics are modeled as multiplicative input uncertainty. This paper proposes two methods to compensate for the model uncertainties: (1 an adaptive passivity-based control scheme and (2 deriving a hybrid (adaptive and sliding controller. The hybrid controller consists of a switching term which compensates for uncertainties in the input matrix and an on-line parameter estimation algorithm. Global stability is ensured by applying Barbalat's Lyapunovlike lemma. The hybrid controller is simulated for the horizontal motion of the Norwegian Experimental Remotely Operated Vehicle (NEROV.
Full Text Available Most of existing adaptive control schemes are designed to minimize error between plant state and goal state despite the fact that executing actions that are predicted to result in smaller errors only can mislead to non-goal states. We develop an adaptive control scheme that involves manipulating a controller of a general type to improve its performance as measured by an evaluation function. The developed method is closely related to a theory of Reinforcement Learning (RL but imposes a practical assumption made for faster learning. We assume that a value function of RL can be approximated by a function of Euclidean distance from a goal state and an action executed at the state. And, we propose to use it for the gradient search as an evaluation function. Simulation results provided through application of the proposed scheme to a pole-balancing problem using a linear state feedback controller and fuzzy controller verify the scheme’s efficacy.
Akira Inoue; Ming-Cong Deng
This paper presents a framework of a combined adaptive and non-adaptive attitude control system for a helicopter experimental system. The design method is based on a combination of adaptive nonlinear control and non-adaptive nonlinear control. With regard to detailed attitude control system design, two schemes are shown for different application cases.
For discrete-time nonlinear stochastic systems with unknown nonparametric structure, a kernel estimation-based nonparametric adaptive controller is constructed based on truncated certainty equivalence principle. Global stability and asymptotic optimality of the closed-loop systems are established without resorting to any external excitations.
Kloiber, Bernhard; Strang, Thomas; de Ponte Müller, Fabian
The Electric Vehicle is seen to be one of the most important enablers for a more environmentally friendly mobility of people. Unfortunately, state of the art electric vehicles suffer from a series of problems, with facing a very limited traveling distance compared to gasoline vehicles being one of the most relevant ones. In this paper we present an approach how to reduce the energy consumption while traveling over longer distances by using the slipstream effect behind a vehicle ahead. We show...
Hogema, J.H.; Janssen, W.H.
In een simulatorexperiment is gebleken dat Intelligent Cruisse Control (ICC) resulteert in een vermindering van korte volgtijden en een iets lagere snelheidskeuze in kritische situaties was er met ICC sprake van een iets tragere reactie.
Wen, John Ting-Yung; Balas, Mark J.
Paper discusses generalization of scheme for adaptive control of finite-dimensional system to infinite-dimensional Hilbert space. Approach involves generalization of command-generator tracker (CGT) theory. Does not require reference model to be same order as that of plant, and knowledge of order of plant not needed. Suitable for application to high-order systems, main emphasis on adjustment of low-order feedback-gain matrix. Analysis particularly relevant to control of large, flexible structures.
Maher, M.; Bahhou, B.; Roux, G. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Maher, M. [Faculte des Sciences, Rabat (Morocco). Lab. de Physique
This paper presents a multivariable adaptive control of a continuous-flow fermentation process for the alcohol production. The linear quadratic control strategy is used for the regulation of substrate and ethanol concentrations in the bioreactor. The control inputs are the dilution rate and the influent substrate concentration. A robust identification algorithm is used for the on-line estimation of linear MIMO model`s parameters. Experimental results of a pilot-plant fermenter application are reported and show the control performances. (authors) 8 refs.
Robust and Adaptive Control shows the reader how to produce consistent and accurate controllers that operate in the presence of uncertainties and unforeseen events. Driven by aerospace applications the focus of the book is primarily on continuous-dynamical systems. The text is a three-part treatment, beginning with robust and optimal linear control methods and moving on to a self-contained presentation of the design and analysis of model reference adaptive control (MRAC) for nonlinear uncertain dynamical systems. Recent extensions and modifications to MRAC design are included, as are guidelines for combining robust optimal and MRAC controllers. Features of the text include: · case studies that demonstrate the benefits of robust and adaptive control for piloted, autonomous and experimental aerial platforms; · detailed background material for each chapter to motivate theoretical developments; · realistic examples and simulation data illustrating key features ...
This paper presents an adaptive strategy for controlling chaotic systems. By employing the phase space reconstruction technique in nonlinear dynamical systems theory, the proposed strategy transforms the nonlinear system into canonical form, and employs a nonlinear observer to estimate the uncertainties and disturbances of the nonlinear system, and then establishes a state-error-like feedback law. The developed control scheme allows chaos control in spite of modeling errors and parametric variations. The effectiveness of the proposed approach has been demonstrated through its applications to two well-known chaotic systems : Duffing oscillator and Rǒssler chaos.
This paper presents an adaptive strategy for controlling chaotic systems. By employing the phase space reconstruction technique in nonlinear dynamical systems theory, the proposed strategy transforms the nonlinear system into canonical form, and employs a nonlinear observer to estimate the uncertainties and disturbances of the nonlinear system, and then establishes a state-error-like feedback law. The developed control scheme allows chaos control in spite of modeling errors and parametric variations. The effectiveness of the proposed approach has been demonstrated through its applications to two well-known chaotic systems: Duffing oscillator and Rossler chaos.
To guarantee the real-time transmission of a video stream,based on the stochastic optimal control method,a frame layer adaptive rate control algorithm for the wireless transcoder is proposed,which is capable of dynamically determining the transcoder's objective bit rate,according to the bandwidth variation of the wireless channel and the bufier occupancy. Then the transient performance,steady performance,and computational complexity of the algorithm are analyzed.Finally,the experiment results demonstrate that the algorithm can improve the synthetic performance of rate control through the compromise between the end-to-end delay and the playout quality.
It is important to develop control techniques able to control not only known chaos but also chaotic systems with unknown parameters. This paper proposes a novel adaptive tracking control approach for identifying the unknown parameters and controlling the chaos, which is not closely related to the particular chaotic system to be controlled. The global uniform boundedness of estimated parameters and the asymptotical stability of the tracking errors are proved by Lyapunov stability theory and LaSalle-Yoshizawa theorem. The suggested method enables stabilization of chaotic motion to a steady state ad well as tracking of any desired trajectory to be achieved in a systematic way. Computer simulation on a complex chaotic system illustrtes the effectiveness of the proposed control method.
Santillo, Mario A. (Inventor); Bernstein, Dennis S. (Inventor)
A discrete-time adaptive control law for stabilization, command following, and disturbance rejection that is effective for systems that are unstable, MIMO, and/or nonminimum phase. The adaptive control algorithm includes guidelines concerning the modeling information needed for implementation. This information includes the relative degree, the first nonzero Markov parameter, and the nonminimum-phase zeros. Except when the plant has nonminimum-phase zeros whose absolute value is less than the plant's spectral radius, the required zero information can be approximated by a sufficient number of Markov parameters. No additional information about the poles or zeros need be known. Numerical examples are presented to illustrate the algorithm's effectiveness in handling systems with errors in the required modeling data, unknown latency, sensor noise, and saturation.
Jie LUO; Chengyu CAO
This paper presents an adaptive control scheme with an integration of sliding mode control into the L1 adaptive control architecture, which provides good tracking performance as well as robustness against matched uncertainties. Sliding mode control is used as an adaptive law in the L1 adaptive control architecture, which is considered as a virtual control of error dynamics between estimated states and real states. Low-pass filtering mechanism in the control law design prevents a discontinuous signal in the adaptive law from appearing in actual control signal while maintaining control accuracy. By using sliding mode control as a virtual control of error dynamics and introducing the low-pass filtered control signal, the chattering effect is eliminated. The performance bounds between the close-loop adaptive system and the closed-loop reference system are characterized in this paper. Numerical simulation is provided to demonstrate the performance of the presented adaptive control scheme.
D M Shenoy; M Dileep Kumar; V V S S Sarma
The air-sea exchange is one of the main mechanisms maintaining the abundances of trace gases in the atmosphere. Some of these, such as carbon dioxide and dimethyl sulphide (DMS), will have a bearing on the atmospheric heat budget. While the former facilitates the trapping of radiation (greenhouse effect) the latter works in the opposite direction through reflectance of radiation back into space by sulphate aerosols that form from oxidation of DMS in atmosphere. Here we report on the first measurements made on DMS in the Bay of Bengal and the factors regulating its abundance in seawater. Phytoplankton alone does not seem to control the extent of DMS concentrations. We find that changes in salinity could effectively regulate the extent of DMSP production by marine phytoplankton. In addition, we provide the first ever evidence to the occurrence of DMS precursor, DMSP, in marine aerosols collected in the boundary layer. This suggests that the marine aerosol transport of DMSP will supplement DMS gaseous evasion in maintaining the atmospheric non-sea salt sulphur budget.
Shi Yingjing; Ma Guangfu; Ma Hongzhong
A global controller design methodology for a flight stage of the cruise missile is proposed.This methodology is based on the method of least squares.To prove robust stability in the full airspace with parameter disturbances.the Concepts of Convex polytopic models and quadratic stability are introduced.The effect of aerodynamic parameters on system performance is analyzed.The designed controller is applied to track the over loading signal of the cruise segment of the cruise missile,avoiding system disturbance owing to controller switching.Simulation results demonstrate the validity of the proposed method.
Basden, Alastair; Geng, Deli; Myers, Richard; Younger, Eddy
The Durham adaptive optics (AO) real-time controller was initially a proof of concept design for a generic AO control system. It has since been developed into a modern and powerful central-processing-unit-based real-time control system, capable of using hardware acceleration (including field programmable gate arrays and graphical processing units), based primarily around commercial off-the-shelf hardware. It is powerful enough to be used as the real-time controller for all currently planned 8 m class telescope AO systems. Here we give details of this controller and the concepts behind it, and report on performance, including latency and jitter, which is less than 10 μs for small AO systems.
Full Text Available In this study, vertical rail vehicle vibrations are controlled by the use of conventional PID and parameters which are adaptive to PID controllers. A parameters adaptive PID controller is designed to improve the passenger comfort by intuitional usage of this method that renews the parameters online and sensitively under variable track inputs. Sinusoidal vertical rail misalignment and measured real rail irregularity are considered as two different disruptive effects of the system. Active vibration control is applied to the system through the secondary suspension. The active suspension application of rail vehicle is examined by using 5-DOF quarter-rail vehicle model by using Manchester benchmark dynamic parameters. The new parameters of adaptive controller are optimized by means of genetic algorithm toolbox of MATLAB. Simulations are performed at maximum urban transportation speed (90 km/h of the rail vehicle with ±5% load changes of rail vehicle body to test the robustness of controllers. As a result, superior performance of parameters of adaptive controller is determined in time and frequency domain.
Full Text Available Problem statement: Research into robot motion control offers research opportunities that will change scientists and engineers for year to come. Autonomous robots are increasingly evident in many aspects of industry and everyday life and a robust robot motion control can be used for homeland security and many consumer applications. This study discussed the adaptive fuzzy knowledge based controller for robot motion control in indoor and outdoor environment. Approach: The proposed method consisted of two components: the process monitor that detects changes in the process characteristics and the adaptation mechanism that used information passed to it by the process monitor to update the controller parameters. Results: Experimental evaluation had been done in both indoor and outdoor environment where the robot communicates with the base station through its Wireless fidelity antenna and the performance monitor used a set of five performance criteria to access the fuzzy knowledge based controller. Conclusion: The proposed method had been found to be robust.
Morales, S.; Dahhou, B.; Dilhac, J.M. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Morales, S.
In Rapid Thermal Processing (RTP) control of the wafer temperature during all processing to get good trajectory following, together with spatial temperature uniformity, is essential. It is well know as RTP process is nonlinear, classical control laws are not very efficient. In this work, the authors aim at studying the applicability of MIMO (Multiple Inputs Multiple Outputs) adaptive techniques to solve the temperature control problems in RTP. A multivariable linear discrete time CARIMA (Controlled Auto Regressive Integrating Moving Average) model of the highly non-linear process is identified on-line using a robust identification technique. The identified model is used to compute an infinite time LQ (Linear Quadratic) based control law, with a partial state reference model. This reference model smooths the original setpoint sequence, and at the same time gives a tracking capability to the LQ control law. After an experimental open-loop investigation, the results of the application of the adaptive control law are presented. Finally, some comments on the future difficulties and developments of the application of adaptive control in RTP are given. (author) 13 refs.
Gómez, E.; A. S. Poznyak; Lozano, R, R.
Existen en la literatura de Control Adaptable, diferentes procedimientos en los que es posible identificar un sistema lineal. El problema fundamental es que una cantidad importante de fenómenos de la vida real son de tipo no lineal y no es tan sencillo el modelar este tipo de dinámicas. En este trabajo se presenta una forma de identificar sistemas no lineales utilizando las propiedades de las Redes Neuronales Artificiales y las técnicas de Algoritmo Genético en la optimización de ...
Frost, Susan A.; Balas, Mark J.
Many dynamic systems containing a large number of modes can benefit from adaptive control techniques, which are well suited to applications that have unknown parameters and poorly known operating conditions. In this paper, we focus on a model reference direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend this adaptive control theory to accommodate problematic modal subsystems of a plant that inhibit the adaptive controller by causing the open-loop plant to be non-minimum phase. We will augment the adaptive controller using a Residual Mode Filter (RMF) to compensate for problematic modal subsystems, thereby allowing the system to satisfy the requirements for the adaptive controller to have guaranteed convergence and bounded gains. We apply these theoretical results to design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed wind turbine that has minimum phase zeros.
Selinger, Jessica C; Donelan, J Maxwell
We have designed and tested a myoelectric controller that automatically adapts energy harvesting from the motion of leg joints to match the power available in different walking conditions. To assist muscles in performing negative mechanical work, the controller engages power generation only when estimated joint mechanical power is negative. When engaged, the controller scales its resistive torque in proportion to estimated joint torque, thereby automatically scaling electrical power generation in proportion to the available mechanical power. To produce real-time estimates of joint torque and mechanical power, the controller leverages a simple model that predicts these variables from measured muscle activity and joint angular velocity. We first tested the model using available literature data for a range of walking speeds and found that estimates of knee joint torque and power well match the corresponding literature profiles (torque R(2): 0.73-0.92; power R(2): 0.60-0.94). We then used human subject experiments to test the performance of the entire controller. Over a range of steady state walking speeds and inclines, as well as a number of non-steady state walking conditions, the myoelectric controller accurately identified when the knee generated negative mechanical power, and automatically adjusted the magnitude of electrical power generation. PMID:26841402
... Counterfeit Drugs Cruise Ship Travel Families with Children Fish Poisoning in Travelers Food and Water Getting Health ... INJURY ABOARD CRUISE SHIPS Cruise ship medical clinics deal with a wide variety of illnesses and injuries. ...
Full Text Available Multimedia communications are communications with several types of media, such as audio, video and data. The current Internet has some levels of capability to support multimedia communications, unfortunately, the QoS (Quality of Service is still challenging. A large number of QoS mechanisms has been proposed; however, the main concern is for low levels, e.g. layer 2 (Data Link or 3 (Transport. In this paper, mechanisms for control the quality of audio and video are proposed. G.723.1 and MPEG-4 are used as the audio and video codec respectively. The proposed algorithm for adaptive quality control of audio communication is based on forward error correction (FEC. In the case of video communication, the proposed algorithm adapts the value of key frame interval, which is an encoding parameter of MPEG-4. We evaluated our proposed algorithms by computer simulation. We have shown that, in most cases, the proposed scheme gained a higher throughput compared to other schemes.
Handelman, David A.
The agility and adaptability of biological systems are worthwhile goals for next-generation unmanned ground vehicles. Management of the requisite number of degrees of freedom, however, remains a challenge, as does the ability of an operator to transfer behavioral intent from human to robot. This paper reviews American Android research funded by NASA, DARPA, and the U.S. Army that attempts to address these issues. Limb coordination technology, an iterative form of inverse kinematics, provides a fundamental ability to control balance and posture independently in highly redundant systems. Goal positions and orientations of distal points of the robot skeleton, such as the hands and feet of a humanoid robot, become variable constraints, as does center-of-gravity position. Behaviors utilize these goals to synthesize full-body motion. Biped walking, crawling and grasping are illustrated, and behavior parameterization, layering and portability are discussed. Robotic skill acquisition enables a show-and-tell approach to behavior modification. Declarative rules built verbally by an operator in the field define nominal task plans, and neural networks trained with verbal, manual and visual signals provide additional behavior shaping. Anticipated benefits of the resultant adaptive collaborative controller for unmanned ground vehicles include increased robot autonomy, reduced operator workload and reduced operator training and skill requirements.
Balas, Mark J.; Frost, Susan
Flexible structures containing a large number of modes can benefit from adaptive control techniques which are well suited to applications that have unknown modeling parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend our adaptive control theory to accommodate troublesome modal subsystems of a plant that might inhibit the adaptive controller. In some cases the plant does not satisfy the requirements of Almost Strict Positive Realness. Instead, there maybe be a modal subsystem that inhibits this property. This section will present new results for our adaptive control theory. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for the troublesome modal subsystem, or the Q modes. Here we present the theory for adaptive controllers modified by RMFs, with attention to the issue of disturbances propagating through the Q modes. We apply the theoretical results to a flexible structure example to illustrate the behavior with and without the residual mode filter. We have proposed a modified adaptive controller with a residual mode filter. The RMF is used to accommodate troublesome modes in the system that might otherwise inhibit the adaptive controller, in particular the ASPR condition. This new theory accounts for leakage of the disturbance term into the Q modes. A simple three-mode example shows that the RMF can restore stability to an otherwise unstable adaptively controlled system. This is done without modifying the adaptive controller design.
Henningsen, Arne; Ravn, Ole
A comparison of the standard concepts in MRAC design suggests that a combination of the implicit and the explicit design techniques may lead to an improvement of the overall system performance in the presence of unmodelled dynamics. Using the ideas of adaptive stability augmentation a combined...
Linearization by feedback of states is based on the idea of transform the nonlinear dynamic equation of a system in a linear form. This linear behavior can be achieve well in a complete way (input state) or in partial way (input output). This can be applied to systems of single or multiple inputs, and can be used to solve problems of stabilization and tracking of references trajectories. Comparing this method with conventional ones, linearization by feedback of states is exact in certain region of the space of state, instead of linear approximations of the equations in a certain point of the operation. In the presence of parametric uncertainties in the model of the system, the introduction of adaptive schemes provide a type toughness to the control system by nonlinear feedback, which gives as result the eventual cancellation of the nonlinear terms in the dynamic relationship between the output and the input of the auxiliary control. In the same way, it has been presented the design of a nonlinearizing control for the non lineal model of a TRIGA Mark III type reactor, with the aim of tracking a predetermined power profile. The asymptotic tracking of such profile is, at the present moment, in the stage of verification by computerized simulation the relative easiness in the design of auxiliary variable of control, as well as the decoupling action of the output variable, make very attractive the utilization of the method herein presented. (Author)
Kedar-Dongarkar, Gurunath; Weslati, Feisel
A powertrain control system for a plugin hybrid electric vehicle. The system comprises an adaptive charge sustaining controller; at least one internal data source connected to the adaptive charge sustaining controller; and a memory connected to the adaptive charge sustaining controller for storing data generated by the at least one internal data source. The adaptive charge sustaining controller is operable to select an operating mode of the vehicle's powertrain along a given route based on programming generated from data stored in the memory associated with that route. Further described is a method of adaptively controlling operation of a plugin hybrid electric vehicle powertrain comprising identifying a route being traveled, activating stored adaptive charge sustaining mode programming for the identified route and controlling operation of the powertrain along the identified route by selecting from a plurality of operational modes based on the stored adaptive charge sustaining mode programming.
Full Text Available For the generator excitation control system which is equipped with static var compensator (SVC and unknown parameters, a novel adaptive dynamic surface control scheme is proposed based on neural network and tracking error transformed function with the following features: (1 the transformation of the excitation generator model to the linear systems is omitted; (2 the prespecified performance of the tracking error can be guaranteed by combining with the tracking error transformed function; (3 the computational burden is greatly reduced by estimating the norm of the weighted vector of neural network instead of the weighted vector itself; therefore, it is more suitable for the real time control; and (4 the explosion of complicity problem inherent in the backstepping control can be eliminated. It is proved that the new scheme can make the system semiglobally uniformly ultimately bounded. Simulation results show the effectiveness of this control scheme.
Ivlev, B I
Process of quantum tunneling of particles in various physical systems can be effectively controlled even by a weak and slow varying in time electromagnetic signal if to adapt specially its shape to a particular system. During an under-barrier motion of a particle such signal provides a "coherent" assistance of tunneling by the multi-quanta absorption resulting in a strong enhancement of the tunneling probability. The semiclassical approach based on trajectories in the complex time is developed for tunneling in a non-stationary field. Enhancement of tunneling occurs when a singularity of the signal coincides in position at the complex time plane with a singularity of the classical Newtonian trajectory of the particle. The developed theory is also applicable to the over-barrier reflection of particles and to reflection of classical waves (electromagnetic, hydrodynamic, etc.) from a spatially-smooth medium.
Jantzen, Jan; Poulsen, Niels Kjølstad
This simulation study provides an analysis of the adaptation mechanism in the self-organising fuzzy controller, SOC. The approach is to apply a traditional adaptive control viewpoint. A simplified performance measure in the SOC controller is used in a loss function, and thus the MIT rule implies...... an update mechanism similar to the SOC update mechanism. Two simulations of proportionally controlled systems show the behaviour of the proportional gain as it adapts to a specified behaviour....
巡航控制是保证车辆安全行驶的基本功能之一，更是车辆自主行驶的关键技术。针对无人车的巡航控制问题，本文首先回顾和评述了前人的研究工作，然后选择了一款两轮驱动的无人车模型，考虑了安全车辆之间相对距离的限制因素、速度的限制因素、传感器时间滞后因素，设计了简化的巡航控制律，并在MATLAB下完成了仿真验证，仿真结果证明了设计思路的可行性。%Cruise control is one of the basic functions of vehicle for safely running, it's also one of typical features of the autonomous vehicles. In this paper, problems related with cruise control of unmanned ground vehicle were proposed and associated preceding contributions were reviewed. One kind of practical unmanned ground vehicle was chosen as the research model, safe relative distance, relative speed and time delay of sensors and actuators are considered as constraints, the research model was simplified, related control law was presented and control system model was constructed under the MATLAB, simulation was performed and the simulation result verified the feasibility of the proposed control law.
Prabhu, K; V. Murali Bhaskaran
Continues Stirred Tank Reactor (CSTR) is an important issue in chemical process and a wide range of research in the area of chemical engineering. Temperature Control of CSTR has been an issue in the chemical control engineering since it has highly non-linear complex equations. This study presents problem of temperature control of CSTR with the adaptive Controller. The Simulation is done in MATLAB and result shows that adaptive controller is an efficient controller for temperature control of C...
Wei Wei; Li Dong-Hai; Wang Jing
The chaos control of uncertain unified chaotic systems is considered. Cascade adaptive control approach with only one control input is presented to stabilize states of the uncertain unified chaotic system at the zero equilibrium point.Since an adaptive controller based on dynamic compensation mechanism is employed, the exact model of the unified chaotic system is not necessarily required.By choosing appropriate controller parameters, chaotic phenomenon can be suppressed and the response speed is tunable. Sufficient condition for the asymptotic stability of the approach is derived. Numerical simulation results confirm that the cascade adaptive control approach with only one control signal is valid in chaos control of uncertain unified chaotic systems.
van Nort, Douglas
parameters. In this view, desired gestural dynamics and sonic response are achieved through modular construction of mapping layers that are themselves subject to parametric control. Complementing this view of the design process, the work concludes with an approach in which the creation of gestural control/sound dynamics are considered in the low-level of the underlying sound model. The result is an adaptive system that is specialized to noise-based transformations that are particularly relevant in an electroacoustic music context. Taken together, these different approaches to design and evaluation result in a unified framework for creation of an instrumental system. The key point is that this framework addresses the influence that mapping structure and control dynamics have on the perceived feel of the instrument. Each of the results illustrate this using either top-down or bottom-up approaches that consider musical control context, thereby pointing to the greater potential for refined sonic articulation that can be had by combining them in the design process.
Andersen, T.O.; Hansen, M.R.; Conrad, Finn
A method for synthesis of a robust adaptive scheme for a hydraulically driven manipulator, that takes full advantage of any known system dynamics to simplify the adaptive control problem for the unknown portion of the dynamics is presented. The control method is based on adaptive perturbation con...... joint behaves as an independent second-order system with fixed dynamics.......A method for synthesis of a robust adaptive scheme for a hydraulically driven manipulator, that takes full advantage of any known system dynamics to simplify the adaptive control problem for the unknown portion of the dynamics is presented. The control method is based on adaptive perturbation...... control.Using the Lyapunov approach, under slowly time-varying assumptions, it is shown that the tracking error and the parameter error remain bounded. This bound is a function of the ideal parameters and a bounded disturbance. The control algorithm decouples and linearizes the manipulator so that each...
Satoh, Yasuyuki; Nakamura, Hisakazu; Katayama, Hitoshi; Nishitani, Hirokazu
In this article, we proposed an adaptive inverse optimal controller for the magnetic levitation system. First, we designed an inverse optimal controller with a pre-feedback gravity compensator and applied it to the magnetic levitation system. However, this controller cannot guarantee any stability margin. We demonstrated that the controller did not work well (offset error remained) in the experiment. Hence, we proposed an improved controller via an adaptive control technique to guarantee the ...
Grzegorz Mikułowski; Łukasz Jankowski
An adaptive landing gear is a landing gear (LG) capable of active adaptation to particular landing conditions by means of controlled hydraulic force. The objective of the adaptive control is to mitigate the peak force transferred to the aircraft structure during touch-down, and thus to limit the structural fatigue factor. This paper investigates the ultimate limits for improvement due to various strategies of active control. Five strategies are proposed and investigated numerically using a~va...
Juntao Fei; Hongfei Ding
This paper presents an adaptive control approach for Micro-Electro-Mechanical Systems (MEMS) z-axis gyroscope sensor. The dynamical model of MEMS gyroscope sensor is derived and adaptive state tracking control for MEMS gyroscope is developed. The proposed adaptive control approaches can estimate the angular velocity and the damping and stiffness coefficients including the coupling terms due to the fabrication imperfection. The stability of the closed-loop systems is established with the propo...
Presents an adaptive controller for continuous systems with unknown deadzones and known linear part which consists of an adaptive deadzone inverse to cancel the effects of deadzone and a linear-like control law to track the system output. It concludes from simulation results that this control possesses good robustness and improves the tracking performance of the system.
Baldi, Simone; Battistelli, Giorgio; Mari, Daniele; Mosca, Edoardo; Tesi, Pietro
This paper addresses the problem of controlling an uncertain multi-input multi-output (MIMO) system by means of adaptive switching control schemes. In particular, the paper aims at extending the approach of multiple-model unfalsified adaptive switched control, so far restricted to single-input singl
BLANCH Carolina; POLLIN Sofie; LAFRUIT Gauthier; EBERLE Wolfgang
Low energy consumption is one of the main challenges for wireless video transmission on battery limited devices. The energy invested at the lower layers of the protocol stack involved in data communication, such as link and physical layer, represent an important part of the total energy consumption. This communication energy highly depends on the channel conditions and on the transmission data rate. Traditionally, video coding is unaware of varying channel conditions. In this paper, we propose a cross-layer approach in which the rate control mechanism of the video codec becomes channel-aware and steers the instantaneous output rate according to the channel conditions to reduce the communication energy. Our results show that energy savings of up to30% can be obtained with a reduction of barely 0.1 dB on the average video quality. The impact of feedback delays is shown to be small. In addition, this adaptive mechanism has low complexity, which makes it suitable for real-time applications.
Full Text Available The problem of robust adaptive stabilization of a class of multi-input nonlinear systems with arbitrary unknown parameters and unknown structure of bounded variation have been considered. By employing the direct adaptive and control Lyapunov function method, a robust adaptive controller is designed to complete the globally adaptive stability of the system states. By employing our result, a kind of nonlinear system is analyzed, the concrete form of the control law is given and the meaningful quadratic control Lyapunov function for the system is constructed. Simulation of parallel manipulator is provided to illustrate the effectiveness of the proposed method.
National Aeronautics and Space Administration — Adaptive control offers an opportunity to fulfill present and future aircraft safety objectives though automated vehicle recovery while maintaining performance and...
LIU Hai-ou; CHEN Hui-yan; DING Hua-rong; HE Zhong-bo
Based on detail analysis of clutch engaging process control targets and adaptive demands, a control strategy which is based on speed signal, different from that of based on main clutch displacement signal, is put forward. It considers both jerk and slipping work which are the most commonly used quality evaluating indexes of vehicle starting phase. The adaptive control system and its reference model are discussed profoundly.Taking the adaptability to different starting gears and different road conditions as examples, some proving field test records are shown to illustrate the main clutch adaptive control strategy at starting phase. Proving field test gives acceptable results.
National Aeronautics and Space Administration — Adaptive control offers an opportunity to fulfill aircraft safety objectives though automated vehicle recovery while maintaining performance and stability...
Taleb, M.; Plestan, F.
This paper proposes, for a class of uncertain nonlinear systems, an adaptive controller based on adaptive second-order sliding mode control and integral sliding mode control concepts. The adaptation strategy solves the problem of gain tuning and has the advantage of chattering reduction. Moreover, limited information about perturbation and uncertainties has to be known. The control is composed of two parts: an adaptive one whose objective is to reject the perturbation and system uncertainties, whereas the second one is chosen such as the nominal part of the system is stabilised in zero. To illustrate the effectiveness of the proposed approach, an application on an academic example is shown with simulation results.
Verschure, Paul F M J
Understanding the nature of consciousness is one of the grand outstanding scientific challenges. The fundamental methodological problem is how phenomenal first person experience can be accounted for in a third person verifiable form, while the conceptual challenge is to both define its function and physical realization. The distributed adaptive control theory of consciousness (DACtoc) proposes answers to these three challenges. The methodological challenge is answered relative to the hard problem and DACtoc proposes that it can be addressed using a convergent synthetic methodology using the analysis of synthetic biologically grounded agents, or quale parsing. DACtoc hypothesizes that consciousness in both its primary and secondary forms serves the ability to deal with the hidden states of the world and emerged during the Cambrian period, affording stable multi-agent environments to emerge. The process of consciousness is an autonomous virtualization memory, which serializes and unifies the parallel and subconscious simulations of the hidden states of the world that are largely due to other agents and the self with the objective to extract norms. These norms are in turn projected as value onto the parallel simulation and control systems that are driving action. This functional hypothesis is mapped onto the brainstem, midbrain and the thalamo-cortical and cortico-cortical systems and analysed with respect to our understanding of deficits of consciousness. Subsequently, some of the implications and predictions of DACtoc are outlined, in particular, the prediction that normative bootstrapping of conscious agents is predicated on an intentionality prior. In the view advanced here, human consciousness constitutes the ultimate evolutionary transition by allowing agents to become autonomous with respect to their evolutionary priors leading to a post-biological Anthropocene.This article is part of the themed issue 'The major synthetic evolutionary transitions'. PMID
Full Text Available Adaptive structures with controllable geometries and shapes are rather useful in many engineering applications, such as adaptive wings, variable focus mirrors, adaptive machines, micro-electromechanical systems, etc. Dynamics and feedback control effectiveness of adaptive shells whose curvatures are actively controlled and continuously changed are evaluated. An adaptive piezoelectric laminated cylindrical shell composite with continuous curvature changes is studied, and its natural frequencies and controlled damping ratios are evaluated. The curvature change of the adaptive shell starts from an open shallow shell (30° and ends with a deep cylindrical shell (360°. Dynamic characteristics and control effectiveness (via the proportional velocity feedback of this series of shells are investigated and compared at every 30° curvature change. Analytical solutions suggest that the lower modes are sensitive to curvature changes and the higher modes are relatively insensitive.
The paper describes the design considerations and implementational aspects of the Adaptive Blockset for Simulink which has been developed in a prototype implementation. The concept behind the Adaptive Blockset for Simulink is to bridge the gap between simulation and prototype controller...... implementation. This is done using the code generation capabilities of Real Time Workshop in combination with C s-function blocks for adaptive control in Simulink. In the paper the design of each group of blocks normally found in adaptive controllers is outlined. The block types are, identification, controller...... design, controller and state variable filter.The use of the Adaptive Blockset is demonstrated using a simple laboratory setup. Both the use of the blockset for simulation and for rapid prototyping of a real-time controller are shown....
Nguyen, Charles C.; Antrazi, Sami S.
The implementation of a joint-space adaptive control scheme used to control non-compliant motion of a Stewart Platform-based Manipulator (SPBM) is presented. The SPBM is used in a facility called the Hardware Real-Time Emulator (HRTE) developed at Goddard Space Flight Center to emulate space operations. The SPBM is comprised of two platforms and six linear actuators driven by DC motors, and possesses six degrees of freedom. The report briefly reviews the development of the adaptive control scheme which is composed of proportional-derivative (PD) controllers whose gains are adjusted by an adaptation law driven by the errors between the desired and actual trajectories of the SPBM actuator lengths. The derivation of the adaptation law is based on the concept of model reference adaptive control (MRAC) and Lyapunov direct method under the assumption that SPBM motion is slow as compared to the controller adaptation rate. An experimental study is conducted to evaluate the performance of the adaptive control scheme implemented to control the SPBM to track a vertical and circular paths under step changes in payload. Experimental results show that the adaptive control scheme provides superior tracking capability as compared to fixed-gain controllers.
Taeed, Fazel; Nymand, Morten
An adaptive slope compensation method for digital current mode control of dc-dc converters is proposed in this paper. The compensation slope is used for stabilizing the inner current loop in peak current mode control. In this method, the compensation slope is adapted with the variations...... in converter duty cycle. The adaptive slope compensation provides optimum controller operation in term of bandwidth over wide range of operating points. In this paper operation principle of the controller is discussed. The proposed controller is implemented in an FPGA to control a 100 W buck converter...
Sun, B.; Salter, P. S.; Booth, M. J.
The focusing of ultrashort laser pulses is extremely important for processes including microscopy, laser fabrication and fundamental science. Adaptive optic elements, such as liquid crystal spatial light modulators or membrane deformable mirrors, are routinely used for the correction of aberrations in these systems, leading to improved resolution and efficiency. Here, we demonstrate that adaptive elements used with ultrashort pulses should not be considered simply in terms of wavefront modification, but that changes to the incident pulse front can also occur. We experimentally show how adaptive elements may be used to engineer pulse fronts with spatial resolution.
Full Text Available In this paper, an adaptive controller is designed for a UAV flight control system against faults and parametric uncertainties based on quantum information technology and the Popov hyperstability theory. First, considering the bounded control input, the state feedback controller is designed to make the system stable. The model of adaptive control is introduced to eliminate the impact by the uncertainties of system parameters via quantum information technology. Then, according to the model reference adaptive principle, an adaptive control law based on the Popov hyperstability theory is designed. This law enable better robustness of the flight control system and tracking control performances. The closed‐loop system’s stability is guaranteed by the Popov hyperstability theory. The simulation results demonstrate that a better dynamic performance of the UAV flight control system with faults and parametric uncertainties can be maintained with the proposed method.
ZHANG Yanxia; GUO Lei
It is well known that the transient behaviors of the traditional adaptive control may be very poor in general, and that the adaptive control designed based on switching between multiple models is an intuitively appealing and practically feasible approach to improve the transient performances. In this paper, we shall prove that for a typical class of linear systems disturbed by random noises, the multiple model based least-squares (LS)adaptive switching control is stable and convergent, and has the same convergence rate as that established for the standard least-squares-based self-tunning regulators. Moreover,the mixed case combining adaptive models with fixed models is also considered.
National Aeronautics and Space Administration — To address NASA needs for quiet crew volumes in a space habitat, Physical Optics Corporation (POC) proposes to develop a new Adaptive Intelligent Ventilation Noise...
National Aeronautics and Space Administration — To address the NASA need for quiet on-orbit crew quarters (CQ), Physical Optics Corporation (POC) proposes to develop a new Adaptive Intelligent Ventilation Noise...
Jiangyan ZHANG; Xiaohong JIAO
In this paper, the control problem of auxiliary power unit (APU) for hybrid electric vehicles is investigated. An adaptive controller is provided to achieve the coordinated control between the engine speed and the battery charging voltage. The proposed adaptive coordinated control laws for the throttle angle of the engine and the voltage of the power-converter can guarantee not only the asymptotic tracking performance of the engine speed and the regulation of the battery charging voltage, but also the robust stability of the closed loop system under external load changes. Simulation results are given to verify the performance of the proposed adaptive controller.
Xiao-juan WU; Xin-jian ZHU; Guang-yi CAO; Heng-yong TU
The operating temperature of a solid oxide fuel cell (SOFC) stack is a very important parameter to be controlled, which impacts the performance of the SOFC due to thermal cycling. In this paper, an adaptive fuzzy control method based on an affine nonlinear temperature model is developed to control the temperature of the SOFC within a specified range. Fuzzy logic systems are used to approximate nonlinear functions in the SOFC system and an adaptive technique is employed to construct the controller. Compared with the traditional fuzzy and proportion-integral-derivative (PID) control, the simulation results show that the designed adaptive fuzzy control method performed much better. So it is feasible to build an adaptive fuzzy controller for temperature control of the SOFC.
Full Text Available Continues Stirred Tank Reactor (CSTR is an important issue in chemical process and a wide range of research in the area of chemical engineering. Temperature Control of CSTR has been an issue in the chemical control engineering since it has highly non-linear complex equations. This study presents problem of temperature control of CSTR with the adaptive Controller. The Simulation is done in MATLAB and result shows that adaptive controller is an efficient controller for temperature control of CSTR than PID controller.
Jin J; Allison B.Z.; Sellers E.W.; Brunner & C.; Horki P.; Wang X; Neuper C.
An adaptive P300 brain-computer interface (BCI) using a 12 × 7 matrix explored new paradigms to improve bit rate and accuracy. During online use, the system adaptively selects the number of flashes to average. Five different flash patterns were tested. The 19-flash paradigm represents the typical row/column presentation (i.e., 12 columns and 7 rows). The 9- and 14-flash A & B paradigms present all items of the 12 × 7 matrix three times using either nine or 14 flashes (instead of 19), decreasi...
GUAN Ping; LIU Xiang-dong; CHEN Jia-bin; LIU Xiao-he
The adaptive fuzzy control is combined with input-output linearization control to constitute the hybrid controller. The control method is then applied to the attitude maneuver control of the flexible satellite.The basic control structure is given. The rules of the controller parameter selection, which guarantee the attitude stabilization of the satellite with parameter uncertainties, have been analyzed. Simulation results show that the precise attitude control is accomplished in spite of the uncertainty in the system.
WUZhao-Jing; XIEXue-Jun; ZHANGSi-Ying
For a class of systems with unmodeled dynamics, robust adaptive stabilization problem is considered in this paper. Firstly， by a series of coordinate changes, the original system is reparameterized. Then, by introducing a reduced-order observer, an error system is obtained. Based on the system, a reduced-order adaptive backstepping controller design scheme is given. It is proved that all the signals in the adaptive control system are globally uniformly bounded, and the regulation error converges to zero asymptotically. Due to the order deduction of the controller, the design scheme in this paper has more practical values. A simulation example further demonstrates the efficiency of the control scheme.
Ian A. Gravagne
Full Text Available It has been known for some time that proportional output feedback will stabilize MIMO, minimum-phase, linear time-invariant systems if the feedback gain is sufficiently large. High-gain adaptive controllers achieve stability by automatically driving up the feedback gain monotonically. More recently, it was demonstrated that sample-and-hold implementations of the high-gain adaptive controller also require adaptation of the sampling rate. In this paper, we use recent advances in the mathematical field of dynamic equations on time scales to unify and generalize the discrete and continuous versions of the high-gain adaptive controller. We prove the stability of high-gain adaptive controllers on a wide class of time scales.
Hormetic dose response occurs for many endpoints associated with exposures of biological organisms to environmental stressors. Cell-based U- or inverted U-shaped responses may derive from common processes involved in activation of adaptive responses required to protect cells from...
Kim, J. D. [Cowell SysNet, Seoul (Korea); Lee, M. J.; Choi, Y. K.; Kim, S. S. [Pusan National University, Pusan (Korea)
This paper investigates the direct adaptive control of nonlinear systems using RBFN(radial basis function networks). The structure of the controller consists of a fixed PD controller and a RBFN controller in parallel. An adaptation law for the parameters of RBFN is developed based on the Lyapunov stability theory to guarantee the stability of the overall control system. The filtered tracking error between the system output and the desired output is shown to be UUB(uniformly ultimately bounded). To evaluate the performance of the controller, the proposed method is applied to the trajectory control of the two-link manipulator. (author). 18 refs., 14 figs., 2 tabs.
Johnson, Kathryn E.
Wind is a clean, renewable resource that has become more popular in recent years due to numerous advances in technology and public awareness. Wind energy is quickly becoming cost competitive with fossil fuels, but further reductions in the cost of wind energy are necessary before it can grow into a fully mature technology. One reason for higher-than-necessary cost of the wind energy is uncertainty in the aerodynamic parameters, which leads to inefficient controllers. This thesis explores an adaptive control technique designed to reduce the negative effects of this uncertainty. The primary focus of this work is a new adaptive controller that is designed to resemble the standard non-adaptive controller used by the wind industry. The standard controller was developed for variable speed wind turbines operating below rated power. The new adaptive controller uses a simple, highly intuitive gain adaptation law intended to seek out the optimal gain for maximizing the turbine's energy capture. It is designed to work even in real, time-varying winds. The adaptive controller has been tested both in simulation and on a real turbine, with numerous experimental results provided in this work. Simulations have considered the effects of erroneous wind measurements and time-varying turbine parameters, both of which are concerns on the real turbine. The adaptive controller has been found to operate as desired under realistic operating conditions, and energy capture has increased on the real turbine as a result. Theoretical analyses of the standard and adaptive controllers were performed, as well, providing additional insight into the system. Finally, a few extensions were made with the intent of making the adaptive control idea even more appealing in the commercial wind turbine market.
This thesis concerns speed control of current vector controlled induction motor drives (CVC drives). The CVC drive is an existing prototype drive developed by Danfoss A/S, Transmission Division. Practical tests have revealed that the open loop dynamical properties of the CVC drive are highly......, (LS) identification and generalized predictive control (GPC) has been implemented and tested on the CVC drive. Allthough GPC is a robust control method, it was not possible to maintain specified controller performance in the entire operating range. This was the main reason for investigating truly...... adaptive speed control of the CVC drive. A direct truly adaptive speed controller has been implemented. The adaptive controller is a moving Average Self-Tuning Regulator which is abbreviated MASTR throughout the thesis. Two practical implementations of this controller were proposed. They were denoted MASTR...
Luković, Tihomir; Asić, Antun; Šperanda, Ivo
Cruising tourism is the largest growing tourism sub-system. The importance of cruising tourism should be viewed in a far wider context than tourism itself. Namely, cruising tourism is maintained by numerous shareholders whose interests need to be reassured for the purpose of sustainable destination development. Tourism’s sub-system, cruise ships, in comparison to the sub-system of coastal tourism, has its own specifics which may easily prove contradictory in itself and thus compromise sustain...
© 2015 Mathematical Sciences Publishers. Adaptive step-size control is a critical feature for the robust and efficient numerical solution of initial-value problems in ordinary differential equations. In this paper, we show that adaptive step-size control can be incorporated within a family of parallel time integrators known as revisionist integral deferred correction (RIDC) methods. The RIDC framework allows for various strategies to implement stepsize control, and we report results from exploring a few of them.
Hanson, Curt; Schaefer, Jacob; Johnson, Marcus; Nguyen, Nhan
Flight research experiments have demonstrated that adaptive flight controls can be an effective technology for improving aircraft safety in the event of failures or damage. However, the nonlinear, timevarying nature of adaptive algorithms continues to challenge traditional methods for the verification and validation testing of safety-critical flight control systems. Increasingly complex adaptive control theories and designs are emerging, but only make testing challenges more difficult. A potential first step toward the acceptance of adaptive flight controllers by aircraft manufacturers, operators, and certification authorities is a very simple design that operates as an augmentation to a non-adaptive baseline controller. Three such controllers were developed as part of a National Aeronautics and Space Administration flight research experiment to determine the appropriate level of complexity required to restore acceptable handling qualities to an aircraft that has suffered failures or damage. The controllers consist of the same basic design, but incorporate incrementally-increasing levels of complexity. Derivations of the controllers and their adaptive parameter update laws are presented along with details of the controllers implementations.
Stress initiates adaptive processes that allow the organism to physiologically cope with prolonged or intermittent exposure to real or perceived threats. A major component of this response is repeated activation of glucocorticoid secretion by the hypothalamo-pituitary-adrenocortical (HPA) axis, which promotes redistribution of energy in a wide range of organ systems, including the brain. Prolonged or cumulative increases in glucocorticoid secretion can reduce benefits afforded by enhanced s...
Mead, W.C.; Brown, S.K.; Jones, R.D.; Bowling, P.S.; Barnes, C.W.
Recent work has demonstrated the ability of neural-network-based controllers to optimize and control machines with complex, non-linear, relatively unknown control spaces. We present a brief overview of neural networks via a taxonomy illustrating some capabilities of different kinds of neural networks. We present some successful control examples, particularly the optimization and control of a small-angle negative ion source.
Erik D. Engeberg
Full Text Available Eight human test subjects attempted to track a desired position trajectory with an instrumented manipulandum (MN. The test subjects used the MN with three different levels of stiffness. A transfer function was developed to represent the human application of a precision grip from the data when the test subjects initially displaced the MN so as to learn the position mapping from the MN onto the display. Another transfer function was formed from the data of the remainder of the experiments, after significant displacement of the MN occurred. Both of these transfer functions accurately modelled the system dynamics for a portion of the experiments, but neither was accurate for the duration of the experiments because the human grip dynamics changed while learning the position mapping. Thus, an adaptive system model was developed to describe the learning process of the human test subjects as they displaced the MN in order to gain knowledge of the position mapping. The adaptive system model was subsequently validated following comparison with the human test subject data. An examination of the average absolute error between the position predicted by the adaptive model and the actual experimental data yielded an overall average error of 0.34mm for all three levels of stiffness.
Shan Lu; Shijie Xu
A strategy for spacecraft autonomous rendezvous on an elliptical orbit in situation of no orbit information is developed. Lawden equation is used to describe relative motion of two spacecraft. Then an adaptive gain factor is introduced, and an adaptive control law for autonomous rendezvous on the elliptical orbit is designed using Lyapunov approach. The relative motion is proved to be ultimately bounded under this control law, and the final relative position error can achieve the expected magnitude. Simulation results indicate that the adaptive control law can realize autonomous rendezvous on the elliptical orbit with relative state information only.
General neural network inverse adaptive controller haa two flaws: the first is the slow convergence speed; the second is the invalidation to the non-minimum phase system.These defects limit the scope in which the neural network inverse adaptive controller is used.We employ Davidon least squares in training the multi-layer feedforward neural network used in approximating the inverse model of plant to expedite the convergence,and then through constructing the pseudo-plant,a neural network inverse adaptive controller is put forward which is still effective to the nonlinear non-minimum phase system.The simulation results show the validity of this scheme.
Adaptive control techniques are well suited to applications that have unknown modeling parameters and poorly known operating conditions. Many physical systems experience external disturbances that are persistent or continually recurring. Flexible structures and systems with compliance between components often form a class of systems that fail to meet standard requirements for adaptive control. For these classes of systems, a residual mode filter can restore the ability of the adaptive controller to perform in a stable manner. New theory will be presented that enables adaptive control with accommodation of persistent disturbances using residual mode filters. After a short introduction to some of the control challenges of large utility-scale wind turbines, this theory will be applied to a high-fidelity simulation of a wind turbine.
Sonneveldt, L.; Van Oort, E.R.; Chu, Q.P.; Mulder, J.A.
In this paper a theoretical framework for nonlinear adaptive flight control is developed and applied to a simplified, over-actuated nonlinear fighter aircraft model. The framework is based on a modular adaptive backstepping scheme with a new type of nonlinear estimator. The nonlinear estimator is co
Chen Feng-Xiang; Wang Wei; Zhang Wei-Dong
The paper is concerned with adaptive tracking problem for a class of chaotic system with time-varying uncertainty,but bounded by norm polynomial. Based on adaptive technique, it proposes a novel controller to asymptotically track the arbitrary desired bounded trajectory. Simulation on the Rossler chaotic system is performed and the result verifies the effectiveness of the proposed method.
de Sousa Júnior, C; Hermerly, E M
A Neural Network - based control approach for mobile robot is proposed. The weight adaptation is made on-line, without previous learning. Several possible situations in robot navigation are considered, including uncertainties in the model and presence of disturbance. Weight adaptation laws are presented as well as simulation results.
This research focuses on development of L 1 adaptive output-feedback control. The objective is to extend the L1 adaptive control framework to a wider class of systems, as well as obtain architectures that afford more straightforward tuning. We start by considering an existing L1 adaptive output-feedback controller for non-strictly positive real systems based on piecewise constant adaptation law. It is shown that L 1 adaptive control architectures achieve decoupling of adaptation from control, which leads to bounded away from zero time-delay and gain margins in the presence of arbitrarily fast adaptation. Computed performance bounds provide quantifiable performance guarantees both for system output and control signal in transient and steady state. A noticeable feature of the L1 adaptive controller is that its output behavior can be made close to the behavior of a linear time-invariant system. In particular, proper design of the lowpass filter can achieve output response, which almost scales for different step reference commands. This property is relevant to applications with human operator in the loop (for example: control augmentation systems of piloted aircraft), since predictability of the system response is necessary for adequate performance of the operator. Next we present applications of the L1 adaptive output-feedback controller in two different fields of engineering: feedback control of human anesthesia, and ascent control of a NASA crew launch vehicle (CLV). The purpose of the feedback controller for anesthesia is to ensure that the patient's level of sedation during surgery follows a prespecified profile. The L1 controller is enabled by anesthesiologist after he/she achieves sufficient patient sedation level by introducing sedatives manually. This problem formulation requires safe switching mechanism, which avoids controller initialization transients. For this purpose, we used an L1 adaptive controller with special output predictor initialization routine
Kappen, H. J.; Ruiz, H. C.
Path integral (PI) control problems are a restricted class of non-linear control problems that can be solved formally as a Feynman-Kac PI and can be estimated using Monte Carlo sampling. In this contribution we review PI control theory in the finite horizon case. We subsequently focus on the problem how to compute and represent control solutions. We review the most commonly used methods in robotics and control. Within the PI theory, the question of how to compute becomes the question of importance sampling. Efficient importance samplers are state feedback controllers and the use of these requires an efficient representation. Learning and representing effective state-feedback controllers for non-linear stochastic control problems is a very challenging, and largely unsolved, problem. We show how to learn and represent such controllers using ideas from the cross entropy method. We derive a gradient descent method that allows to learn feed-back controllers using an arbitrary parametrisation. We refer to this method as the path integral cross entropy method or PICE. We illustrate this method for some simple examples. The PI control methods can be used to estimate the posterior distribution in latent state models. In neuroscience these problems arise when estimating connectivity from neural recording data using EM. We demonstrate the PI control method as an accurate alternative to particle filtering.
Schulz, Richard; And Others
Research suggests that primary control increases as humans develop from infancy through middle age and then decreases in old age. To minimize losses, individuals rely on cognitively based secondary control processes in middle and old age. Literature on adult control processes is reviewed. (SLD)
Lin, Chih-Min; Peng, Ya-Fu
An adaptive cerebellar model articulation controller (CMAC) is proposed for command to line-of-sight (CLOS) missile guidance law design. In this design, the three-dimensional (3-D) CLOS guidance problem is formulated as a tracking problem of a time-varying nonlinear system. The adaptive CMAC control system is comprised of a CMAC and a compensation controller. The CMAC control is used to imitate a feedback linearization control law and the compensation controller is utilized to compensate the difference between the feedback linearization control law and the CMAC control. The online adaptive law is derived based on the Lyapunov stability theorem to learn the weights of receptive-field basis functions in CMAC control. In addition, in order to relax the requirement of approximation error bound, an estimation law is derived to estimate the error bound. Then the adaptive CMAC control system is designed to achieve satisfactory tracking performance. Simulation results for different engagement scenarios illustrate the validity of the proposed adaptive CMAC-based guidance law. PMID:15940993
Alex M C Smith
Full Text Available In this paper we present a hybrid control scheme, combining the advantages of task-space and joint-space control. The controller is based on a human-like adaptive design, which minimises both control effort and tracking error. Our novel hybrid adaptive controller has been tested in extensive simulations, in a scenario where a Baxter robot manipulator is affected by external disturbances in the form of interaction with the environment and tool-like end-effector perturbations. The results demonstrated improved performance in the hybrid controller over both of its component parts. In addition, we introduce a novel method for online adaptation of learning parameters, using the fuzzy control formalism to utilise expert knowledge from the experimenter. This mechanism of meta-learning induces further improvement in performance and avoids the need for tuning through trial testing.
JIANG Rui; LUO Guiming
The least-squares(LS)algorithm has been used for system modeling for a long time. Without any excitation conditions, only the convergence rate of the common LS algorithm can be obtained. This paper analyzed the weighted least-squares(WLS)algorithm and described the good properties of the WLS algorithm. The WLS algorithm was then used for daptive control of linear stochastic systems to show that the linear closed-loop system was globally stable and that the system identification was consistent. Compared to the past optimal adaptive controller,this controller does not impose restricted conditions on the coefficients of the system, such as knowing the first coefficient before the controller. Without any persistent excitation conditions, the analysis shows that, with the regulation of the adaptive control, the closed-loop system was globally stable and the adaptive controller converged to the one-step-ahead optimal controller in some sense.
李洪兴; 苗志宏; 王家银
This paper focuses on the control problem of the quadruple inverted pendulum by variable universe adaptive fuzzy control.First,the mathematical model on the quadruple inverted pendulum is described and its controllability is versified.Then,an efficient controller on the quadruple inverted pendulum is designed by using variable universe adaptive fuzzy control theory.Finally the simulation of the quadruple inverted pendulum is shown in detail.Besides,the experimental results on the hardware systems,i.e.real object systems,on a single inverted pendulum,a double inverted pendulum and a triple inverted pendulum are briefly introduced.``
Yaonan WANG; Jinzhu PENG; Wei SUN; Hongshan YU; Hui ZHANG
To deal with the uncertainty factors of robotic systems,a robust adaptive tracking controller is Droposed.The knowledge of the uncertainty factors is assumed to be unidentified;the proposed controller can guarantee robustness to parametric and dynamics uncertainties and can also reject any bounded,immeasurable disturbances entering the System.The stability of the proposed controller is proven by the Lyapunov method.The proposed controller can easily be implemented and the stability of the closed system can be ensured;the tracking error and adaptation parameter error are uniformly ultimately bounded(UUB).Finally,some simulation examples are utilized to illustrate the control performance.
National Aeronautics and Space Administration — Most fault adaptive control research addresses the preservation of system stability or functionality in the presence of a specific failure (fault). This paper...
National Aeronautics and Space Administration — The innovation of the proposed project is the development of High Efficiency Lighting with Integrated Adaptive Control (HELIAC) systems to drive plant growth. Solar...
National Aeronautics and Space Administration — The proposed project is the continued development of the High Efficiency Lighting with Integrated Adaptive Control (HELIAC) system. Solar radiation is not a viable...
National Aeronautics and Space Administration — SSCI, in collaboration with Boeing Phantom Works, proposes to develop and test an efficient Integrated Damage Adaptive Control System (IDACS). The proposed system...
National Aeronautics and Space Administration — SSCI proposes to further develop, implement and test the damage-adaptive control algorithms developed in Phase I within the framework of an Integrated Damage...
Nguyen, Nhan T.
This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.
El-Deen, M. M. G. Naser
Significant progress has been made on maximising passive solar heating loads through the careful selection of glazing, orientation and internal mass within building spaces. Control of space heating in buildings of this type has become a complex problem. Additionally, and in common with most building control applications, there is a need to develop control solutions that permit simple and transparent set up and commissioning procedures. This work concerns the development and testing of an adap...
Wrangham, Richard W.; Carmody, Rachel Naomi
Charles Darwin attributed human evolutionary success to three traits. Our social habits and anatomy were important, he said, but the critical feature was our intelligence, because it led to so much else, including such traits as language, weapons, tools, boats, and the control of fire. Among these, he opined, the control of fire was “probably the greatest ever [discovery] made by man, excepting language.” Despite this early suggestion that the control of fire was even more important than tool...
Belik, Vitaly; Hövel, Philipp
We consider recurrent contagious processes on a time-varying network. As a control procedure to mitigate the epidemic, we propose an adaptive rewiring mechanism for temporary isolation of infected nodes upon their detection. As a case study, we investigate the network of pig trade in Germany. Based on extensive numerical simulations for a wide range of parameters, we demonstrate that the adaptation mechanism leads to a significant extension of the parameter range, for which most of the index nodes (origins of the epidemic) lead to vanishing epidemics. We find that diseases with detection times around a week and infectious periods up to 3 months can be effectively controlled. Furthermore the performance of adaptation is very heterogeneous with respect to the index node. We identify index nodes that are most responsive to the adaptation strategy and quantify the success of the proposed adaptation scheme in dependence on the infectious period and detection times.
Alejandro Carrasco Elizalde; Peter Goldsmith
The collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration for an adaptive fuzzy controller developed in this paper. Swarm intelligence is used to adjust the parameters of the membership functions used in the adaptive fuzzy controller. The rules of the cont...
Clark, Frankie J.
Approved for public release; distribution is unlimited. The Adaptive Architectures for Command and Control (A2C2) project is an ongoing research effort sponsored by the Office of Naval Research to explore adaptation in joint command and control. The objective of the project's eighth experiment is to study the adjustments that organizations make when they are confronted with a scenario for which their organizational is ill-suited. To accomplish this, teams will each be in one of two fundame...
Hansen, Poul Erik; Conrad, Finn
Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF).......Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF)....
An H(sub infinity)-NMA architecture for the Crew Launch Vehicle was developed in a state feedback setting. The minimal complexity adaptive law was shown to improve base line performance relative to a performance metric based on Crew Launch Vehicle design requirements for all most all of the Worst-on-Worst dispersion cases. The adaptive law was able to maintain stability for some dispersions that are unstable with the nominal control law. Due to the nature of the H(sub infinity)-NMA architecture, the augmented adaptive control signal has low bandwidth which is a great benefit for a manned launch vehicle.
Ping He; Chun-Guo Jing; Chang-Zhong Chen; Tao Fan; Hassan Saberi Nik
In this paper, the synchronization problem of general complex networks is investigated by using adaptive control schemes. Time-delay coupling, derivative coupling, nonlinear coupling etc. exist universally in real-world complex networks. The adaptive synchronization scheme is designed for the complex network with multiple class of coupling terms. A criterion guaranteeing synchronization of such complex networks is established by employing the Lyapunov stability theorem and adaptive control schemes. Finally, an illustrative example with numerical simulation is given to show the feasibility and efficiency of theoretical results.
Mingjun ZHANG; Huaguang ZHANG
In this paper, a robust adaptive fuzzy control scheme for a class of nonlinear system with uncertainty is proposed. First, using prior knowledge about the plant we obtain a fuzzy model, which is called the generalized fuzzy hyperbolic model (GFHM). Secondly, for the case that the states of the system are not available an observer is designed and a robust adaptive fuzzy output feedback control scheme is developed. The overall control system guarantees that the tracking error converges to a small neighborhood of origin and that all signals involved are uniformly bounded. The main advantages of the proposed control scheme are that the human knowledge about the plant under control can be used to design the controller and only one parameter in the adaptive mechanism needs to be on-line adjusted.
Xiao-Yuan Luo; Zhi-Hao Zhu; Xin-Ping Guan
In this paper, a robust adaptive fuzzy dynamic surface control for a class of uncertain nonlinear systems is proposed. A novel adaptive fuzzy dynamic surface model is built to approximate the uncertain nonlinear functions by only one fuzzy logic system. The approximation capability of this model is proved and the model is implemented to solve the problem that too many approximators are used in the controller design of uncertain nonlinear systems. The shortage of "explosion of complexity" in backstepping design procedure is overcome by using the proposed dynamic surface control method. It is proved by constructing appropriate Lyapunov candidates that all signals of closed-loop systems are semi-globaily uniformly ultimate bounded. Also, this novel controller stabilizes the states of uncertain nonlinear systems faster than the adaptive sliding mode controller (SMC). Two simulation examples are provided to illustrate the effectiveness of the control approach proposed in this paper.
Berkhoff, A.P.; Wesselink, J.M.
Recent implementations of multiple-input multiple-output adaptive controllers for reduction of broadband noise and vibrations provide considerably improved performance over traditional adaptive algorithms. The most significant performance improvements are in terms of speed of convergence, the amount
Zhang, Bi; Hong, Hyokchan; Mao, Zhizhong
The Hammerstein-Wiener model is a block-oriented model, having a linear dynamic block sandwiched by two static nonlinear blocks. This note develops an adaptive controller for a special form of Hammerstein-Wiener nonlinear systems which are parameterized by the key-term separation principle. The adaptive control law and recursive parameter estimation are updated by the use of internal variable estimations. By modeling the errors due to the estimation of internal variables, we establish convergence and stability properties. Theoretical results show that parameter estimation convergence and closed-loop system stability can be guaranteed under sufficient condition. From a qualitative analysis of the sufficient condition, we introduce an adaptive weighted factor to improve the performance of the adaptive controller. Numerical examples are given to confirm the results in this paper.
Yizhong WANG; Huaguang ZHANG; Jun YANG
This paper focuses on the robust adaptive control problems for a class of interval time-delay systems and a class of large-scale interconnected systems. The nonlinear uncertainties of the systems under study are bounded by high-order polynomial functions with unknown gains. Firstly, the adaptive feedback controller which can guarantee the stability of the closed-loop system in the sense of uniform ultimate boundedness is proposed. Then the proposed adaptive idea is extended to robust stabilizing designing method for a class of large-scale interconnected systems. Here, another problem we address is to design a decentralized feedback adaptive controller such that the closed-loop system is stable in the sense of uniform ultimate boundedness for all admissible uncertainties and time-delay. Finally, an illustrative example is given to show the validity of the proposed approach.
National Aeronautics and Space Administration — A novel approach is proposed for the suppression of the aircraft's structural vibration to increase the resilience of the flight control law in the presence of the...
Ran Maopeng; Wang Qing; Hou Delong; Dong Chaoyang
This paper presents an integrated missile guidance and control law based on adaptive fuzzy sliding mode control. The integrated model is formulated as a block-strict-feedback nonlinear system, in which modeling errors, unmodeled nonlinearities, target maneuvers, etc. are viewed as unknown uncertainties. The adaptive nonlinear control law is designed based on backstepping and sliding mode control techniques. An adaptive fuzzy system is adopted to approximate the coupling nonlinear functions of...
Full Text Available A fed-batch alcohol fermentation on a pilot plant scale with a digital supervisory control system was evaluated as an experimental application case study of an adaptive controller. The verification of intrinsically dynamic variations in the characteristics of the fermentation, observed in previous work, showed the necessity of an adaptive control strategy for controller parameter tuning in order to adjust the changes in the specific rates of consumption, growth and product formation during the process. Satisfactory experimental results were obtained for set-point variations and sugar feed concentration load changes in the manipulated inlet flow to the fermenter
Galeazzi, Roberto; Borup, Kasper Trolle; Niemann, Hans Henrik;
This paper investigates the feasibility of operating a wind turbine with lightweight tower in the full load region exploiting an adaptive nonlinear controller that allows the turbine to dynamically lean against the wind while maintaining nominal power output. The use of lightweight structures...... for towers and foundations would greatly reduce the construction cost of the wind turbine, however extra features ought be included in the control system architecture to avoid tower collapse. An adaptive backstepping collective pitch controller is proposed for tower point tracking control, i.e. to modify...
Jens G. Balchen
Full Text Available A technique for the adaptation of controller parameters in a single control loop based upon the estimation of frequency response parameters has been presented in an earlier paper. This paper contains an extension and a generalization of the first method and results in a more versatile solution which is applicable to a wider range of process characteristics. The application of this adaptive control technique is illustrated by a laboratory refrigeration cycle in which the evaporator pressure controls the speed of the compressor.
SZWABE Andrzej; SCHORR Andreas; HAUCK Franz J.; KASSLER Andreas J.
Dynamic adaptation of multimedia content is seen as an important feature of next generation networks and pervasive systems enabling terminals and applications to adapt to changes in e.g. context, access network, and available Quality-of-Service(QoS) due to mobility of users, devices or sessions. We present the architecture of a multimedia stream adaptation service which enables communication between terminals having heterogeneous hardware and software capabilities and served by heterogeneous networks. The service runs on special content adaptation nodes which can be placed at any location within the network. The flexible structure of our architecture allows using a variety of different adaptation engines. A generic transcoding engine is used to change the codec of streams. An MPEG-21 Digital Item Adaptation (DIA) based transformation engine allows adjusting the data rate of scalable media streams. An intelligent decision-taking engine implements adaptive flow control which takes into account current network QoS parameters and congestion information. Measurements demonstrate the quality gains achieved through adaptive congestion control mechanisms under conditions typical for a heterogeneous network.
Kulkarni, Nilesh V.; Kaneshige, John; Krishnakumar, Kalmanje; Burken, John
This paper presents a stable discrete-time adaptive law that targets modeling errors in a direct adaptive control framework. The update law was developed in our previous work for the adaptive disturbance rejection application. The approach is based on the philosophy that without modeling errors, the original control design has been tuned to achieve the desired performance. The adaptive control should, therefore, work towards getting this performance even in the face of modeling uncertainties/errors. In this work, the baseline controller uses dynamic inversion with proportional-integral augmentation. Dynamic inversion is carried out using the assumed system model. On-line adaptation of this control law is achieved by providing a parameterized augmentation signal to the dynamic inversion block. The parameters of this augmentation signal are updated to achieve the nominal desired error dynamics. Contrary to the typical Lyapunov-based adaptive approaches that guarantee only stability, the current approach investigates conditions for stability as well as performance. A high-fidelity F-15 model is used to illustrate the overall approach.
LIU Yu-sheng; CHEN Jiang; LI Xing-yuan
Many physical systems such as biochemical processes and machines with friction are of nonlinearly parameterized systems with uncertainties.How to control such systems effectively is one of the most challenging problems.This paper presents a robust adaptive controller for a significant class of nonlinearly parameterized systems.The controller can be used in cases where there exist parameter and nonlinear uncertainties,unmodeled dynamics and unknown bounded disturbances.The design of the controller is based on the control Lyapunov function method.A dynamic signal is introduced and adaptive nonlinear damping terms are used to restrain the effects of unmodeled dynamics,nonlinear uncertainties and unknown bounded disturbances.The backstepping procedure is employed to overcome the complexity in the design.With the proposed method,the estimation of the unknown parameters of the system is not required and there is only one adaptive parameter no matter how high the order of the system is and how many unknown parameters.there are.It is proved theoretically that the proposed robust adaptive control scheme guarantees the stability of nonlinearly parameterized system.Furthermore,all the states approach the equilibrium in arbitrary precision by choosing some design constants appropriately.Simulation results illustrate the effectiveness of the proposed robust adaptive controller.
Full Text Available This paper presents an application of adaptive neuro-fuzzy (ANFIS control for switched reluctance motor (SRM speed. The ANFIS has the advantages of expert knowledge of the fuzzy inference system and the learning capability of neural networks. An adaptive neuro-fuzzy controller of the motor speed is then designed and simulated. Digital simulation results show that the designed ANFIS speed controller realizes a good dynamic behaviour of the motor, a perfect speed tracking with no overshoot and a good rejection of impact loads disturbance. The results of applying the adaptive neuro-fuzzy controller to a SRM give better performance and high robustness than those obtained by the application of a conventional controller (PI.
Merrill, W.; Leininger, G.
The objective of this paper is to utilize the design methods of modern control theory to realize a 'dual-adaptive' feedback control unit for a highly non-linear single spool airbreathing turbojet engine. Using a very detailed and accurate simulation of the non-linear engine as the data source, linear operating point models of unspecified dimension are identified. Feedback control laws are designed at each operating point for a prespecified set of sampling rates using sampled-data output regulator theory. The control system sampling rate is determined by an adaptive sampling algorithm in correspondence with turbojet engine performance. The result is a 'dual-adpative' control law that is functionally dependent upon the sampling rate selected and environmental operating conditions. Simulation transients demonstrate the utility of the dual-adaptive design to improve on-board computer utilization while maintaining acceptable levels of engine performance.
In the book (Adaptive Identification,Prediction and Control-Multi Level Recursive Approach), the concept of dynamical linearization of nonlinear systems has been presented.This dynamical linearization is formal only,not a real linearization.From the linearization procedure,we can find a new approach of system identification,which is on-line real-time modeling and real-time feedback control correction.The modeling and real-time feedback control have been integrated in the identification approach,with the parameter adaptation model being abandoned.The structure adaptation of control systems has been achieved,which avoids the complex modeling steps.The objective of this paper is to introduce the approach of integrated modeling and control.
YAO Jianyong; JIAO Zongxia; YAO Bin; SHANG Yaoxing; DONG Wenbin
This paper deals with the high performance force control of hydraulic load samulator.Many prevtous works for hydraultc force control are based on their linearization equations,but hydraulic inherent nonlinear properties and uncertainties make the conventional feedback proportional-integral-derivative control not yield to high-performance requirements.In this paper,a nonlinear system model is derived and linear parameterization is made for adaptive control.Then a discontinuous projection-based nonlinear adaptive robust force controller is developed for hydraulic load simulator.The proposed controller constructs an asymptotically stable adaptive controller and adaptation laws,which can compensate for the system nonlinearities and uncertain parameters.Meanwhile a well-designed robust controller is also developed to cope with the hydraulic system uncertain nonlinearities.The controller achieves a guaranteed transient performance and final tracking accuracy in the presence of both parametric uncertainties and uncertain nonlinearities; in the absence of uncertain nonlinearities,the scheme also achieves asymptotic tracking performance.Simulation and experiment comparative results are obtained to verify the high-performance nature of the proposed control strategy and the tracking accuracy is greatly improved.
Lefevre, Brian D.
For the purpose of maintaining dynamic stability and improving guidance command tracking performance under off-nominal flight conditions, a hybrid adaptive control scheme is selected and modified for use as a launch vehicle flight controller. This architecture merges a model reference adaptive approach, which utilizes both direct and indirect adaptive elements, with a classical dynamic inversion controller. This structure is chosen for a number of reasons: the properties of the reference model can be easily adjusted to tune the desired handling qualities of the spacecraft, the indirect adaptive element (which consists of an online parameter identification algorithm) continually refines the estimates of the evolving characteristic parameters utilized in the dynamic inversion, and the direct adaptive element (which consists of a neural network) augments the linear feedback signal to compensate for any nonlinearities in the vehicle dynamics. The combination of these elements enables the control system to retain the nonlinear capabilities of an adaptive network while relying heavily on the linear portion of the feedback signal to dictate the dynamic response under most operating conditions. To begin the analysis, the ascent dynamics of a launch vehicle with a single 1st stage rocket motor (typical of the Ares 1 spacecraft) are characterized. The dynamics are then linearized with assumptions that are appropriate for a launch vehicle, so that the resulting equations may be inverted by the flight controller in order to compute the control signals necessary to generate the desired response from the vehicle. Next, the development of the hybrid adaptive launch vehicle ascent flight control architecture is discussed in detail. Alterations of the generic hybrid adaptive control architecture include the incorporation of a command conversion operation which transforms guidance input from quaternion form (as provided by NASA) to the body-fixed angular rate commands needed by the
De Croon, G.C.H.E.; Postma, E.O.; Van den Herik, H.J.
We propose a novel gaze-control model for detecting objects in images. The model, named act-detect, uses the information from local image samples in order to shift its gaze towards object locations. The model constitutes two main contributions. The first contribution is that the model’s setup makes
El-Nagar, Ahmad M
In this study, an intelligent adaptive controller approach using the interval type-2 fuzzy neural network (IT2FNN) is presented. The proposed controller consists of a lower level proportional - integral (PI) controller, which is the main controller and an upper level IT2FNN which tuning on-line the parameters of a PI controller. The proposed adaptive PI controller based on IT2FNN (API-IT2FNN) is implemented practically using the Arduino DUE kit for controlling the speed of a nonlinear DC motor-generator system. The parameters of the IT2FNN are tuned on-line using back-propagation algorithm. The Lyapunov theorem is used to derive the stability and convergence of the IT2FNN. The obtained experimental results, which are compared with other controllers, demonstrate that the proposed API-IT2FNN is able to improve the system response over a wide range of system uncertainties. PMID:27342993
Full Text Available Purpose: An adaptive control system is built which controlling the cutting force and maintaining constant roughness of the surface being milled by digital adaptation of cutting parameters.Design/methodology/approach: The paper discusses the use of combining the methods of neural networks, fuzzy logic and PSO evolutionary strategy (Particle Swarm Optimization in modeling and adaptively controlling the process of end milling. An overall approach of hybrid modeling of cutting process (ANfis-system, used for working out the CNC milling simulator has been prepared. The basic control design is based on the control scheme (UNKS consisting of two neural identificators of the process dynamics and primary regulator.Findings: The experimental results show that not only does the milling system with the design controller have high robustness, and global stability but also the machining efficiency of the milling system with the adaptive controller is much higher than for traditional CNC milling system. Experiments have confirmed efficiency of the adaptive control system, which is reflected in improved surface quality and decreased tool wear.Research limitations/implications: The proposed architecture for on-line determining of optimal cutting conditions is applied to ball-end milling in this paper, but it is obvious that the system can be extended to other machines to improve cutting efficiency.Practical implications: The results of experiments demonstrate the ability of the proposed system to effectively regulate peak cutting forces for cutting conditions commonly encountered in end milling operations. The high accuracy of results within a wide range of machining parameters indicates that the system can be practically applied in industry.Originality/value: By the hybrid process modeling and feed-forward neural control scheme (UNKS the combined system for off-line optimization and adaptive adjustment of cutting parameters is built.
Rasmussen, Henrik; Larsen, Lars F. S.
are capable of adapting to variety of systems. This paper proposes a novel method for superheat and capacity control of refrigeration systems; namely by controlling the superheat by the compressor speed and capacity by the refrigerant flow. A new low order nonlinear model of the evaporator is developed...... and used in a backstepping design of a nonlinear adaptive controller. The stability of the proposed method is validated theoretically by Lyapunov analysis and experimental results show the performance of the system for a wide range of operating points. The method is compared to a conventional method based...
Yang, Bong-Jun; Calise, Anthony J.; Craig, James I.; Whorton, Mark S.
Neural network-based adaptive control is considered for active control of a highly flexible truss structure which may be used to support solar sail membranes. The objective is to suppress unwanted vibrations in SAFE (Solar Array Flight Experiment) boom, a test-bed located at NASA. Compared to previous tests that restrained truss structures in planar motion, full three dimensional motions are tested. Experimental results illustrate the potential of adaptive control in compensating for nonlinear actuation and modeling error, and in rejecting external disturbances.
Saito, Asaki; Konishi, Keiji
We demonstrate the dynamical characteristics of adaptive delayed-feedback control systems, exploiting a discrete-time adaptive control method derived for carrying out detailed analysis. In particular, the systems exhibit singularities such as power-law decay of the distribution of transient times and almost zero finite-time Lyapunov exponents. We can explain these results by characterizing such systems as having (1) a Jacobian matrix with unity eigenvalue in the whole phase space, and (2) parameters approaching a stability boundary proven to be identical with that of (nonadaptive) delayed-feedback control. PMID:22060398
Full Text Available An adaptive landing gear is a landing gear (LG capable of active adaptation to particular landing conditions by means of controlled hydraulic force. The objective of the adaptive control is to mitigate the peak force transferred to the aircraft structure during touch-down, and thus to limit the structural fatigue factor. This paper investigates the ultimate limits for improvement due to various strategies of active control. Five strategies are proposed and investigated numerically using a~validated model of a real, passive landing gear as a reference. Potential for improvement is estimated statistically in terms of the mean and median (significant peak strut forces as well as in terms of the extended safe sinking velocity range. Three control strategies are verified experimentally using a laboratory test stand.
Alejandro Carrasco Elizalde
Full Text Available The collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration for an adaptive fuzzy controller developed in this paper. Swarm intelligence is used to adjust the parameters of the membership functions used in the adaptive fuzzy controller. The rules of the controller are designed using a computing-with-words approach called Fuzzy-Lyapunov synthesis to improve the stability and robustness of an adaptive fuzzy controller. Computing-with-words provides a powerful tool to manipulate numbers and symbols, like words in a natural language.
Dynamic model and control strategy of parallel mechanism have always been a problem in robotics research. In this paper,different dynamics formulation methods are discussed first, A model of redundant driven parallel mechanism with a planar parallel manipulator is then constructed as an example. A nonlinear adaptive control method is introduced. Matrix pseudo-inversion is used to get a desired actuator torque from a desired end-effector coordinate while the feedback torque is directly calculated in the actuator space. This treatment avoids forward kinematics computation that is very difficult in a parallel mechanism. Experiments with PID together with the descibed adaptive control strategy were carried out for a planar parallel mechanism. The results show that the proposed adaptive controller outperforms conventional PID methods in tracking desired input at a high speed,
Christensen, Anders; Ravn, Ole
SLLAB is a MATLAB-family software package for solving control and identification problems. This paper concerns the planning of a general-purpose subroutine structure for solving identification and adaptive control problems. A general-purpose identification algorithm is suggested, which allows a t...
Yang, Yongheng; Zhou, Keliang; Blaabjerg, Frede
sensitivity of the most popular harmonic controllers for grid-interfaced converters. The frequency adaptability of these harmonic controllers is evaluated in the presence of a variable grid frequency within a specified reasonable range, e.g., +-1% of the nominal grid frequency (50 Hz). Solutions...
Bagchi, Arunabha; Chen, Han-Fu
We study linear-quadratic adaptive tracking problems for a special class of stochastic systems expressed in the state-space form. This is a long-standing problem in the control of aircraft flying through atmospheric turbulence. Using an ELS-based algorithm and introducing dither in the control law w
Battistelli, Giorgio; Hespanha, João; Mosca, Edoardo; Tesi, Pietro
In recent years, unfalsified adaptive switching supervisory control (UASSC) has emerged as an effective technique for tackling the problem of controlling uncertain plants only on the basis of the plant I/O data. The aim of this paper is to construct a novel switching logic, which, when combined with
Niet, de, A.; Vrugt, van de, Noëlle Maria; Korving, Hans; Boucherie, Richard J.; Savic, D.A.; Kapelan, Z.; Butler, D.
In biological wastewater treatment, nitrogen and phosphorous are removed by activated sludge. The process requires oxygen input via aeration of the activated sludge tank. Aeration is responsible for about 60% of the energy consumption of a treatment plant. Hence optimization of aeration can contribute considerably to the increase of energy-efficiency in wastewater treatment. To this end, we introduce an adaptive model based control strategy for aeration called adaptive WOMBAT. The strategy is...
Fransson, Per-Anders; Hafström, Anna; Karlberg, Mikael; Magnusson, Måns; Tjäder, Annika; Johansson, Rolf
he objective for this study was to investigate whether the adaptation of postural control was similar during galvanic vestibular stimulation and during vibratory proprioceptivestimulation of the calf muscles. Healthy subjects were tested during erect stance with eyes open or closed. An analysis method designed to consider the adaptive adjustments was used to evaluate the motion dynamics and the evoked changes of posture and stimulation response.Galvanic vestibular stimulation induced primaril...
Clayton, Dale H.; Moyer, Brett R; Bush, Sarah E.; Jones, Tony G; Gardiner, David W; Rhodes, Barry B; Goller, Franz
The beaks of Darwin's finches and other birds are among the best known examples of adaptive evolution. Beak morphology is usually interpreted in relation to its critical role in feeding. However, the beak also plays an important role in preening, which is the first line of defence against harmful ectoparasites such as feather lice, fleas, bugs, flies, ticks and feather mites. Here, we show a feature of the beak specifically adapted for ectoparasite control. Experimental trimming of the tiny (...
Landau Ioan Doré
The paper will review a number of recent developments for adaptive feedback compensation of multiple unknown and time-varying narrow band disturbances and for adaptive feedforward compensation of broad band disturbances in the presence of the inherent internal positive feedback caused by the coupling between the compensator system and the measurement of the image of the disturbance. Some experimental results obtained on a relevant active vibration control system will illustrate the performance of the various algorithms presented.
Chen Yimei; Han Zhengzhi; Tang Houjun
The problem of adaptive stabilization of a class of multi-input nonlinear systems with unknown parameters both in the state vector-field and the input vector-field has been considered. By employing the control Lyapunov function method, a direct adaptive controller is designed to complete the global adaptive stability of the uncertain system. At the same time, the controller is also verified to possess the optimality. Example and simulations are provided to illustrate the effectiveness of the proposed method.
Baer-Riedhart, Jennifer L.; Landy, Robert J.
The highly integrated digital electronic control (HIDEC) program at NASA Ames Research Center, Dryden Flight Research Facility is a multiphase flight research program to quantify the benefits of promising integrated control systems. McDonnell Aircraft Company is the prime contractor, with United Technologies Pratt and Whitney Aircraft, and Lear Siegler Incorporated as major subcontractors. The NASA F-15A testbed aircraft was modified by the HIDEC program by installing a digital electronic flight control system (DEFCS) and replacing the standard F100 (Arab 3) engines with F100 engine model derivative (EMD) engines equipped with digital electronic engine controls (DEEC), and integrating the DEEC's and DEFCS. The modified aircraft provides the capability for testing many integrated control modes involving the flight controls, engine controls, and inlet controls. This paper focuses on the first two phases of the HIDEC program, which are the digital flight control system/aircraft model identification (DEFCS/AMI) phase and the adaptive engine control system (ADECS) phase.
Xia, Feng; Peng, Chen; Sun, Youxian; Dong, Jinxiang
There is a trend towards using wireless technologies in networked control systems. However, the adverse properties of the radio channels make it difficult to design and implement control systems in wireless environments. To attack the uncertainty in available communication resources in wireless control systems closed over WLAN, a cross-layer adaptive feedback scheduling (CLAFS) scheme is developed, which takes advantage of the co-design of control and wireless communications. By exploiting cross-layer design, CLAFS adjusts the sampling periods of control systems at the application layer based on information about deadline miss ratio and transmission rate from the physical layer. Within the framework of feedback scheduling, the control performance is maximized through controlling the deadline miss ratio. Key design parameters of the feedback scheduler are adapted to dynamic changes in the channel condition. An event-driven invocation mechanism for the feedback scheduler is also developed. Simulation results sh...
National Aeronautics and Space Administration — We report here on first steps towards integrating systems health monitoring with adaptive contingency controls. In the scenario considered, the adaptive controller...
Zhang, Yanjun; Tao, Gang; Chen, Mou
This paper presents a new study on the adaptive neural network-based control of a class of noncanonical nonlinear systems with large parametric uncertainties. Unlike commonly studied canonical form nonlinear systems whose neural network approximation system models have explicit relative degree structures, which can directly be used to derive parameterized controllers for adaptation, noncanonical form nonlinear systems usually do not have explicit relative degrees, and thus their approximation system models are also in noncanonical forms. It is well-known that the adaptive control of noncanonical form nonlinear systems involves the parameterization of system dynamics. As demonstrated in this paper, it is also the case for noncanonical neural network approximation system models. Effective control of such systems is an open research problem, especially in the presence of uncertain parameters. This paper shows that it is necessary to reparameterize such neural network system models for adaptive control design, and that such reparameterization can be realized using a relative degree formulation, a concept yet to be studied for general neural network system models. This paper then derives the parameterized controllers that guarantee closed-loop stability and asymptotic output tracking for noncanonical form neural network system models. An illustrative example is presented with the simulation results to demonstrate the control design procedure, and to verify the effectiveness of such a new design method.
Zhang, Huaguang; Luo, Yanhong; Wang, Ding
There are many methods of stable controller design for nonlinear systems. In seeking to go beyond the minimum requirement of stability, Adaptive Dynamic Programming for Control approaches the challenging topic of optimal control for nonlinear systems using the tools of adaptive dynamic programming (ADP). The range of systems treated is extensive; affine, switched, singularly perturbed and time-delay nonlinear systems are discussed as are the uses of neural networks and techniques of value and policy iteration. The text features three main aspects of ADP in which the methods proposed for stabilization and for tracking and games benefit from the incorporation of optimal control methods: • infinite-horizon control for which the difficulty of solving partial differential Hamilton–Jacobi–Bellman equations directly is overcome, and proof provided that the iterative value function updating sequence converges to the infimum of all the value functions obtained by admissible control law sequences; • finite-...
SONG Yimin; LI Jianxin; WANG Shiyu; LIU Jianping
An investigation on the neural networks based active vibration control of flexible redundant manipulators was conducted.The smart links of the manipulator were synthesized with the flexible links to which were attached piezoceramic actuators and strain gauge sensors.A nonlinear adaptive control strategy named neural networks based indirect adaptive control (NNIAC) was employed to improve the dynamic performance of the manipulator.The mathematical model of the 4-layered dynamic recurrent neural networks (DRNN) was introduced.The neuro-identifier and the neurocontroller featuring the DRNN topology were designed off line so as to enhance the initial robustness of the NNIAC.By adjusting the neuro-identifier and the neuro-controller alternatively,the manipulator was controlled on line for achieving the desired dynamic performance.Finally,a planar 3R redundant manipulator with one smart link was utilized as an illustrative example.The simulation results proved the validity of the control strategy.
Sundararajan, N.; Goglia, G. L.
The use of recursive lattice filters for identification and adaptive control of large space structures is studied. Lattice filters were used to identify the structural dynamics model of the flexible structures. This identification model is then used for adaptive control. Before the identified model and control laws are integrated, the identified model is passed through a series of validation procedures and only when the model passes these validation procedures is control engaged. This type of validation scheme prevents instability when the overall loop is closed. Another important area of research, namely that of robust controller synthesis, was investigated using frequency domain multivariable controller synthesis methods. The method uses the Linear Quadratic Guassian/Loop Transfer Recovery (LQG/LTR) approach to ensure stability against unmodeled higher frequency modes and achieves the desired performance.
Full Text Available An indirect Adaptive fuzzy excitation control (IAFLC of power systems based on multi-input-multi-output linearization technique is developed in this paper. The power system considered in this paper consists of two generators and infinite bus connected through a network of transformers and transmission lines. The fuzzy controller is constructed from fuzzy feedback linearization controller whose parameters are adjusted indirectly from the estimates of plant parameters. The adaptation law adjusts the controller parameters on-line so that the plant output tracks the reference model output. Simulation results shown that the proposed controller IAFLC, compared with a controller based on tradition linearization technique can enhance the transient stability of the power system.
LIU Yusheng; LI Xingyuan
The ideas of adaptive nonlinear damping and changing supply functions were used to counteract the effects of parameter and nonlinear uncertainties,unmodeled dynamics and unknown bounded disturbances.The high-gain observer was used to estimate the state of the system.A robust adaptive output feedback control scheme was proposed for nonlinearly parameterized systems represented by inputoutput models.The scheme does not need to estimate the unknown parameters nor add a dynamical signal to dominate the effects of unmodeled dynamics.It is proven that the proposed control scheme guarantees that all the variables in the closed-loop system are bounded and the mean-square tracking error can be made arbitrarily small by choosing some design parameters appropriately.Simulation results have illustrated the effectiveness of the proposed robust adaptive control scheme.
It is well known that the transient behaviors of the traditional adaptive control may be very poor in general,and that the adaptive control designed based in switching between multiple models is an intuitively appealing and practically feasible approach to improve the transient performances.In this paper,we shall prove that for a typical class of linear systems disturbed by random noises,the multiple model based least-equares(LS)adaptive switching control is statble and convergent and has the same convergence rate as that established for the standard least-squares-based self-tunning regulators.Moreover,the mixed case combining adative models with fixed models is also considered.
Li Chuntao; Tan Yonghong
An adaptive control scheme is developed for a class of single-input nonlinear systems preceded by unknown hysteresis, which is a non-differentiable and multi-value mapping nonlinearity. The controller based on the three-layer neural network (NN), whose weights are derived from Lyapunov stability analysis, guarantees closed-loop semiglobal stability and convergence of the tracking errors to a small residual set. An example is used to confirm the effectiveness of the proposed control scheme.
Torrence D J Welch
Full Text Available Balance control must be rapidly modified to provide stability in the face of environmental challenges. Although changes in reactive balance over repeated perturbations have been observed previously, only anticipatory postural adjustments preceding voluntary movements have been studied in the framework of motor adaptation and learning theory. Here, we hypothesized that adaptation occurs in task-level balance control during responses to perturbations due to central changes in the control of both anticipatory and reactive components of balance. Our adaptation paradigm consisted of a Training set of forward support-surface perturbations, a Reversal set of novel countermanding perturbations that reversed direction, and a Washout set identical to the Training set. Adaptation was characterized by a change in a motor variable from the beginning to the end of each set, the presence of aftereffects at the beginning of the Washout set when the novel perturbations were removed, and a return of the variable at the end of the Washout to a level comparable to the end of the Training set. Task-level balance performance was characterized by peak center of mass (CoM excursion and velocity, which showed adaptive changes with repetitive trials. Only small changes in anticipatory postural control, characterized by body lean and background muscle activity were observed. Adaptation was found in the evoked long-latency muscular response, and also in the sensorimotor transformation mediating that response. Finally, in each set, temporal patterns of muscle activity converged towards an optimum predicted by a trade-off between maximizing motor performance and minimizing muscle activity. Our results suggest that adaptation in balance, as well as other motor tasks, is mediated by altering central sensitivity to perturbations and may be driven by energetic considerations.
Liu, Zhi; Zhang, Yun; Chen, C. L. Philip
In order to assure the communication quality in network systems with heavy traffic and limited bandwidth, a new ATRED (adaptive thresholds random early detection) congestion control algorithm is proposed for the congestion avoidance and resource management of network systems. Different to the traditional AQM (active queue management) algorithms, the control parameters of ATRED are not configured statically, but dynamically adjusted by the adaptive mechanism. By integrating with the adaptive strategy, ATRED alleviates the tuning difficulty of RED (random early detection) and shows a better control on the queue management, and achieve a more robust performance than RED under varying network conditions. Furthermore, a dynamic transmission control protocol-AQM control system using ATRED controller is introduced for the systematic analysis. It is proved that the stability of the network system can be guaranteed when the adaptive mechanism is finely designed. Simulation studies show the proposed ATRED algorithm achieves a good performance in varying network environments, which is superior to the RED and Gentle-RED algorithm, and providing more reliable service under varying network conditions.
Full Text Available Adaptive mixing control (AMC is a recently developed control scheme for uncertain plants, where the control action coming from a bank of precomputed controller is mixed based on the parameter estimates generated by an on-line parameter estimator. Even if the stability of the control scheme, also in the presence of modeling errors and disturbances, has been shown analytically, its transient performance might be sensitive to the initial conditions of the parameter estimator. In particular, for some initial conditions, transient oscillations may not be acceptable in practical applications. In order to account for such a possible phenomenon and to improve the learning capability of the adaptive scheme, in this paper a new mixing architecture is developed, involving the use of parallel parameter estimators, or multi-estimators, each one working on a small subset of the uncertainty set. A supervisory logic, using performance signals based on the past and present estimation error, selects the parameter estimate to determine the mixing of the controllers. The stability and robustness properties of the resulting approach, referred to as multi-estimator adaptive mixing control (Multi-AMC, are analytically established. Besides, extensive simulations demonstrate that the scheme improves the transient performance of the original AMC with a single estimator. The control scheme and the analysis are carried out in a discrete-time framework, for easier implementation of the method in digital control.
LIU Min; XU Shijie; HAN Chao
Although the simple adaptive control (SAC) is widely studied both in theory and application in flexible space structure control and other control problems,it is restricted by the almost strictly positive real (ASPR) conditions.In most practical control problems,the ASPR conditions are not satisfied.Therefore,based on the SAC theory,this paper proposes a backstepping simple adaptive control algorithm which suits the system with arbitrary relative degree with no need of parallel feedforward compensator.The proposed control algorithm consists of decomposition of the arbitrary relative degree system into a known subsystem and an unknown ASPR subsystem which are eonneeted in cascade,design of constant outpul feedback controller for the known subsystem,and implementation of backstepping method and SAC of the unknown ASPR subsystem.Inheriting the characteristics of the SAC,this method can be adaptive online for the parameter uncertainties.Then,the application of the proposed controller to large flexible space structure with collocated sensors and actuators is studied,and the simulation results validate the proposed controller.It is a new strategy to apply the classical SAC to high relative degree plants.
Rasmussen, Henrik; Vadstrup, P.; Børsting, H.
It is well known from the literature that iron loses in an induction motor implies field angle estimation errors and hence detuning problems. In this paper a new method for estimating the iron loss resistor in an induction motor is presented. The method is based on a traditional dynamic model of ...... current controlled in a Field Oriented Control scheme. This deviation is used to force a MIT-rule based adaptive estimator. An adaptive compensator containing the developed estimator is introduced and verified by simulations and tested by real time experiments....
Rasmussen, Henrik; Vadstrup, P.; Børsting, H.
It is well known from the literature that iron loses in an induction motor implies field angle estimation errors and hence detuning problems. In this paper a new method for estimating the iron loss resistor in an induction motor is presented. The method is based on a traditional dynamic model of ...... controlled in a Field Oriented Control scheme. This deviation is used to force a MIT-rule based adaptive estimator. An adaptive compensator containing the developed estimator is introduced and verified by simulations and tested by real time experiments....
This work investigates adaptive control of a large class of uncertain me-delay chaotic systems (UTCSs) with unknown general perturbation terms bounded by a polynomial ( unknown gains). Associated with the different cases of known and unknown system matrices, two corresponding adaptive controllers are proposed to stabilize unstable fixed points of the systems by means of Lyapunov stability theory and linear matrix inequalities (LMI) which can be solved easily by convex optimization algorithms. Two examples are used for examining the effectiveness of the proposed methods.
Hussain, Zakaria; Bin Zaidan, Martha Arbayani; M.O. Tokhi; Jailani, Rozita
This paper describes the development of an adaptive control mechanism for FES-assisted indoor rowing exercise (FES-rowing). The FES-rowing is intro-duced as a total body exercise for rehabilitation of function of lower body through the application of functional elec-trical stimulation (FES). A model of the rowing ergometer with humanoid is developed using the visual Nastran soft-ware environment (vN4D). A fuzzy logic control (FLC) scheme is designed in Matlab/Simulink and adapted online by pr...
Yang Chunhui; Liu Junxian; Chen Honghui; Luo Xueshan
Adaptive optimization is one of the means that agile organization of command and control resource (AOC2R) adapts for the dynamic battlefield environment. A math model of the adaptive optimization of AOC2R is put forward by analyzing the interrelating concept and research. The model takes the adaptive process as a multi-stage decision making problem. The 2-phases method is presented to calculate the model, which obtains the related parameters by running the colored Petri net (CPN) model of AOC2R and then searches for the result by ant colony optimization (ACO) algorithm integrated with genetic optimization techniques. The simulation results demonstrate that the proposed algorithm greatly improves the performance of AOC2R.
Full Text Available This paper presents an integrated missile guidance and control law based on adaptive fuzzy sliding mode control. The integrated model is formulated as a block-strict-feedback nonlinear system, in which modeling errors, unmodeled nonlinearities, target maneuvers, etc. are viewed as unknown uncertainties. The adaptive nonlinear control law is designed based on backstepping and sliding mode control techniques. An adaptive fuzzy system is adopted to approximate the coupling nonlinear functions of the system, and for the uncertainties, we utilize an online-adaptive control law to estimate the unknown parameters. The stability analysis of the closed-loop system is also conducted. Simulation results show that, with the application of the adaptive fuzzy sliding mode control, small miss distances and smooth missile trajectories are achieved, and the system is robust against system uncertainties and external disturbances.
Ran Maopeng; Wang Qing; Hou Delong; Dong Chaoyang
This paper presents an integrated missile guidance and control law based on adaptive fuzzy sliding mode control. The integrated model is formulated as a block-strict-feedback nonlinear system, in which modeling errors, unmodeled nonlinearities, target maneuvers, etc. are viewed as unknown uncertainties. The adaptive nonlinear control law is designed based on backstepping and sliding mode control techniques. An adaptive fuzzy system is adopted to approximate the coupling nonlinear functions of the system, and for the uncertainties, we utilize an online-adaptive control law to estimate the unknown parameters. The stability analysis of the closed-loop system is also conducted. Simulation results show that, with the application of the adaptive fuzzy sliding mode control, small miss distances and smooth missile trajectories are achieved, and the system is robust against system uncertainties and external disturbances.
The variation of joint groove size during tungsten inert gas (TIG) welding will result in the non-uniform fill of deposited metal. To solve this problem, an adaptive fill control system was developed based on laser vision sensing. The system hardware consists of a modular development kit (MDK) as the real-time image capturing system, a computer as the controller, a D/A conversion card as the interface of controlled variable output, and a DC TIG welding system as the controlled device. The system software is developed and the developed feature extraction algorithm and control strategy are of good accuracy and robustness. Experimental results show that the system can implement adaptive fill of melting metal with high stability, reliability and accuracy. The groove is filled well and the quality of the weld formation satisfies the relevant industry criteria.
This paper deals with nonholonomic systems in chained form with unknown covariance stochastic disturbances. The objective is to design the almost global adaptive asymptotical controllers in probability u0 and u1 for the systems by using discontinuous control. A switching control law u0 is designed to almost globally asymptotically stabilize the state x0 in both the singular x0 (t0)=0 case and the non-singular x0 (t0)≠0 case. Then the state scaling technique is introduced for the discontinuous feedback into the (x1, x2, …, xn)-subsystem. Thereby, by using backstepping technique the global adaptive asymptotical control law u1 has been presented for (x1, x2, …, xn) -subsystem for both different u0 in non-singular x0 (t0)≠0 case and the singular case x0 (t0)=0. The control algorithm validity is proved by simulation.
A neuromorphic continuous-time state space pole assignment adaptive controller is proposed, which is particularly appropriate for controlling a large-scale time-variant state-space model due to the parallely distributed nature of neurocomputing. In our approach, Hopfield neural network is exploited to identify the parameters of a continuous-time state-space model, and a dedicated recurrent neural network is designed to compute pole placement feedback control law in real time. Thus the identification and the control computation are incorporated in the closed-loop, adaptive, real-time control system. The merit of this approach is that the neural networks converge to their solutions very quickly and simultaneously.
单剑锋; 黄忠华; 崔占忠
A scheme of adaptive control based on a recurrent neural network with a neural network compensation is presented for a class of nonlinear systems with a nonlinear prefix. The recurrent neural network is used to identify the unknown nonlinear part and compensate the difference between the real output and the identified model output. The identified model of the controlled object consists of a linear model and the neural network. The generalized minimum variance control method is used to identify pareters, which can deal with the problem of adaptive control of systems with unknown nonlinear part, which can not be controlled by traditional methods. Simulation results show that this algorithm has higher precision, faster convergent speed.
Cheng, George Shu-Xing; Mulkey, Steven L.; Wang, Qiang
A novel 3-Input-3-Output (3.times.3) Model-Free Adaptive (MFA) controller with a set of artificial neural networks as part of the controller is introduced. A 3.times.3 MFA control system using the inventive 3.times.3 MFA controller is described to control key process variables including Power, Steam Throttle Pressure, and Steam Temperature of boiler-turbine-generator (BTG) units in conventional and advanced power plants. Those advanced power plants may comprise Once-Through Supercritical (OTSC) Boilers, Circulating Fluidized-Bed (CFB) Boilers, and Once-Through Supercritical Circulating Fluidized-Bed (OTSC CFB) Boilers.
Full Text Available The spatial path following control problem of autonomous underwater vehicles (AUVs is addressed in this paper. In order to realize AUVs’ spatial path following control under systemic variations and ocean current, three adaptive neural network controllers which are based on the Lyapunov stability theorem are introduced to estimate uncertain parameters of the vehicle’s model and unknown current disturbances. These controllers are designed to guarantee that all the error states in the path following system are asymptotically stable. Simulation results demonstrated that the proposed controller was effective in reducing the path following error and was robust against the disturbances caused by vehicle's uncertainty and ocean currents.
Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor); Barlow, Ray; Sessions, Heather; Silulwane, Nonkqubela; Engel, Hermann; Aiken, James; Fishwick, James; Martinez-Vicente, Victor; Morel, Andre
This report documents the scientific activities on board the South African Fisheries Research Ship (FRS) Africana during an ocean color calibration and validation cruise in the Benguela upwelling ecosystem (BEN-CAL), 4-17 October 2002. The cruise, denoted Afncana voyage 170, was staged in the southern Benguela between Cape Town and the Orange River within the region 14-18.5 deg E,29-34 deg S, with 15 scientists participat- ing from seven different international organizations. Uniquely in October 2002, four high-precision ocean color sensors were operational, and these included the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Aqua and Terra spacecraft, the Medium Resolution Imaging Spectrometer (MERIS), and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS). SeaWiFS imagery was transmitted daily to the ship to assist in choosing the vessel's course and selecting stations for bio-optical deployments. There were four primary objectives of the cruise. The first was to conduct bio-optical measurements with above- and in-water optical instruments to vicariously calibrate the satellite sensors. The second was to interrelate diverse measurements of the apparent optical properties (AOPs) at satellite sensor wavelengths with inherent optical properties (IOPs) and bio-optically active constituents of seawater such as particles, pigments, and dissolved compounds. The third was to determine the interrelationships between optical properties, phytoplankton pigment composition, photosynthetic rates, and primary production, while the fourth objective was to collect samples for a second pigment round-robin intercalibration experiment. Weather conditions were generally very favorable, and a range of hyperspectral and fixed wavelength AOP instruments were deployed during daylight hours. Various IOP instruments were used to determine the absorption, attenuation, scattering, and backscattering properties of particulate matter and dissolved substances, while
Shoureshi, Rahmat; Brackney, Larry
During phase 2 research on the application of active noise control to jet engines, the development of multiple-input/multiple-output (MIMO) active adaptive noise control algorithms and acoustic/controls models for turbofan engines were considered. Specific goals for this research phase included: (1) implementation of a MIMO adaptive minimum variance active noise controller; and (2) turbofan engine model development. A minimum variance control law for adaptive active noise control has been developed, simulated, and implemented for single-input/single-output (SISO) systems. Since acoustic systems tend to be distributed, multiple sensors, and actuators are more appropriate. As such, the SISO minimum variance controller was extended to the MIMO case. Simulation and experimental results are presented. A state-space model of a simplified gas turbine engine is developed using the bond graph technique. The model retains important system behavior, yet is of low enough order to be useful for controller design. Expansion of the model to include multiple stages and spools is also discussed.
Shin, Jongho; Jin Kim, H; Kim, Youdan
This paper explores an application of support vector regression for adaptive control of an unmanned aerial vehicle (UAV). Unlike neural networks, support vector regression (SVR) generates global solutions, because SVR basically solves quadratic programming (QP) problems. With this advantage, the input-output feedback-linearized inverse dynamic model and the compensation term for the inversion error are identified off-line, which we call I-SVR (inversion SVR) and C-SVR (compensation SVR), respectively. In order to compensate for the inversion error and the unexpected uncertainty, an online adaptation algorithm for the C-SVR is proposed. Then, the stability of the overall error dynamics is analyzed by the uniformly ultimately bounded property in the nonlinear system theory. In order to validate the effectiveness of the proposed adaptive controller, numerical simulations are performed on the UAV model.
Recently, suboptimality estimates for model predictive controllers (MPC) have been derived for the case without additional stabilizing endpoint constraints or a Lyapunov function type endpoint weight. The proposed methods yield a posteriori and a priori estimates of the degree of suboptimality with respect to the infinite horizon optimal control and can be evaluated at runtime of the MPC algorithm. Our aim is to design automatic adaptation strategies of the optimization horizon in order to guarantee stability and a predefined degree of suboptimality for the closed loop solution. Here, we present a stability proof for an arbitrary adaptation scheme and state a simple shortening and prolongation strategy which can be used for adapting the optimization horizon.
Ren, Haipeng; Fan, Juntao
With the price decreasing of the pneumatic proportional valve and the high performance micro controller, the simple structure and high tracking performance pneumatic servo system demonstrates more application potential in many fields. However, most existing control methods with high tracking performance need to know the model information and to use pressure sensor. This limits the application of the pneumatic servo system. An adaptive backstepping slide mode control method is proposed for pneumatic position servo system. The proposed method designs adaptive slide mode controller using backstepping design technique. The controller parameter adaptive law is derived from Lyapunov analysis to guarantee the stability of the system. A theorem is testified to show that the state of closed-loop system is uniformly bounded, and the closed-loop system is stable. The advantages of the proposed method include that system dynamic model parameters are not required for the controller design, uncertain parameters bounds are not need, and the bulk and expensive pressure sensor is not needed as well. Experimental results show that the designed controller can achieve better tracking performance, as compared with some existing methods.
Milani, Reza Hamidi; Zarabadipour, Hassan; Shahnazi, Reza
For engineering systems, uncertainties and time delays are two important issues that must be considered in control design. Uncertainties are often encountered in various dynamical systems due to modeling errors, measurement noises, linearization and approximations. Time delays have always been among the most difficult problems encountered in process control. In practical applications of feedback control, time delay arises frequently and can severely degrade closed-loop system performance and in some cases, drives the system to instability. Therefore, stability analysis and controller synthesis for uncertain nonlinear time-delay systems are important both in theory and in practice and many analytical techniques have been developed using delay-dependent Lyapunov function. In the past decade the magnetic and levitation (maglev) transportation system as a new system with high functionality has been the focus of numerous studies. However, maglev transportation systems are highly nonlinear and thus designing controller for those are challenging. The main topic of this paper is to design an adaptive robust controller for maglev transportation systems with time-delay, parametric uncertainties and external disturbances. In this paper, an adaptive robust control (ARC) is designed for this purpose. It should be noted that the adaptive gain is derived from Lyapunov-Krasovskii synthesis method, therefore asymptotic stability is guaranteed.
Willigenburg, van L.G.; Vollebregt, H.M.; Sman, van der R.G.M.
An adaptive optimal scheduling and controller design is presented that attempts to improve the performance of beer membrane filtration over the ones currently obtained by operators. The research was performed as part of a large European research project called EU Cafe with the aim to investigate the
Maas, H.L.M.M.; Meiler, P.P.
This paper describes a concept to manage the information exchange between the operators and their consoles (the interface to the computer system) within a Command and Control (C2) centre. Application of his concept will result in a more effective and efficient information exchange, using adaptive in
慕小武; 虞继敏; 毕卫萍; 程代展
Robust adaptive control of nonholonomic systems in chained form with linearly parameterized and strongly nonlinear disturbance and drift terms is dicussed.The novelty of the proposed method is a combined use of the state-scaling and the back-stepping procedure.
Simonov, A.N.; Vdovine, G.V.; Loktev, M.
We present a prototype of an adaptive intraocular lens based on a modal liquid-crystal spatial phase modulator with wireless control. The modal corrector consists of a nematic liquid-crystal layer sandwiched between two glass substrates with transparent low- and high-ohmic electrodes, respectively.
Full Text Available An adaptive control technology and PI-fuzzy compound control technology are proposed to control an active power filter (APF. AC side current compensation and DC capacitor voltage tracking control strategy are discussed and analyzed. Model reference adaptive controller for the AC side current compensation is derived and established based on Lyapunov stability theory; proportional and integral (PI fuzzy compound controller is designed for the DC side capacitor voltage control. The adaptive current controller based on PI-fuzzy compound system is compared with the conventional PI controller for active power filter. Simulation results demonstrate the feasibility and satisfactory performance of the proposed control strategies. It is shown that the proposed control method has an excellent dynamic performance such as small current tracking error, reduced total harmonic distortion (THD, and strong robustness in the presence of parameters variation and nonlinear load.
Folly, R.; Berlim, R.; Salgado, A.; Franca, R.; Valdman, B. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Escola de Quimica
A fed-batch alcohol fermentation on a pilot plant scale with a digital supervisory control was evaluated as an experimental application case study of an adaptive controller. The verification of intrinsically dynamic variations in the characteristics of the fermentation, observed in previous work, showed the necessity of an adaptive control strategy for controller parameter tuning in order to adjust the changes in the specific rates of consumption, growth and product formation during the process. Satisfactory experimental results were obtained for set-point variations and sugar feed concentration load changes in the manipulated inlet flow to the fermenter. (author) 5 refs., 10 figs., 2 tabs.; e-mail: Valdman at H2O.EQ.UFRJ.BR
Shi-Wei Wang; Ding-Li Yu
This paper presents an application of adaptive neural network model-based predictive control (MPC) to the air-fuel ratio of an engine simulation. A multi-layer perceptron (MLP) neural network is trained using two on-line training algorithms: a back propagation algorithm and a recursive least squares (RLS) algorithm. It is used to model parameter uncertainties in the nonlinear dynamics of internal combustion (IC) engines. Based on the adaptive model, an MPC strategy for controlling air-fuel ratio is realized, and its control performance compared with that of a traditional PI controller.A reduced Hessian method, a newly developed sequential quadratic programming (SQP) method for solving nonlinear programming (NLP) problems, is implemented to speed up nonlinear optimization in the MPC.
Bugeja, Marvin K; Fabri, Simon G; Camilleri, Liberato
This paper proposes two novel dual adaptive neural control schemes for the dynamic control of nonholonomic mobile robots. The two schemes are developed in discrete time, and the robot's nonlinear dynamic functions are assumed to be unknown. Gaussian radial basis function and sigmoidal multilayer perceptron neural networks are used for function approximation. In each scheme, the unknown network parameters are estimated stochastically in real time, and no preliminary offline neural network training is used. In contrast to other adaptive techniques hitherto proposed in the literature on mobile robots, the dual control laws presented in this paper do not rely on the heuristic certainty equivalence property but account for the uncertainty in the estimates. This results in a major improvement in tracking performance, despite the plant uncertainty and unmodeled dynamics. Monte Carlo simulation and statistical hypothesis testing are used to illustrate the effectiveness of the two proposed stochastic controllers as applied to the trajectory-tracking problem of a differentially driven wheeled mobile robot.
Valencia, J.; Ercilla, G.; Hernández-Molina, F. J.; Casas, D.
The MOWER Cruise has executed a geophysics and geologic expedition in the Gulf of Cádiz (sector adjacent to the Strait of Gibraltar) and west off Portugal, in the framework of the coordinate research project MOWER "Erosive features and associated sandy deposits generated by the Mediterranean Outflow Water (MOW) around Iberia: paleoceanographic, sedimentary & economic implications" (CTM 2012-39599-C03). The main aim of this project is to identify and study the erosional features (terraces and channels) and associated sedimentary deposits (sandy contourites) generated by the Mediterranean Water Masses around the middle continental slope of Iberia (The Mediterranean Outflow Water - MOW - in the Atlantic margins), their Pliocene and Quaternary evolution and their paleoceanographic, sedimentary and economic implications. This objective directly involves the study of alongslope (contourite) processes associated with the MOW and across-slope (turbiditic flows, debris flows, etc.) processes in the sedimentary stacking pattern and evolution of the Iberian margins. The MOWER project and cruise are related to the Integrated Ocean Drilling Program (IODP) Expedition 339 (Mediterranean Outflow). It is also linked and coordinated with CONDRIBER Project "Contourite drifts and associated mass-transport deposits along the SW Iberia margin - implications to slope stability and tsunami hazard assessment" (2013-2015) funded by the Fundação para a Ciência e Tecnologia, Portugal (PTDC/GEO-GEO/4430/2012).
Full Text Available This paper deals with the control problem of the chaotic system subject to disturbance. The sliding mode surface is designed by singular system approach, and sufficient condition for convergence is given. Then, the adaptive sliding mode controller is designed to make the state arrive at the sliding mode surface in finite time. Finally, Lorenz system is considered as an example to show the effectiveness of the proposed method.
The key conclusions of this research are: 1. The EFXLMS algorithm demonstrated superior performance than the FXLMS algorithm during fast adaptive processes, in particular for non-stationary inputs. 2. Good attenuation of the peak. and root-mean-square (rms) values of the structural responses using the hybrid control system were observed for most of the real accelerograms. It was also observed that the hybrid control system always improved the performance of the passive contr...
Jiang, Yu; Jiang, Zhong-Ping
This paper studies the robust optimal control design for uncertain nonlinear systems from a perspective of robust adaptive dynamic programming (robust-ADP). The objective is to fill up a gap in the past literature of ADP where dynamic uncertainties or unmodeled dynamics are not addressed. A key strategy is to integrate tools from modern nonlinear control theory, such as the robust redesign and the backstepping techniques as well as the nonlinear small-gain theorem, with the theory of ADP. The...
Javaid, N.; Ahmad, A.; A. Rahim; Z.A. Khan; M. Ishfaq; Qasim, U.
Wireless Body Area Networks (WBANs) are widely used for applications such as modern health-care systems, where wireless sensors (nodes) monitor the parameter(s) of interest. Nodes are provided with limited battery power and battery power is dependent on radio activity. MAC protocols play a key role in controlling the radio activity. Therefore, we present Adaptive Medium Access Control (A-MAC) protocol for WBANs supported by linear programming models for the minimization of energy consumption ...
Pezzulo, G; Rigoli, F.; Friston, K.
We review a theory of homeostatic regulation and adaptive behavioural control within the Active Inference framework. Our aim is to connect two research streams that are usually considered independently; namely, Active Inference and associative learning theories of animal behaviour. The former uses a probabilistic (Bayesian) formulation of perception and action, while the latter calls on multiple (Pavlovian, habitual, goal-directed) processes for homeostatic and behavioural control. We offer a...
Pornsin-Sirirak, T. N.; Tai, Y. C.; Nassef, H.; Ho, C M
This paper describes the first flexible parylene electrostatic actuator valves intended for micro adaptive flow control for the future use on the wings of micro-air-vehicle (MAV). The actuator diaphragm is made of two layers of parylene membranes with offset vent holes. Without electrostatic actuation, air can move freely from one side of the skin to the other side through the vent holes. With actuation, these vent holes are sealed and the airflow is controlled. The membrane behaves as a comp...
Milan Manojle Šunjevarić; Goran Z. Đukanović; Nataša M. Gospić
In this paper, an overview of the algorithms for access control in mobile wireless networks is presented. A review of adaptive control methods of accepting a call in WCDMA networks is discussed, based on the overview of the algorithms used for this purpose, and their comparison. Appropriate comments and conculsions in comparison with the basic characteristics of these algorithms are given. The OVSF codes are explained as well as how the allocation method influences the capacity and probabilit...
Partial pressure, system vibration and asymmetric system dynamic performance exit in asymmetric cylinder controller by symmetric valve hydraulic system. To solve this problem in the force control system, model reference adaptive controller is designed using equilibrium point stability theory and output error equation polynomial. The reference model is selected in such a way that it meets the system dynamic performance. Hardware configuration of asymmetric cylinder controlled by asymmetric valve hydraulic system is replaced by intelligent control algorithm, thus the cost is lowered and easy to application. Simulation results demonstrate that the proposed adaptive control sheme has good adaptive ability and well solves asymmetric dynamic performance problem. The designed adaptive controller is fairly robust to load disturbance and system parameter variation.
LU Minyue; GU Zhongquan
A decentralized generalized predictive control (GPC) algorithm is developed for strongly coupled multi-input multi-output systems with parallel computation. The algorithm is applied to adaptive control of structural vibration. The key steps in this algorithm are to group the actuators and the sensors and then to pair these groups into subsystems. It is important that the on-line identification and the control law design can be a parallel process for all these subsystems. It avoids the high computation cost in ordinary predictive control,and is of great advantage especially for large-scale systems.
Bartolini, G.; Levant, A.; Pisano, A.; Usai, E.
This paper endows the second-order sliding mode control (2-SMC) approach with additional capabilities of learning and control adaptation. We present a 2-SMC scheme that estimates and compensates for the uncertainties affecting the system dynamics. It also adjusts the discontinuous control effort online, so that it can be reduced to arbitrarily small values. The proposed scheme is particularly useful when the available information regarding the uncertainties is conservative, and the classical `fixed-gain' SMC would inevitably lead to largely oversized discontinuous control effort. Benefits from the viewpoint of chattering reduction are obtained, as confirmed by computer simulations.
朱雅光; 金波; 李伟
Considering the compliance control problem of a hexapod robot under different environments, a control strategy based on the improved adaptive control algorithm is proposed. The model of robot structure and impedance control is established. Then, the indirect adaptive control algorithm is derived. Through the analysis of its parameters, it can be noticed that the algorithm does not meet the requirements of the robot compliance control in a complex environment. Therefore, the fuzzy control algorithm is used to adjust the adaptive control parameters. The satisfied system response can be obtained based on the adjustment in real time according to the error between input and output. Comparative experiments and analysis of traditional adaptive control and the improved adaptive control algorithm are presented. It can be verified that not only desired contact force can be reached quickly in different environments, but also smaller contact impact and sliding avoidance are guaranteed, which means that the control strategy has great significance to enhance the adaptability of the hexapod robot.
Mohamed Said Sayed Ahmed; Ping Zhang; Yun-Jie Wu
A modified adaptive two-phase sliding mode controller for the synchronous motor drive that is highly robust to uncertain-ties and external disturbances is proposed in this paper. The proposed controller uses two-phase sliding mode control (SMC) where the 1st phase mainly controls the system in steady states and disturbed states-it is a smoothing phase. The 2nd phase is used mainly in the case of disturbed states. Also, it is an autotuning phase and uses a simple adaptive algorithm to tune the gain of conventional variable structure control (VSC). The modified controller is useful in position control of a permanent magnet synchronous drive.
Hao, Lina; Sun, Zhiyong; Li, Zhi; Su, Yunquan; Gao, Jianchao
IPMC is a type of electro-active polymer material, also called artificial muscle, which can generate a relatively large deformation under a relatively low input voltage (generally speaking, less than 5 V), and can be implemented in a water environment. Due to these advantages, IPMC can be used in many fields such as biomimetics, service robots, bio-manipulation, etc. Until now, most existing methods for IPMC manipulation are displacement control not directly force control, however, under most conditions, the success rate of manipulations for tiny fragile objects is limited by the contact force, such as using an IPMC gripper to fix cells. Like most EAPs, a creep phenomenon exists in IPMC, of which the generated force will change with time and the creep model will be influenced by the change of the water content or other environmental factors, so a proper force control method is urgently needed. This paper presents a novel adaptive force control method (AIPOF control—adaptive integral periodic output feedback control), based on employing a creep model of which parameters are obtained by using the FRLS on-line identification method. The AIPOF control method can achieve an arbitrary pole configuration as long as the plant is controllable and observable. This paper also designs the POF and IPOF controller to compare their test results. Simulation and experiments of micro-force-tracking tests are carried out, with results confirming that the proposed control method is viable.
Oveisi, Atta; Nestorović, Tamara
In this paper, a new observer-based adaptive fuzzy integral sliding mode controller is proposed based on the Lyapunov stability theorem. The plant is subjected to a square-integrable disturbance and is assumed to have mismatch uncertainties both in state- and input-matrices. Based on the classical sliding mode controller, the equivalent control effort is obtained to satisfy the sufficient requirement of sliding mode controller and then the control law is modified to guarantee the reachability of the system trajectory to the sliding manifold. In order to relax the norm-bounded constrains on the control law and solve the chattering problem of sliding mode controller, a fuzzy logic inference mechanism is combined with the controller. An adaptive law is then introduced to tune the parameters of the fuzzy system on-line. Finally, for evaluating the controller and the robust performance of the closed-loop system, the proposed regulator is implemented on a real-time mechanical vibrating system.
McFarland, Michael Bryan
Research has shown that neural networks can be used to improve upon approximate dynamic inversion for control of uncertain nonlinear systems. In one architecture, the neural network adaptively cancels inversion errors through on-line learning. Such learning is accomplished by a simple weight update rule derived from Lyapunov theory, thus assuring stability of the closed-loop system. In this research, previous results using linear-in-parameters neural networks were reformulated in the context of a more general class of composite nonlinear systems, and the control scheme was shown to possess important similarities and major differences with established methods of adaptive control. The neural-adaptive nonlinear control methodology in question has been used to design an autopilot for an anti-air missile with enhanced agile maneuvering capability, and simulation results indicate that this approach is a feasible one. There are, however, certain difficulties associated with choosing the proper network architecture which make it difficult to achieve the rapid learning required in this application. Accordingly, this technique has been further extended to incorporate the important class of feedforward neural networks with a single hidden layer. These neural networks feature well-known approximation capabilities and provide an effective, although nonlinear, parameterization of the adaptive control problem. Numerical results from a six-degree-of-freedom nonlinear agile anti-air missile simulation demonstrate the effectiveness of the autopilot design based on multilayer networks. Previous work in this area has implicitly assumed precise knowledge of the plant order, and made no allowances for unmodeled dynamics. This thesis describes an approach to the problem of controlling a class of nonlinear systems in the face of both unknown nonlinearities and unmodeled dynamics. The proposed methodology is similar to robust adaptive control techniques derived for control of linear
Bein, Doina; Madan, Bharat B.; Phoha, Shashi; Rajtmajer, Sarah; Rish, Anna
Given a specific scenario for the border control problem, we propose a dynamic data-driven adaptation of the associated sensor network via embedded software agents which make sensor network control, adaptation and collaboration decisions based on the contextual information value of competing data provided by different multi-modal sensors. We further propose the use of influence diagrams to guide data-driven decision making in selecting the appropriate action or course of actions which maximize a given utility function by designing a sensor embedded software agent that uses an influence diagram to make decisions about whether to engage or not engage higher level sensors for accurately detecting human presence in the region. The overarching goal of the sensor system is to increase the probability of target detection and classification and reduce the rate of false alarms. The proposed decision support software agent is validated experimentally on a laboratory testbed for multiple border control scenarios.
Juan C. Tudón-Martínez
Full Text Available Several methods have been proposed to estimate the force of a semiactive damper, particularly of a magnetorheological damper because of its importance in automotive and civil engineering. Usually, all models have been proposed assuming experimental data in nominal operating conditions and some of them are estimated for control purposes. Because dampers are prone to fail, fault estimation is useful to design adaptive vibration controllers to accommodate the malfunction in the suspension system. This paper deals with the diagnosis and estimation of faults in an automotive magnetorheological damper. A robust LPV observer is proposed to estimate the lack of force caused by a damper leakage in a vehicle corner. Once the faulty damper is isolated in the vehicle and the fault is estimated, an Adaptive Vibration Control System is proposed to reduce the fault effect using compensation forces from the remaining healthy dampers. To fulfill the semiactive damper constraints in the fault adaptation, an LPV controller is designed for vehicle comfort and road holding. Simulation results show that the fault observer has good performance with robustness to noise and road disturbances and the proposed AVCS improves the comfort up to 24% with respect to a controlled suspension without fault tolerance features.
Building robots and machines to act within a fuzzy environment is a problem featuring complexity and ambiguity. In order to avoid obstacles, or move away from it, the robot has to perform functions such as obstacle identification, finding the location of the obstacle, its velocity, direction of movement, size, shape, and so on. This paper presents about the design, and implementation of an adaptive fuzzy controller designed for a 3 degree of freedom spherical coordinate robotic manipulator interfaced with a microcontroller and an ultrasonic sensor. Distance between the obstacle and the sensor and its time rate are considered as inputs to the controller and how the manipulator to take diversion from its planned trajectory, in order to avoid collision with the obstacle, is treated as output from the controller. The obstacles are identified as stationary or moving objects and accordingly adaptive self tuning is accomplished with three set of linguistic rules. The prototype of the manipulator has been fabricated and tested for collision avoidance by placing stationary and moving obstacles in its planned trajectory. The performance of the adaptive control algorithm is analyzed in MATLAB by generating 3D fuzzy control surfaces.
Basar, T. [Univ. of Illinois, Urbana, IL (United States)
We present an optimization-based adaptive controller design for nonlinear systems exhibiting parametric as well as functional uncertainty. The approach involves the formulation of an appropriate cost functional that places positive weight on deviations from the achievement of desired objectives (such as tracking of a reference trajectory while the system exhibits good transient performance) and negative weight on the energy of the uncertainty. This cost functional also translates into a disturbance attenuation inequality which quantifies the effect of the presence of uncertainty on the desired objective, which in turn yields an interpretation for the optimizing control as one that optimally attenuates the disturbance, viewed as the collection of unknown parameters and unknown signals entering the system dynamics. In addition to this disturbance attenuation property, the controllers obtained also feature adaptation in the sense that they help with identification of the unknown parameters, even though this has not been set as the primary goal of the design. In spite of this adaptation/identification role, the controllers obtained are not of certainty-equivalent type, which means that the identification and the control phases of the design are not decoupled.
REN Liyong; LU Xianliang; WEI Qingsong; ZHOU Xu
To solve the problem that most of existing layered multicast protocols cannot adapt to dynamic network conditions because their layers are coarsely granulated and static, a new congestion control mechanism for dynamic adaptive layered multicast(DALM) is presented. In this mechanism, a novel feedback aggregating algorithm is put forward, which can dynamically determine the number of layers and the rate of each layer, and can efficiently improve network bandwidth utilization ratio.Additionally, because all layers is transmitted in only one group, the intricate and time-consuming internet group management protocol(IGMP) operations, caused by receiver joining a new layer or leaving the topmost subscribed layer, are thoroughly eliminated. And this mechanism also avoids other problems resulted from multiple groups. Simulation results show that DALM is adaptive and TCP friendly.
Khizhnyak, Anatoliy; Markov, Vladimir
Effective performance of forthcoming laser systems capable of power delivery on a distant target requires an adaptive optics system to correct atmospheric perturbations on the laser beam. The turbulence-induced effects are responsible for beam wobbling, wandering, and intensity scintillation, resulting in degradation of the beam quality and power density on the target. Adaptive optics methods are used to compensate for these negative effects. In its turn, operation of the AOS system requires a reference wave that can be generated by the beacon on the target. This report discusses a beaconless approach for wavefront correction with its performance based on the detection of the target-scattered light. Postprocessing of the beacon-generated light field enables retrieval and detailed characterization of the turbulence-perturbed wavefront -data that is essential to control the adaptive optics module of a high-power laser system.
Full Text Available An adaptive gain sliding observer for uncertain parameter nonlinear systems together with an adaptive gain sliding controller is proposed in this paper. It considered nonlinear, SISO affine systems, with uncertainties in steady-state functions and parameters. A further parameter term, adaptively updated, has been introduced in steady state space model of the controlled system, in order to obtain useful information despite fault detection and isolation. By using of the sliding observer with adaptive gain, the robustness to uncertainties is increased and the parameters adaptively updated can provide useful information in fault detection. Also, the state estimation error is bounded accordingly with bound limits of the uncertainties. The both of them, the sliding adaptive observer and sliding controller are designed to fulfill the attractiveness condition of its corresponding switching surface. An application to a single arm with flexible joint robot is presented. In order to alleviate chattering, a parameterized tangent hyperbolic has been used as switching function, instead of pure relay one, to the observer and the controller. Also, the gains of the switching functions, to the sliding observer and sliding controller are adaptively updated depending of estimation error and tracking error, respectively. By the using adaptive gains, the transient and tracking response can be improved.
Wang, Zhen; Wu, Zhong; Du, Yijiang
During the reentry process of reusable launch vehicles (RLVs), the large range of flight envelope will not only result in high nonlinearities, strong coupling and fast time-varying characteristics of the attitude dynamics, but also result in great uncertainties in the atmospheric density, aerodynamic coefficients and environmental disturbances, etc. In order to attenuate the effects of these problems on the control performance of the reentry process, a robust adaptive backstepping control (RABC) strategy is proposed for RLV in this paper. This strategy consists of two-loop controllers designed via backstepping method. Both the outer and the inner loop adopt a robust adaptive controller, which can deal with the disturbances and uncertainties by the variable-structure term with the estimation of their bounds. The outer loop can track the desired attitude by the design of virtual control-the desired angular velocity, while the inner one can track the desired angular velocity by the design of control torque. Theoretical analysis indicates that the closed-loop system under the proposed control strategy is globally asymptotically stable. Even if the boundaries of the disturbances and uncertainties are unknown, the attitude can track the desired value accurately. Simulation results of a certain RLV demonstrate the effectiveness of the control strategy.
Full Text Available There is a trend towards using wireless technologies in networked control systems. However, the adverse properties of the radio channels make it difficult to design and implement control systems in wireless environments. To attack the uncertainty in available communication resources in wireless control systems closed over WLAN, a cross-layer adaptive feedback scheduling (CLAFS scheme is developed, which takes advantage of the co-design of control and wireless communications. By exploiting crosslayer design, CLAFS adjusts the sampling periods of control systems at the application layer based on information about deadline miss ratio and transmission rate from the physical layer. Within the framework of feedback scheduling, the control performance is maximized through controlling the deadline miss ratio. Key design parameters of the feedback scheduler are adapted to dynamic changes in the channel condition. An eventdriven invocation mechanism for the feedback scheduler is also developed. Simulation results show that the proposed approach is efficient in dealing with channel capacity variations and noise interference, thus providing an enabling technology for control over WLAN.
Poyneer, L A; Veran, J
We have recently proposed Predictive Fourier Control, a computationally efficient and adaptive algorithm for predictive wavefront control that assumes frozen flow turbulence. We summarize refinements to the state-space model that allow operation with arbitrary computational delays and reduce the computational cost of solving for new control. We present initial atmospheric characterization using observations with Gemini North's Altair AO system. These observations, taken over 1 year, indicate that frozen flow is exists, contains substantial power, and is strongly detected 94% of the time.
Full Text Available To maintain balance during locomotion, the central nervous system (CNS accommodates changes in the constraints of spatial environment (e.g., existence of an obstacle or changes in the surface properties. Locomotion while modifying the basic movement patterns in response to such constraints is referred to as adaptive locomotion. The most powerful means of ensuring balance during adaptive locomotion is to visually perceive the environmental properties at a distance and modify the movement patterns in an anticipatory manner to avoid perturbation altogether. For this reason, visuomotor control of adaptive locomotion is characterized, at least in part, by its anticipatory nature. The purpose of the present article is to review the relevant studies which revealed the anticipatory nature of the visuomotor control of adaptive locomotion. The anticipatory locomotor adjustments for stationary and changeable environment, as well as the spatio-temporal patterns of gaze behavior to support the anticipatory locomotor adjustments are described. Such description will clearly show that anticipatory locomotor adjustments are initiated when an object of interest (e.g., a goal or obstacle still exists in far space. This review also show that, as a prerequisite of anticipatory locomotor adjustments, environmental properties are accurately perceived from a distance in relation to individual’s action capabilities.
Engel, E.; Kovalev, I. V.; Karandeev, D.
The ongoing evolution of the power system towards a Smart Grid implies an important role of intelligent technologies, but poses strict requirements on their control schemes to preserve stability and controllability. This paper presents the adaptive neuro-controller for the vector control of induction motor within Smart Gird. The validity and effectiveness of the proposed energy-saving technology of vector controlled induction motor based on adaptive neuro-controller are verified by simulation results at different operating conditions over a wide speed range of induction motor.
Lan, Lan; Jiang, Shuidong; Zhou, Yang; Fang, Houfei; Tan, Shujun; Wu, Zhigang
Maintaining geometrical high precision for a graphite fiber reinforced composite (GFRC) reflector is a challenging task. Although great efforts have been placed to improve the fabrication precision, geometry adaptive control for a reflector is becoming more and more necessary. This paper studied geometry adaptive control for a GFRC reflector with piezoelectric ceramic transducer (PZT) actuators assembled on the ribs. In order to model the piezoelectric effect in finite element analysis (FEA), a thermal analogy was used in which the temperature was applied to simulate the actuation voltage, and the piezoelectric constant was mimicked by a Coefficient of Thermal Expansion (CTE). PZT actuator's equivalent model was validated by an experiment. The deformations of a triangular GFRC specimen with three PZT actuators were also measured experimentally and compared with that of simulation. This study developed a multidisciplinary analytical model, which includes the composite structure, thermal, thermal deformation and control system, to perform an optimization analysis and design for the adaptive GFRC reflector by considering the free vibration, gravity deformation and geometry controllability.
WANG Xue-song; CHENG Yu-hu; SUN Wei
Aimed at the lack of self-tuning PID parameters in conventional PID controllers, the structure and learning algorithm of an adaptive PID controller based on reinforcement learning were proposed. Actor-Critic learning was used to tune PID parameters in an adaptive way by taking advantage of the model-free and on-line learning properties of reinforcement learning effectively. In order to reduce the demand of storage space and to improve the learning efficiency,a single RBF neural network was used to approximate the policy function of Actor and the value function of Critic simultaneously. The inputs of RBF network are the system error, as well as the first and the second-order differences of error. The Actor can realize the mapping from the system state to PID parameters, while the Critic evaluates the outputs of the Actor and produces TD error. Based on TD error performance index and gradient descent method, the updating rules of RBF kernel function and network weights were given. Simulation results show that the proposed controller is efficient for complex nonlinear systems and it is perfectly adaptable and strongly robust, which is better than that of a conventional PID controller.
Yugang NIU; Xingyu WANG; Junwei LU
A dissipative-based adaptive neural control scheme was developed for a class of nonlinear uncertain systems with unknown nonlinearities that might not be linearly parameterized. The major advantage of the present work was to relax the requirement of matching condition, I.e., the unknown nonlinearities appear on the same equation as the control input in a state-space representation, which was required in most of the available neural network controllers. By synthesizing a state-feedback neural controller to nake the closed-loop system dissipative with respect to a quadratic supply rate, the developed control scheme guarantees that the L2-gain of controlled system was less than or equal to a prescribed level. And then, it is shown that the output tracking error is uniformly ultimate bounded. The design scheme is illustrated using a numerical simulation.
Buescher, Kevin L.; Baum, Christopher C.; Jones, Roger D.
A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data.
di Bernardo, M.; di Gennaro, F.; Olm, J. M.; Santini, S.
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.
Full Text Available Nonlinear characteristics of wind turbines and electric generators necessitate complicated and nonlinear control of grid connected Wind Energy Conversion Systems (WECS. This paper proposes a modified self-tuning PID control strategy, using reinforcement learning for WECS control. The controller employs Actor-Critic learning in order to tune PID parameters adaptively. These Actor-Critic learning is a special kind of reinforcement learning that uses a single wavelet neural network to approximate the policy function of the Actor and the value function of the Critic simultaneously. These controllers are used to control a typical WECS in noiseless and noisy condition and results are compared with an adaptive Radial Basis Function (RBF PID control based on reinforcement learning and conventional PID control. Practical emulated results prove the capability and the robustness of the suggested controller versus the other PID controllers to control of the WECS. The ability of presented controller is tested by experimental setup.
DNA damage triggers surveillance mechanisms, the DNA checkpoints, that control the genome integrity. The DNA checkpoints induce several responses, either cellular or transcriptional, that favor DNA repair. In particular, activation of the DNA checkpoints inhibits cell cycle progression in all phases, depending on the stage when lesions occur. These arrests are generally transient and cells ultimately reenter the cell division cycle whether lesions have been repaired (this process is termed 'recovery') or have proved un-repairable (this option is called 'adaptation'). The mechanisms controlling cell cycle arrests, recovery and adaptation are largely conserved among eukaryotes, and much information is now available for the yeast Saccharomyces cerevisiae, that is used as a model organism in these studies. (author)
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Olaf Mühling; Ralf Ruhmann; Arno Seeboth
The aim of this review is to present the actual status of development in adaptive solar control by use of thermotropic and organic thermochromic materials. Such materials are suitable for application in smart windows. In detail polymer blends, hydrogels, resins, and thermoplastic films with a reversible temperature-dependent switching behavior are described. A comparative evaluation of the concepts for these energy efficient materials is given as well. Furthermore, the change of strategy from...
Full Text Available A direct model reference adaptive controller (MRAC is derived for an underwater vehicle with significant thruster dynamics and limited thruster power. The reference model decomposition (RMD technique is used to compensate for the thruster dynamics. A reference model adjustment (RMA technique modifying the reference model acceleration is used to avoid thruster saturation. The design methods are simulated for the yawing motion of an underwater vehicle.
Thor I. Fossen
Full Text Available Robust adaptive control of underwater vehicles in 6 DOF is analysed in the context of measurement noise. The performance of the adaptive control laws of Sadegh and Harowitz (1990 and Slotine and Benedetto (1990 are compared. Both these schemes require that all states are measured, that is the velocities and positions in surge, sway, heave, roll, pitch and yaw. However, for underwater vehicles it is difficult to measure the linear velocities whereas angular velocity measurements can be obtained by using a 3 axes angular rate sensor. This problem is addressed by designing a nonlinear observer for linear velocity state estimation. The proposed observer requires that the position and the attitude are measured, e.g. by using a hydroacoustic positioning system for linear positions, two gyros for roll and pitch and a compass for yaw. In addition angular rate measurements will be assumed available from a 3-axes rate sensor or a state estimator. It is also assumed that the measurement rate is limited to 2 Hz for all the sensors. Simulation studies with a 3 DOF AUV model are used to demonstrate the convergence and robustness of the adaptive control laws and the velocity state observer.
Li, Shuhui; Wang, Jian
We report feedback-assisted adaptive multicasting from a single Gaussian mode to multiple orbital angular momentum (OAM) modes using a single phase-only spatial light modulator loaded with a complex phase pattern. By designing and optimizing the complex phase pattern through the adaptive correction of feedback coefficients, the power of each multicast OAM channel can be arbitrarily controlled. We experimentally demonstrate power-controllable multicasting from a single Gaussian mode to two and six OAM modes with different target power distributions. Equalized power multicasting, “up-down” power multicasting and “ladder” power multicasting are realized in the experiment. The difference between measured power distributions and target power distributions is assessed to be less than 1 dB. Moreover, we demonstrate data-carrying OAM multicasting by employing orthogonal frequency-division multiplexing 64-ary quadrature amplitude modulation (OFDM 64-QAM) signal. The measured bit-error rate curves and observed optical signal-to-noise ratio penalties show favorable operation performance of the proposed adaptive power-controllable OAM multicasting. PMID:25989251
Trong-Toan TRAN; Shuzhi Sam GE; Wei HE
In this paper, we address the control problem of an uncertain robotic manipulator with input saturations, unknown input scalings and disturbances. For this purpose, a model reference adaptive control like (MRAC-like) is used to handle the input saturations. The model reference is input to state stable (ISS) and driven by the errors between the required control signals and input saturations. The uncertain parameters are dealt with by using linear-in-the-parameters property of robotic dynamics, while unknown input scalings and disturbances are handled by non-regressor based approach. Our design ensures that all the signals in the closed-loop system are bounded, and the tracking error converges to the compact set which depends on the predetermined bounds of the control inputs. Simulation on a planar elbow manipulator with two joints is provided to illustrate the effectiveness of the proposed controller.
Full Text Available The problem of reactive power control for mains-side inverter (MSI in doubly fed induction generator (DFIG is studied in this paper. To accommodate the modelling nonlinearities and inherent uncertainties, a novel robust adaptive control algorithm for MSI is proposed by utilizing Lyapunov theory that ensures asymptotic stability of the system under unpredictable external disturbances and significant parametric uncertainties. The distinguishing benefit of the aforementioned scheme consists in its capabilities to maintain satisfactory performance under varying operation conditions without the need for manually redesigning or reprogramming the control gains in contrast to the commonly used PI/PID control. Simulations are also built to confirm the correctness and benefits of the control scheme.
Full Text Available This paper presents a technique for speed sensorless Rotor Flux Oriented Control (RFOC of 3-phase Induction Motor (IM under open-phase fault (unbalanced or faulty IM. The presented RFOC strategy is based on rotational transformation. An adaptive sliding mode control system with an adaptive switching gain is proposed instead of the speed PI controller. Using an adaptive sliding mode control causes the proposed speed sensorless RFOC drive system to become insensitive to uncertainties such as load disturbances and parameter variations. Moreover, with adaptation of the sliding switching gain, calculation of the system uncertainties upper bound is not needed. Finally, simulation results have been presented to confirm the good performance of the proposed method.
National Oceanic and Atmospheric Administration, Department of Commerce — The Post-Cruise Questionnaire is a mandatory post trip legal document that observers fill out after every trip they have completed.
PEI Bingnan; LI Chuanguang
A modified LMS algorithm for noise-control is suggested after a mathematical model ofsound-cancellation is established, on the basis of thesound wave interference principle and the physicalmodel of progressive waves in a duct. Its applicationin controlling noise with the frequency range from 100to 800 Hz can be implemented by using the adaptivedigital signal processing technique. The experimentson a pink noise, a broadband noise and a noise takenfrom a tank were made, which show that there existsan attenuation of 11 dB at the frequency of 500 Hzor so, and that the proposed adaptive noise controltechnique is very effective and valid.
Full Text Available The convergence of model-free adaptive control (MFAC algorithm can be guaranteed when the system is subject to measurement data dropout. The system output convergent speed gets slower as dropout rate increases. This paper proposes a MFAC algorithm with data compensation. The missing data is first estimated using the dynamical linearization method, and then the estimated value is introduced to update control input. The convergence analysis of the proposed MFAC algorithm is given, and the effectiveness is also validated by simulations. It is shown that the proposed algorithm can compensate the effect of the data dropout, and the better output performance can be obtained.
Full Text Available This paper presents a robust adaptive fuzzy sliding mode control method for a class of uncertain nonlinear systems. The fractional order calculus is employed in the parameter updating stage. The underlying stability analysis as well as parameter update law design is carried out by Lyapunov based technique. In the simulation, two examples including a comparison with the traditional integer order counterpart are given to show the effectiveness of the proposed method. The main contribution of this paper consists in the control performance is better for the fractional order updating law than that of traditional integer order.
Kallesøe, Carsten; Jensen, Tom Nørgaard; Wisniewski, Rafal
Water scarcity is an increasing problem worldwide and at the same time a huge amount of water is lost through leakages in the distribution network. It is well known that improved pressure control can lower the leakage problems. In this work water networks with a single pressure actuator and several....... Subsequently, these relations are exploited in an adaptive reference control scheme for the actuator pressure that ensures constant pressure at the critical points. Numerical experiments underpin the results. © Copyright IEEE - All rights reserved....
Ortega, Pedro A
Explaining adaptive behavior is a central problem in artificial intelligence research. Here we formalize adaptive agents as mixture distributions over sequences of inputs and outputs (I/O). Each distribution of the mixture constitutes a 'possible world', but the agent does not know which of the possible worlds it is actually facing. The problem is to adapt the I/O stream in a way that is compatible with the true world. A natural measure of adaptation can be obtained by the Kullback-Leibler (KL) divergence between the I/O distribution of the true world and the I/O distribution expected by the agent that is uncertain about possible worlds. In the case of pure input streams, the Bayesian mixture provides a well-known solution for this problem. We show, however, that in the case of I/O streams this solution breaks down, because outputs are issued by the agent itself and require a different probabilistic syntax as provided by intervention calculus. Based on this calculus, we obtain a Bayesian control rule that all...
The non-stationary property of electromyography (EMG) signals in real life settings usually hinders the clinical application of the myoelectric pattern recognition for prosthesis control. The classical EMG pattern recognition approach consists of two separate steps: training and testing, without considering the changes between training and testing data induced by electrode shift, fatigue, impedance changes and psychological factors, and often results in performance degradation. The aim of this study was to develop an adaptive myoelectric pattern recognition system, aiming to retrain the classifier online with the testing data without supervision, providing a self-correction mechanism for suppressing misclassifications. This paper presents an adaptive unsupervised classifier based on support vector machine (SVM) to improve the classification performance. Experimental data from 15 healthy subjects were used to evaluate performance. Preliminary study on intra-session and inter-session EMG data was conducted to verify the performance of the unsupervised adaptive SVM classifier. The unsupervised adaptive SVM classifier outperformed the conventional SVM by 3.3% and 8.0% for the combination of time-domain and autoregressive features in the intra-session and inter-session tests, respectively. The proposed approach is capable of incorporating the useful information in testing data to the classification model by taking into account the overtime changes in the testing data with respect to the training data to retrain the original classifier, therefore providing a self-correction mechanism for suppressing misclassifications.
Berkhoff, A.P.; Wesselink, J.M.
Model errors in multiple-input multiple-output adaptive controllers for reduction of broadband noise and vibrations may lead to unstable systems or increased error signals. In this paper, a combination of high-authority control (HAC) and low-authority control (LAC) is considered for improved perform
Li, Ning; Cao, Jinde
In this paper, we investigate synchronization for memristor-based neural networks with time-varying delay via an adaptive and feedback controller. Under the framework of Filippov's solution and differential inclusion theory, and by using the adaptive control technique and structuring a novel Lyapunov functional, an adaptive updated law was designed, and two synchronization criteria were derived for memristor-based neural networks with time-varying delay. By removing some of the basic literature assumptions, the derived synchronization criteria were found to be more general than those in existing literature. Finally, two simulation examples are provided to illustrate the effectiveness of the theoretical results. PMID:25299765
Wai, Rong-Jong; Lee, Jeng-Dao
A magnetic-levitation (maglev) transportation system including levitation and propulsion control is a subject of considerable scientific interest because of highly nonlinear and unstable behaviors. In this paper, the dynamic model of a maglev transportation system including levitated electromagnets and a propulsive linear induction motor (LIM) based on the concepts of mechanical geometry and motion dynamics is developed first. Then, a model-based sliding-mode control (SMC) strategy is introduced. In order to alleviate chattering phenomena caused by the inappropriate selection of uncertainty bound, a simple bound estimation algorithm is embedded in the SMC strategy to form an adaptive sliding-mode control (ASMC) scheme. However, this estimation algorithm is always a positive value so that tracking errors introduced by any uncertainty will cause the estimated bound increase even to infinity with time. Therefore, it further designs an adaptive fuzzy-neural-network control (AFNNC) scheme by imitating the SMC strategy for the maglev transportation system. In the model-free AFNNC, online learning algorithms are designed to cope with the problem of chattering phenomena caused by the sign action in SMC design, and to ensure the stability of the controlled system without the requirement of auxiliary compensated controllers despite the existence of uncertainties. The outputs of the AFNNC scheme can be directly supplied to the electromagnets and LIM without complicated control transformations for relaxing strict constrains in conventional model-based control methodologies. The effectiveness of the proposed control schemes for the maglev transportation system is verified by numerical simulations, and the superiority of the AFNNC scheme is indicated in comparison with the SMC and ASMC strategies. PMID:18269938
Sri Latha Eti
Full Text Available Brushless DC Motors are widely used for many industrial applications because of their high efficiency, high torque and low volume. This paper proposed an improved Adaptive Fuzzy PI controller to control the speed of BLDC motor. This paper provides an overview of different tuning methods of PID Controller applied to control the speed of the transfer function model of the BLDC motor drive and then to the mathematical model of the BLDC motor drive. It is difficult to tune the parameters and get satisfied control characteristics by using normal conventional PI controller. The experimental results verify that Adaptive Fuzzy PI controller has better control performance than the conventional PI controller. The modeling, control and simulation of the BLDC motor have been done using the MATLAB/SIMULINK software. Also, the dynamic characteristics of the BLDC motor (i.e. speed and torque as well as currents and voltages of the inverter components are observed by using the developed model.
Zhang, Jianling; An, Jinwen; Wang, Mina
This paper describes the application and simulation of an adaptive fuzzy controller for a missile model. The fuzzy control system is tested using different values of fuzzy controller correctional factor on a nonlinear missile model. It is shown that the self-tuning fuzzy controller is well suited for controlling the pitch loop of the missile control system with air turbulence and parameter variety. The research shows that the Popov stability criterion could successfully guarantee the stability of the fuzzy system. It provides a good method for the design of missile control system. Simulation results suggest significant benefits from fuzzy logic in control task for missile pitch loop control.
Full Text Available This paper presents a technique to control the electric vehicle (EV speed and torque at any curve. Our propulsion model consist of two permanent magnet synchronous (PMSM motors. The fuzzy adaptive PI controller is used to adjust the different static error constants, as per the speed error. The suggested based on the direct torque fuzzy control (DTFC. A Mamdani type fuzzy direct torque controller is first developed and then rules are modified using stator current membership functions. The computations are ensured by the electronic differential, this driving process permit to steer each driving wheels at any curve separately.Modeling and simulation are carried out using the Matlab/Simulink tool to investigate the performance of the proposed system.
Full Text Available EMS-type maglev system is essentially nonlinear and unstable. It is complicated to design a stable controller for maglev system which is under large-scale disturbance and parameter variance. Theory analysis expresses that this phenomenon corresponds to a HOPF bifurcation in mathematical model. An adaptive control law which adjusts the PID control parameters is given in this paper according to HOPF bifurcation theory. Through identification of the levitated mass, the controller adjusts the feedback coefficient to make the system far from the HOPF bifurcation point and maintain the stability of the maglev system. Simulation result indicates that adjusting proportion gain parameter using this method can extend the state stability range of maglev system and avoid the self-excited vibration efficiently.
Khorrami, Farshad; Jain, Sandeep; Das, Nirod K.
Smart structures lend themselves naturally to a decentralized control design framework, especially with adaptation mechanisms. The main reason being that it is highly undesirable to connect all the sensors and actuators in a large structure to a central processor. It is rather desirable to have local decision-making at each smart patch. Furthermore, this local controllers should be easily `expandable' to `contractible.' This corresponds to the fact that addition/deletion of several smart patches should not require a total redesign of the control system. The decentralized control strategies advocated in this paper are of expandable/contractible type. On another front, we are considering utilization of micro-strip antennas for power transfer to and from smart structures. We have made preliminary contributions in this direction and further developments are underway. These approaches are being pursued for active vibration damping and noise cancellation via piezoelectric ceramics although the methodology is general enough to be applicable to other type of active structures.
Berbaoui Brahim; Bousmaha Bouchiba,; Youssef Mouloudi,; Abdellah Laoufi
Based on the feedback linearized technique and control of differential and algebraic systems, the Indirect Adaptive fuzzy excitation control is presented in this paper for SVC (static var compensator) and generator excitation controllers in power systems with nonlinear loads. It can improve both the power angle stability ofgenerators and the voltage behavior at the SVC location. Simulation results shown that the proposed controller IAFLC, compared with a controller based on tradition lineariz...
Wernicke, J.-Th. [Wind Force Engineering and Consulting GmbH, Bremerhaven (Germany)
The technology of Time Division Multiplexing (TDM) is compared with conventional strain gauge technologies in practical operation in a wind power system. Load cycles in the rotor blade were measured during plant life, and the data were used in plant control. The system is a tool in technical project management and financial management of a wind park. (orig.)
Traditionally, cruise companies have stated that they are in the transport business but not in the business of providing medical services to passengers. They have claimed not to be able to supervise or control the ship's medical personnel and cruise ship's doctors have therefore mostly been signed on as independent contractors, not employees. A United States court decision from 1988, Barbetta versus S/S Bermuda Star, supported this view and ruled that a ship's owner cannot be held vicariously liable for the negligence of the ship's doctor directed at the ship's passengers. Some years ago a cruise passenger fell and hit his head while boarding a trolley ashore. Hours later he was seen aboard by the ship's doctor, who sent him to a local hospital. He died 1 week later, and his daughter filed a complaint alleging the cruise company was vicariously liable for the purported negligence of the ship's doctor and nurse, under actual or apparent agency theories. A United States district court initially dismissed the case, but in November 2014 the United States Court of Appeals for the Eleventh Circuit disagreed and reversed. From then on independently contracted ship's doctors may be considered de facto employees of the cruise line. The author discusses the employment status of physicians working on cruise ships and reviews arguments for and against the Appellate Court's decision.
Yıldız, Yıldıray; Yildiz, Yildiray; Ünel, Mustafa; Unel, Mustafa; Demirel, Ahmet Eren
Position control of a quad tilt-wing UAV via a nonlinear hierarchical adaptive control approach is presented. The hierarchy consists of two levels. In the upper level, a model reference adaptive controller creates virtual control commands so as to make the UAV follow a given desired trajectory. The virtual control inputs are then converted to desired attitude angle references which are fed to the lower level attitude controller. Lower level controller is a nonlinear adaptive controller. The o...
Xuan Phu Do
Full Text Available This paper presents a new direct adaptive fuzzy controller and its effectiveness is verified by investigating the damping force tracking control of magnetorheological (MR fluid based damper (MR damper in short system. In the formulation of the proposed controller, a model of interval type 2 fuzzy controller is combined with the direct adaptive control to achieve high performance in vibration control. In addition, H∞ (H infinity tracking technique is used in building a model of the direct adaptive fuzzy controller in which an enhanced iterative algorithm is combined with the fuzzy model. After establishing a closed-loop control structure to achieve high control performance, a cylindrical MR damper is adopted and damping force tracking results are obtained and discussed. In addition, in order to demonstrate the effectiveness of the proposed control strategy, two existing controllers are modified and tested for comparative work. It has been demonstrated from simulation and experiment that the proposed control scheme provides much better control performance in terms of damping force tracking error. This leads to excellent vibration control performance of the semiactive MR damper system associated with the proposed controller.
Nguyen, Nhan T. (Inventor); Burken, John J. (Inventor); Hanson, Curtis E. (Inventor)
Disclosed is a novel adaptive control method and system called optimal control modification with normalization and covariance adjustment. The invention addresses specifically to current challenges with adaptive control in these areas: 1) persistent excitation, 2) complex nonlinear input-output mapping, 3) large inputs and persistent learning, and 4) the lack of stability analysis tools for certification. The invention has been subject to many simulations and flight testing. The results substantiate the effectiveness of the invention and demonstrate the technical feasibility for use in modern aircraft flight control systems.
Scanlon, B. R.; Cook, C.; Fernando, D. N.; LeBlanc, M.
Increasing vulnerability to droughts with reduced per capita water storage, particularly in semiarid regions, underscores the need for predictive understanding of drought controls and development of adaptation strategies for water resources management. In this study we evaluate causes of major droughts in southwest and southcentral US (California and Texas) and southeast Australia (Murray Darling Basin). Impacts of climate cycles (ENSO, PDO, AMO, NAO, IOD) and atmospheric circulation on drought initiation and persistence are examined. Effects of drought on surface water reservoir storage, groundwater storage, irrigation, and crop production are compared. Adaptation strategies being evaluated include water transfers among sectors, particularly from irrigated agriculture to other groups, increasing storage using managed aquifer recharge, water reuse, and development of new water sources (e.g. seawater desalination). It is critical to develop a broad portfolio of water sources to increase resilience to future droughts.
Sun, Hongfei; Yang, Zhiling; Meng, Bin
A new tracking-control method for general non-linear systems is proposed. A virtual controller and some command references are introduced to asymptotically stabilise the system of the tracking error dynamics. Then, the actual controller and command references are derived by solving a system of linear algebraic equations. Compared with other tracking-control methods in the literature, the tracking-controller design in this paper is simple because it needs only to solve a system of linear algebraic equations. The boundedness of the tracking controller and command references is guaranteed by the solvability of the terminal value problem (TVP) of an ordinary differential equation. For non-linear systems with minimum-phase properties, the TVP is automatically solvable. A numerical example shows that the tracking-control method is still available for some systems with non-minimum-phase properties. To enhance the robustness of the tracking controller, a non-linear disturbance observer (NDO) is introduced to estimate the disturbance. The combination of the tracking controller and the NDO is applied to the tracking control of an air-breathing hypersonic vehicle.
Full Text Available In Wireless Sensor Networks (WSN when an event is detected there is an increase in data traffic that mightlead to packets being transmitted through the network close to the packet handling capacity of the WSN.The WSN experiences a decrease in network performance due to packet loss, long delays, and reduction inthroughput. In this paper we developed an adaptive congestion control algorithm that monitors networkutilization and adjust traffic levels and/or increases network resources to improve throughput and conserveenergy. The traffic congestion control protocol DelStatic is developed by introducing backpressuremechanism into NOAH. We analyzed various routing protocols and established that DSR has a higherresource congestion control capability. The proposed protocol, ACCP uses a sink switching algorithm totrigger DelStatic or DSR feedback to a congested node based on its Node Rank. From the simulationresults, ACCP protocol does not only improve throughput but also conserves energy which is critical tosensor application survivability on the field. Our Adaptive Congestion control achieved reliability, highthroughput and energy efficiency.
Full Text Available This paper proposes adaptive Maximum Power Point Tracking (MPPT controller for Permanent Magnet Synchronous Generator (PMSG wind turbine and direct power control for grid side inverter for transformer less integration of wind energy. PMSG wind turbine with two back to back voltage source converters are considered more efficient, used to make real and reactive power control. The optimal control strategy has introduced for integrated control of PMSG Maximum Power Extraction, DC link voltage control and grid voltage support controls. Simulation model using MATLAB Simulink has developed to investigate the performance of proposed control techniques for PMSG wind turbine steady and variable wind conditions. This paper shows that the direct driven grid connected PMSG system has excellent performances and confirms the feasibility of the proposed techniques. While the wind turbine market continues to be dominated by conventional gear-driven wind turbine systems, the direct drive is attracting attention. PM machines are more attractive and superior with higher efficiency and energy yield, higher reliability, and power-to-weight ratio compared with electricity-excited machines.
Suto, T. [Japan Society for the Promotion of Science, Tokyo (Japan); Ura, T. [The University of Tokyo, Tokyo (Japan). Institute of Industrial Science
A small autonomous robot with high software development efficiency was developed to investigate the control system of an autonomous cruising-type AUV in the actual environment. This robot has a minimum of functions required as a cruising type. One researcher can make an experiment on the robot because of its compactness and lightweight. The robot can also automatically cruise around in a small pool. It was confirmed that an adaptive constant altitude swimming controller utilizing a neural network verified by simulation can also be properly adjusted by an actual robot. The switching mechanism of neural networks was introduced to classify environmental patterns. The corresponding controller is adjusted automatically. In this study, a lightweight and compact cruising-type test-bed robot that has not existed until now was developed. This robot is easy to manufacture and construct in software. Therefore, it is to be desired that the researches and development of autonomous functions are promoted using such a robot. 9 refs., 13 figs., 1 tab.
XIAO Bing; HU Qing-lei; MA Guang-fu
In this paper,a neural network adaptive controller is proposed for attitude tracking of flexible spacecraft in presence of unknown inertial matrix and external disturbance.In this approach,neural network technique is employed to approximate the unknown system dynamics with finite combinations of some basis functions,and a robust controller is also designed to attenuate the effect of approximation error,more specially,the knowledge of angular velocity is not required.In the closed-loop system,Lyapunov stability analysis shows that the attitude trajectories asymptotically follow the reference output trajectories.Finally,simulation results are presented for the attitude tracking of a flexible spacecraft to show the excellent performance of the proposed controller and illustrate its robustness in face of external disturbances and unknown dynamics.
This book provides a comprehensive discussion of nonlinear multi-modal structural vibration problems, and shows how vibration suppression can be applied to such systems by considering a sample set of relevant control techniques. It covers the basic principles of nonlinear vibrations that occur in flexible and/or adaptive structures, with an emphasis on engineering analysis and relevant control techniques. Understanding nonlinear vibrations is becoming increasingly important in a range of engineering applications, particularly in the design of flexible structures such as aircraft, satellites, bridges, and sports stadia. There is an increasing trend towards lighter structures, with increased slenderness, often made of new composite materials and requiring some form of deployment and/or active vibration control. There are also applications in the areas of robotics, mechatronics, micro electrical mechanical systems, non-destructive testing and related disciplines such as structural health monitoring. Two broader ...
Herzallah, Randa; Kárný, Miroslav
Optimal stochastic controller pushes the closed-loop behavior as close as possible to the desired one. The fully probabilistic design (FPD) uses probabilistic description of the desired closed loop and minimizes Kullback-Leibler divergence of the closed-loop description to the desired one. Practical exploitation of the fully probabilistic design control theory continues to be hindered by the computational complexities involved in numerically solving the associated stochastic dynamic programming problem; in particular, very hard multivariate integration and an approximate interpolation of the involved multivariate functions. This paper proposes a new fully probabilistic control algorithm that uses the adaptive critic methods to circumvent the need for explicitly evaluating the optimal value function, thereby dramatically reducing computational requirements. This is a main contribution of this paper. PMID:21752597
Burelli, Paolo; Yannakakis, Georgios N.
model of the camera behaviour that can be used to control camera movements based on player preferences. For this purpose, we collect eye gaze, camera and game-play data from subjects playing a 3D platform game, we cluster gaze and camera information to identify camera behaviour profiles and we employ......Automatic camera control aims to define a framework to control virtual camera movements in dynamic and unpredictable virtual environments while ensuring a set of desired visual properties. We inves- tigate the relationship between camera placement and playing behaviour in games and build a user...... machine learning to build predictive models of the virtual camera behaviour. The perfor- mance of the models on unseen data reveals accuracies above 70% for all the player behaviour types identified. The characteristics of the gener- ated models, their limits and their use for creating adaptive automatic...
Full Text Available In this paper, the problem of the position and attitude tracking of an autonomous underwater vehicle (AUV in the horizontal plane, under the presence of ocean current disturbances is discussed. The effect of the gradual variation of the parameters is taken into account. The effectiveness of the adaptive controller is compared with a feedback linearization method and fuzzy gain control approach. The proposed strategy has been tested through simulations. Also, the performance of the propos-ed method is compared with other strategies given in some other studies. The boundedness and asymptotic converge-nce properties of the control algorithm and its semi-global stability are analytically proven using Lyapunov stability theory and Barbalat’s lemma.
YANG Ben-kun; BIAN Xin-qian; GUO Wei-lai
A pressurizer is one of important equipment in a pressurized water reactor plant. It is used to maintain the pressure of primary coolant within allowed range because the sharp change of coolant pressure affects the security of reactor,therefor,the study of pressurizer's pressure control methods is very important. In this paper, an adaptive fuzzy controller is presented for pressure control of a pressurizer in a nuclear power plant. The controller can on-line tune fuzzy control rules and parameters by self-learning in the actual control process, which possesses the way of thinking like human to make a decision. The simulation results for a pressurized water reactor plant show that the adaptive fuzzy controller has optimum and intelligent characteristics, which prove the controller is effective.
Martín-Sánchez, Juan M
This book is a didactic explanation of the developments of predictive, adaptive predictive and optimized adaptive control, including the latest methodology of adaptive predictive expert (ADEX) control, and their practical applications. It is focused on the stability perspective, used in the introduction of these methodologies, and is divided into six parts, with exercises and real-time simulations provided for the reader as appropriate. ADEX Optimized Adaptive Controllers and Systems begins with the conceptual and intuitive knowledge of the technology and derives the stability conditions to be verified by the driver block and the adaptive mechanism of the optimized adaptive controller to guarantee achievement of desired control performance. The second and third parts are centered on the design of the driver block and adaptive mechanism, which verify these stability conditions. The authors then proceed to detail the stability theory that supports predictive, adaptive predictive and optimized adaptive control m...
Mayer, D.; Pfeiffer, T.; Vrbata, J.; Melz, T.
Tuned vibration absorbers have become common for passive vibration reduction in many industrial applications. Lightly damped absorbers (also called neutralizers) can be used to suppress narrowband disturbances by tuning them to the excitation frequency. If the resonance is adapted in-operation, the performance of those devices can be significantly enhanced, or inertial mass can be decreased. However, the integration of actuators, sensors and control electronics into the system raises new design challenges. In this work, the development of adaptive-passive systems for vibration reduction at an industrial scale is presented. As an example, vibration reduction of a ship engine was studied in a full scale test. Simulations were used to study the feasibility and evaluate the system concept at an early stage. Several ways to adjust the resonance of the neutralizer were evaluated, including piezoelectric actuation and common mechatronic drives. Prototypes were implemented and tested. Since vibration absorbers suffer from high dynamic loads, reliability tests were used to assess the long-term behavior under operational conditions and to improve the components. It was proved that the adaptive systems are capable to withstand the mechanical loads in an industrial application. Also a control strategy had to be implemented in order to track the excitation frequency. The most mature concepts were integrated into the full scale test. An imbalance exciter was used to simulate the engine vibrations at a realistic level experimentally. The neutralizers were tested at varying excitation frequencies to evaluate the tracking capabilities of the control system. It was proved that a significant vibration reduction is possible.
Mohler, R. R.; Rajkumar, V.; Zakrzewski, R. R.
A control design methodology based on a nonlinear time-series reference model is presented. It is indicated by highly nonlinear simulations that such designs successfully stabilize troublesome aircraft maneuvers undergoing large changes in angle of attack as well as large electric power transients due to line faults. In both applications, the nonlinear controller was significantly better than the corresponding linear adaptive controller. For the electric power network, a flexible AC transmission system with series capacitor power feedback control is studied. A bilinear autoregressive moving average reference model is identified from system data, and the feedback control is manipulated according to a desired reference state. The control is optimized according to a predictive one-step quadratic performance index. A similar algorithm is derived for control of rapid changes in aircraft angle of attack over a normally unstable flight regime. In the latter case, however, a generalization of a bilinear time-series model reference includes quadratic and cubic terms in angle of attack.
REZAZADEH, A.; SEDIGHIZADEH, M.
Nonlinear characteristics of wind turbines and electric generators necessitate complicated and nonlinear control of grid connected Wind Energy Conversion Systems (WECS). This paper proposes a modified self-tuning PID control strategy, using reinforcement learning for WECS control. The controller employs Actor-Critic learning in order to tune PID parameters adaptively. These Actor-Critic learning is a special kind of reinforcement learning that uses a single wavelet neural network to appro...
Fafoutis, Xenofon; Dragoni, Nicola
ODMAC (On-Demand Media Access Control) is a recently proposed MAC protocol designed to support individual duty cycles for Energy Harvesting — Wireless Sensor Networks (EH-WSNs). Individual duty cycles are vital for EH-WSNs, because they allow nodes to adapt their energy consumption to the ever......-changing environmental energy sources. In this paper, we present an improved and extended version of ODMAC and we analyze it by means of an analytical model that can approximate several performance metrics in an arbitrary network topology. The simulations and the analytical experiments show ODMAC's ability to satisfy...
Li Yanming; Lai Xinquan; Ye Qiang; Yuan Bing; Chen Fuji [Institute of Electronic CAD, Xidian University, Xi' an 710071 (China); Jia Xinzhang, E-mail: email@example.com, E-mail: firstname.lastname@example.org [Microelectronics Institute, Xidian University, Xi' an 710071 (China)
A current-mode buck DC-DC controller based on adaptive on-time (AOT) control is presented. The on-time is obtained by the techniques of input feedforward and output feedback, and the adaptive control is achieved by a sample-hold and time-ahead circuit. The AOT current-mode control scheme not only obtains excellent transient response speed, but also achieves the independence of loop stability on output capacitor ESR. In addition, the AOT current-mode control does not have subharmonic oscillation phenomenon seen in fixed frequency peak current-mode control, so there is no need of the slope compensation circuit. The auto-skip pulse frequency modulation (PFM) mode improves the conversion efficiency of light load effectively. The controller has been fabricated with UMC 0.6-mum BCD process successfully and the detailed experimental results are shown.
Full Text Available In this paper a hybrid controller combining a linear model following controller (LMFC and fuzzy logic control (FLC for speed vector controlled permanent magnet synchronous motor (PMSM is described on this study. The FLC is introduced at the adaptive mechanism level. First, an LMFC system is designed to allow the plant states to be controlled to follow the states produced by a reference model. In the nominal conditions, the model following is perfect and the adaptive mechanism based on the fuzzy logic is idle. Secondly, when parameter variations or external disturbances occur, an augmented signal will be generated by FLC mechanism to preserve the desired model following control performance. The effectiveness and robustness of the proposed controller is demonstrated by some simulation results.
LI Yan; FAN Xiao-ping
An adaptive fuzzy logic controller (AFC) is presented for the signal control of the urban traffic network.The AFC is composed of the signal control system-oriented control level and the signal controller-oriented fuzzy rules regulation level.The control level decides the signal tunings in an intersection with a fuzzy logic controller.The regulation level optimizes the fuzzy rules by the Adaptive Rule Module in AFC according to both the system performance index in current control period and the traffic flows in the last one.Consequently the system performances are improved.A weight coefficient controller (WCC) is also developed to describe the interactions of traffic flow among the adjacent intersections.So the AFC combined with the WCC can be applied in a road network for signal timings.Simulations of the AFC on a real traffic scenario have been conducted.Simulation results indicate that the adaptive controller for traffic control shows better performance than the actuated one.
Tomizuka, M. (Univ. of Calif., Berkeley (United States of America))
Approximately 20 years have passed since adaptive control transformed from art to science as it sprouted up with a stability theory as a core thereof. In the meantime, many application cases have been reported, and the expectation for the adaptive control is uprising. In this report, the reality and the application limitation of the adaptive control from the standpoint of how to use it are described. Described items are as follows: Discrete type adaptive control based on pole placement - direct method. structure of the controller. adaptive control rule and parameter identification algorithm. problems inapplication - Examination of linearity. Model dimensions. Zero point of the control target. Influence of external disturbance. Adaptive feed forward control. Introduction of integral action. Influence of noise. It is important that the simplification of the whole algorithm and adaptation of the theory are made by fully utilizing the foresighted informations on the control targets by not only simply applying a genearalized theory to practice. 14 refs., 3 figs.
Tran Vu TU
Full Text Available This paper firstly proposes an improved genetic algorithm (GA for optimization in adaptive bus signal priority control at signalized intersections. Unlike conventional genetic algorithms with slow convergence speed, this algorithm can increase the convergence speed by utilizing the compensation rule between consecutive signal cycles to narrow new possible generated population spaces. Secondly, the paper would like to present a way to apply the algorithm to a simple adaptive bus signal priority control as well as compare how much the computation time is saved when applying the improved algorithm. Then the research thirdly investigates the efficiency of the proposed algorithm under various flow rate situations. The results show that the improved genetic algorithm can reduce the computation time considerably, by up to 48.39% for the studied case. With high saturation degrees on the cross street, the convergence rate performance of the improved genetic algorithm is significantly good. The figure can be up to 36.2% when compared with the convergence rate of the conventional GA.
SHAO Hua-gang; CHEN Xiao; WANG Wei-nong
In this paper we propose a scalable admission control scheme for the QoS sensitivity traffic in DiffServ domains. In our scheme, the ingress routers perform admissibility test in a fully distributed and parallel fashion for requests based on our resource per-assigning mechanism.Then, we introduce a novel two phase token passing mechanism to adaptively optimize resource per-assigning among contending edge ronters in proportion to their traffic.In addition, we adopt a measurement based admission decision-making criterion to gain the benefit of high utilization of statistical multiplexing. Our simulation results indicate that even under very high request load it is possible to perform admission control and resource allocation in parallel without suffering in terms of response time, packet loss rate, or utilization.
Full Text Available The paper tackles with thickness control structure of the cold rolled strips. This structure is based on the rolls position control of a reversible quarto rolling mill. The main feature of the system proposed in the paper consists in the compensation of the errors introduced by the deficient dynamics of the hydraulic servo-system used for the rolls positioning, by means of a dynamic compensator that approximates the inverse system of the servo-system. Because the servo-system is considered variant over time, an on-line identification of the servo-system and parameter adapting of the compensator are achieved. The results obtained by numerical simulation are presented together with the data taken from real process. These results illustrate the efficiency of the proposed solutions.
Poyneer, L; Veran, J P
In many scenarios, an Adaptive Optics (AO) control system operates in the presence of temporally non-white noise. We use a Kalman filter with a state space formulation that allows suppression of this colored noise, hence improving residual error over the case where the noise is assumed to be white. We demonstrate the effectiveness of this new filter in the case of the estimated Gemini Planet Imager tip-tilt environment, where there are both common-path and non-common path vibrations. We discuss how this same framework can also be used to suppress spatial aliasing during predictive wavefront control assuming frozen flow in a low-order AO system without a spatially filtered wavefront sensor, and present experimental measurements from Altair that clearly reveal these aliased components.
An, Fengyan; Sun, Hongling; Li, Xiaodong
In this paper, active control of periodic vibration is implemented using maglev actuators which exhibit inherent nonlinear behaviors. A multi-channel feedforward control algorithm is proposed to solve these nonlinear problems, in which maglev actuators are treated as single-input-single-output systems with unknown time-varying nonlinearities. A radial basis function network is used by the algorithm as its controller, whose parameters are adapted only with the model of the linear system in the secondary path. Compared with the strategies in the conventional magnetic-levitation system control as well as nonlinear active noise/vibration control, the proposed algorithm has the advantage that the nonlinear modeling procedure of maglev actuators and the usage of displacement sensors could be both avoided. Numerical simulations and real-time experiments are carried out based on a multiple-degree-of-freedom vibration isolation system. The results show that the proposed algorithm not only could efficiently compensate for the actuators' time-varying nonlinearities, but also has the ability to greatly attenuate the energy of periodic vibration.
van Nooijen, Ronald; Kolechkina, Alla; Mol, Bart
For small sewer systems that combine foul water and storm water sewer functions in flat terrain, central control of the sewer system may have problems during dry weather. These systems are a combination of local gravity flow networks connected by pumps. Under those conditions the level in the wet well (local storage at the pumping station) should be kept below the entrance pipe but above the top of the intake of the pump. The pumps are dimensioned to cope with the combined flow of foul water and precipitation run off so their capacity is relatively large when compared wityh the volume available in the wet well. Under local control this is not a major problem because the effective controller time step is very short. For central control the control time step can become a problem. Especially when there is uncertainty about the relation between level and volume in the wet well. In this paper we describe a way to dynamically adapt the level to volume relation based on dry weather behaviour. This is important because a better estimate of this volume will reduce the number of on/off cycles for the pumps. It will also allow detection and correction for changes in pump performance due to aging.
The Reactor TRIGA PUSPATI (RTP)-type TRIGA Mark II was installed in the year 1982. The Power Controller System (PCS) or Automated Power Controller System (APCS) is very important for reactor operation and safety reasons. It is a function of controlled reactivity and reactor power. The existing power controller system is under development and due to slow response, low accuracy and low stability on reactor power control affecting the reactor safety. The nuclear reactor is a nonlinear system in nature, and it is power increases continuously with time. The reactor parameters vary as a function of power, fuel burnup and control rod worth. The output power value given by the power control system is not exactly as real value of reactor power. Therefore, controller system design is very important, an adaptive controller seems to be inevitable. The method chooses is a linear controller by using feedback linearization, for example Model Reference Adaptive Control. The developed APCS for RTP will be design by using Model Reference Adaptive Control (MRAC). The structured of RTP model to produce the dynamic behaviour of RTP on entire operating power range from 0 to 1MWatt. The dynamic behavior of RTP model is produced by coupling of neutronic and thermal-hydraulics. It will be developed by using software MATLAB/Simulink and hardware module card to handle analog input signal. A new algorithm for APCS is developed to control the movement of control rods with uniformity and orderly for RTP. Before APCS test to real plant, simulation results shall be obtained from RTP model on reactor power, reactivity, period, control rod positions, fuel and coolant temperatures. Those data are comparable with the real data for validation. After completing the RTP model, APCS will be tested to real plant on power control system performance by using real signal from RTP including fail-safe operation, system reliable, fast response, stability and accuracy. The new algorithm shall be a satisfied
Jiang, Jiefeng; Beck, Jeffrey; Heller, Katherine; Egner, Tobias
The anterior cingulate and lateral prefrontal cortices have been implicated in implementing context-appropriate attentional control, but the learning mechanisms underlying our ability to flexibly adapt the control settings to changing environments remain poorly understood. Here we show that human adjustments to varying control demands are captured by a reinforcement learner with a flexible, volatility-driven learning rate. Using model-based functional magnetic resonance imaging, we demonstrat...
Jia Yinghong; Xu Shijie
An adaptive sliding mode control (ASMC) law is proposed in decentralized scheme for trajectory tracking control of a new concept space robot. Each joint of the system is a free ball joint capable of rotating with three degrees of freedom (DOF). A cluster of control moment gyroscopes (CMGs) is mounted on each link and the base to actuate the system. The modified Rodrigues parameters (MRPs) are employed to describe the angular displacements, and the equations of motion are derived using Kane’s equations. The controller for each link or the base is designed sep-arately in decentralized scheme. The unknown disturbances, inertia parameter uncertainties and nonlinear uncertainties are classified as a ‘‘lumped” matched uncertainty with unknown upper bound, and a continuous sliding mode control (SMC) law is proposed, in which the control gain is tuned by the improved adaptation laws for the upper bound on norm of the uncertainty. A gen-eral amplification function is designed and incorporated in the adaptation laws to reduce the control error without conspicuously increasing the magnitude of the control input. Uniformly ultimate boundedness of the closed loop system is proved by Lyapunov’s method. Simulation results based on a three-link system verify the effectiveness of the proposed controller.
Full Text Available An adaptive sliding mode control (ASMC law is proposed in decentralized scheme for trajectory tracking control of a new concept space robot. Each joint of the system is a free ball joint capable of rotating with three degrees of freedom (DOF. A cluster of control moment gyroscopes (CMGs is mounted on each link and the base to actuate the system. The modified Rodrigues parameters (MRPs are employed to describe the angular displacements, and the equations of motion are derived using Kane’s equations. The controller for each link or the base is designed separately in decentralized scheme. The unknown disturbances, inertia parameter uncertainties and nonlinear uncertainties are classified as a “lumped” matched uncertainty with unknown upper bound, and a continuous sliding mode control (SMC law is proposed, in which the control gain is tuned by the improved adaptation laws for the upper bound on norm of the uncertainty. A general amplification function is designed and incorporated in the adaptation laws to reduce the control error without conspicuously increasing the magnitude of the control input. Uniformly ultimate boundedness of the closed loop system is proved by Lyapunov’s method. Simulation results based on a three-link system verify the effectiveness of the proposed controller.
Saberian, Fatemeh; Ghate, Archis; Kim, Minsun
Hypoxia, that is, insufficient oxygen partial pressure, is a known cause of reduced radiosensitivity in solid tumors, and especially in head-and-neck tumors. It is thus believed to adversely affect the outcome of fractionated radiotherapy. Oxygen partial pressure varies spatially and temporally over the treatment course and exhibits inter-patient and intra-tumor variation. Emerging advances in non-invasive functional imaging offer the future possibility of adapting radiotherapy plans to this uncertain spatiotemporal evolution of hypoxia over the treatment course. We study the potential benefits of such adaptive planning via a theoretical stochastic control framework using computer-simulated evolution of hypoxia on computer-generated test cases in head-and-neck cancer. The exact solution of the resulting control problem is computationally intractable. We develop an approximation algorithm, called certainty equivalent control, that calls for the solution of a sequence of convex programs over the treatment course; dose-volume constraints are handled using a simple constraint generation method. These convex programs are solved using an interior point algorithm with a logarithmic barrier via Newton’s method and backtracking line search. Convexity of various formulations in this paper is guaranteed by a sufficient condition on radiobiological tumor-response parameters. This condition is expected to hold for head-and-neck tumors and for other similarly responding tumors where the linear dose-response parameter is larger than the quadratic dose-response parameter. We perform numerical experiments on four test cases by using a first-order vector autoregressive process with exponential and rational-quadratic covariance functions from the spatiotemporal statistics literature to simulate the evolution of hypoxia. Our results suggest that dynamic planning could lead to a considerable improvement in the number of tumor cells remaining at the end of the treatment course
The design and performance of a self-adaptive feedforward rf control system are reported. The system was built for the linac of the Accelerator Test Facility (ATF) at Brookhaven National Laboratory. Variables of time along the linac macropulse, such as field or phase are discretized and represented as vectors. Upon turn-on or after a large change in the operating-point, the control system acquires the response of the system to test signal vectors and generates a linearized system response matrix. During operation an error vector is generated by comparing the linac variable vectors and a target vector. The error vector is multiplied by the inverse of the system's matrix to generate a correction vector is added to an operating point vector. This control system can be used to control a klystron to produce flat rf amplitude and phase pulses, to control a rf cavity to reduce the rf field fluctuation, and to compensate the energy spread among bunches in a rf linac. Beam loading effects can be corrected and a programmed ramp can be produced. The performance of the control system has been evaluated on the control of a klystron's output as well as an rf cavity. Both amplitude and phase have been regulated simultaneously. In initial tests, the rf output from a klystron has been regulated to an amplitude fluctuation of less than ±0.3% and phase variation of less than ±0.6deg. The rf field of the ATF's photo-cathode microwave gun cavity has been regulated to ±5% in amplitude and simultaneously to ±1deg in phase. Regulating just the rf field amplitude in the rf gun cavity, we have achieved amplitude fluctuation of less than ±2%. (orig.)
Full Text Available This paper presents a microgrid stability controller (MSC in order to provide existing distributed generation units (DGs the additional functionality of working in islanding mode without changing their control strategies in grid-connected mode and to enhance the stability of the microgrid. Microgrid operating characteristics and mathematical models of the MSC indicate that the system is inherently nonlinear and time-variable. Therefore, this paper proposes an adaptive robust total sliding-mode control (ARTSMC system for the MSC. It is proved that the ARTSMC system is insensitive to parametric uncertainties and external disturbances. The MSC provides fast dynamic response and robustness to the microgrid. When the system is operating in grid-connected mode, it is able to improve the controllability of the exchanged power between the microgrid and the utility grid, while smoothing the DGs’ output power. When the microgrid is operating in islanded mode, it provides voltage and frequency support, while guaranteeing seamless transition between the two operation modes. Simulation and experimental results show the effectiveness of the proposed approach.
Hai-ying DONG; Chuan-hua SUN
-For the characteristics of wind power generation system is multivariable,nonlinear and random,in this paper the neural network PID adaptive control is adopted.The size of pitch angle is adjusted in time to improve the performance of power control.The PID parameters are corrected by the gradient descent method,and Radial Basis Functinn(RBF)neural network is used as the system identifier in this method.Simulation results shaw that by using neural adaptive PID controller the generator power control can inhibit effectively the speed and affect the output power of generator.The dynamic performance and robustness of the controlled system is good,and the performance of wind power system is improved.
YU Jian-cheng; ZHANG Ai-qun; WANG Xiao-hui; WU Bao-ju
This paper thoroughly studies a control system with control allocation for a manned submersible in deep sea being developed in China. The proposed control system consists of a neural-network-based direct adaptive controller and a dynamic control allocation module. A control energy cost function is used as the optimization criteria of the control allocation module, and weighted pseudo-inverse is used to find the solution of the control allocation problem. In the presence of bounded unknown disturbance and neural networks approximation error, stability of the closed-loop control system of manned submersible is proved with Lyaponov theory. The feasibility and validity of the proposed control system is further verified through experiments conducted on a semi-physical simulation platform for the manned submersible in deep sea.
Full Text Available Based on the feedback linearized technique and control of differential and algebraic systems, the Indirect Adaptive fuzzy excitation control is presented in this paper for SVC (static var compensator and generator excitation controllers in power systems with nonlinear loads. It can improve both the power angle stability ofgenerators and the voltage behavior at the SVC location. Simulation results shown that the proposed controller IAFLC, compared with a controller based on tradition linearization technique can enhance the transient stability of the power system. In addition, this system is used through the Algerian South-Western power system (SONELGAZ "Algerian electrical society" NAAMA city and BECHAR city.
Full Text Available Automatic steering control is the key factor and essential condition in the realization of the automatic navigation control of agricultural vehicles. In order to get satisfactory steering control performance, an adaptive sliding mode control method based on a nonlinear integral sliding surface is proposed in this paper for agricultural vehicle steering control. First, the vehicle steering system is modeled as a second-order mathematic model; the system uncertainties and unmodeled dynamics as well as the external disturbances are regarded as the equivalent disturbances satisfying a certain boundary. Second, a transient process of the desired system response is constructed in each navigation control period. Based on the transient process, a nonlinear integral sliding surface is designed. Then the corresponding sliding mode control law is proposed to guarantee the fast response characteristics with no overshoot in the closed-loop steering control system. Meanwhile, the switching gain of sliding mode control is adaptively adjusted to alleviate the control input chattering by using the fuzzy control method. Finally, the effectiveness and the superiority of the proposed method are verified by a series of simulation and actual steering control experiments.
Full Text Available The aim of this review is to present the actual status of development in adaptive solar control by use of thermotropic and organic thermochromic materials. Such materials are suitable for application in smart windows. In detail polymer blends, hydrogels, resins, and thermoplastic films with a reversible temperature-dependent switching behavior are described. A comparative evaluation of the concepts for these energy efficient materials is given as well. Furthermore, the change of strategy from ordinary shadow systems to intrinsic solar energy reflection materials based on phase transition components and a first remark about their realization is reported. Own current results concerning extruded films and high thermally stable casting resins with thermotropic properties make a significant contribution to this field.
To get simpler operation in modified fuzzy adaptive learning control network (FALCON) in some engineering application, sigmoid nonlinear function is employed as a substitute of traditional Gaussian membership function. For making the modified FALCON learning more efficient and stable, a simulated annealing (SA) learning coefficient is introduced into learning algorithm. At first, the basic concepts and main advantages of FALCON were briefly reviewed. Subsequently, the topological structure and nodes operation were illustrated; the gradient-descent learning algorithm with SA learning coefficient was derived;and the distinctions between the archetype and the modification were analyzed. Eventually, the significance and worthiness of the modified FALCON were validated by its application to probability prediction of anode effect in aluminium electrolysis cells.
Full Text Available Adaptive vehicle speed control is critical for developing Advanced Driver Assistance Systems (ADAS. Vehicle speed control considering variable road geometry has become a hotspot in ADAS research. In this paper, first, an exploration of intrinsic relationship between vehicle operation and road geometry is made. Secondly, a collaborative vehicle coupling model, a road geometry model, and an AVSC, which can respond to variable road geometry in advance, are developed. Then, based on H∞ control method and the minimum energy principle, a performance index is specified by a cost function for the proposed AVSC, which can explicitly consider variable road geometry in its optimization process. The proposed AVSC is designed by the Hamilton-Jacobi Inequality (HJI. Finally, simulations are carried out by combining the vehicle model with the road geometry model, in an aim of minimizing the performance index of the AVSC. Analyses of the simulation results indicate that the proposed AVSC can automatically and effectively regulate speed according to variable road geometry. It is believed that the proposed AVSC can be used to improve the economy, comfort, and safety effects of current ADAS.
Kandil, Osama A.; Yang, Zhi
Adaptive active flow control for twin-tail buffet alleviation is investigated. The concept behind this technique is to place control ports on the tail outer and inner surfaces with flow suction or blowing applied through these ports in order to minimize the pressure difference across the tail. The suction or blowing volume flow rate from each port is proportional to the pressure difference across the tail at this location. A parametric study of the effects of the number and location of these ports on the buffet response is carried out. The computational model consists of a sharp-edged delta wing of aspect ratio one and swept-back flexible twin tail with taper ratio of 0.23. This complex multidisciplinary problem is solved sequentially using three sets of equations for the fluid flow, aeroelastic response and grid deformation, using a dynamic multi-block grid structure. The computational model is pitched at 30 deg angle of attack. The freestream Mach number and Reynolds number are 0.3 and 1.25 million, respectively. The model is investigated for the inboard position of the twin tails, which corresponds to a separation distance between the twin tails of 33% of the wing span. Comparison of the time history and power spectral density responses of the tails for various distributions of the control ports are presented and discussed.
Basin, Michael; Bharath Panathula, Chandrasekhara; Shtessel, Yuri
This paper presents an adaptive gain algorithm for second-order sliding-mode control (2-SMC), specifically a super-twisting (STW)-like controller, with uniform finite/fixed convergence time, that is robust to perturbations with unknown bounds. It is shown that a second-order sliding mode is established as exact finite-time convergence to the origin if the adaptive gain does not have the ability to get reduced and converge to a small vicinity of the origin if the adaptation algorithm does not overestimate the control gain. The estimate of fixed convergence time of the studied adaptive STW-like controller is derived based on the Lyapunov analysis. The efficacy of the proposed adaptive algorithm is illustrated in a tutorial example, where the adaptive STW-like controller with uniform finite/fixed convergence time is compared to the adaptive STW controller with non-uniform finite convergence time.
Seraji, Homayoun (Inventor)
The described and improved multi-arm invention of this application presents three strategies for adaptive control of cooperative multi-arm robots which coordinate control over a common load. In the position-position control strategy, the adaptive controllers ensure that the end-effector positions of both arms track desired trajectories in Cartesian space despite unknown time-varying interaction forces exerted through a load. In the position-hybrid control strategy, the adaptive controller of one arm controls end-effector motions in the free directions and applied forces in the constraint directions; while the adaptive controller of the other arm ensures that the end-effector tracks desired position trajectories. In the hybrid-hybrid control strategy, the adaptive controllers ensure that both end-effectors track reference position trajectories while simultaneously applying desired forces on the load. In all three control strategies, the cross-coupling effects between the arms are treated as disturbances which are compensated for by the adaptive controllers while following desired commands in a common frame of reference. The adaptive controllers do not require the complex mathematical model of the arm dynamics or any knowledge of the arm dynamic parameters or the load parameters such as mass and stiffness. Circuits in the adaptive feedback and feedforward controllers are varied by novel adaptation laws.
Full Text Available This paper presents a method for optimization of control parameters of an adaptive GBN scheme in error-prone satellite channel. Method is based on the channel model with three state, where channel have the variable noise level.
Full Text Available X–Z inverted pendulum is a new kind of inverted pendulum and it can move with the combination of the vertical and horizontal forces. This paper addresses the control problem of X-Z inverted pendulum in the presents of system uncertainties and external disturbances, and an adaptive fuzzy sliding mode control approach is proposed. The fuzzy system is used to approximate the system uncertainties and the complicated intermediate control functions in the backstepping control design. To update the parameters of the fuzzy system, a proper proportional-integral adaptation law is introduced. Finally, simulation studies are done to show the stabilization of the X-Z inverted pendulum under the proposed method.
Ke, Liu; Tokar, R.; Mcvey, B.
In this study, an integrated neural network control architecture for nonlinear dynamic systems is presented. Most of the recent emphasis in the neural network control field has no error feedback as the control input which rises the adaptation problem. The integrated architecture in this paper combines feed forward control and error feedback adaptive control using neural networks. The paper reveals the different internal functionality of these two kinds of neural network controllers for certain input styles, e.g., state feedback and error feedback. Feed forward neural network controllers with state feedback establish fixed control mappings which can not adapt when model uncertainties present. With error feedbacks, neural network controllers learn the slopes or the gains respecting to the error feedbacks, which are error driven adaptive control systems. The results demonstrate that the two kinds of control scheme can be combined to realize their individual advantages. Testing with disturbances added to the plant shows good tracking and adaptation.
Yue FU; Tianyou CHAI
A multivariable adaptive controller feasible for implementation on distributed computer systems (DCS) is presented for a class of uncertain nonlinear multivariable discrete time systems. The adaptive controller is composed of a linear adaptive controller, a neural network nonlinear adaptive controller and a switching mechanism. The linear controller can provide boundedness of the input and output signals, and the nonlinear controller can improve the performance of the system. The purpose of using the switching mechanism is to obtain the improved system performance and stability simultaneously. Theory analysis and simulation results are presented to show the effectiveness of the proposed method.
Luecht, Richard M.
This paper presents a multistage adaptive testing test development paradigm that promises to handle content balancing and other test development needs, psychometric reliability concerns, and item exposure. The bundled multistage adaptive testing (BMAT) framework is a modification of the computer-adaptive sequential testing framework introduced by…
Full Text Available This paper focuses on high precision leveling control of an underwater heavy load platform, which is viewed as an underwater parallel robot on the basis of its work pattern. The kinematic of platform with deformation is analyzed and the dynamics model of joint space is established. An adaptive backstepping controller according to Lyapunov's function is proposed for leveling control of platform based on joint space. Furthermore, the “lowest point fixed angle error” leveling scheme called “chase” is chosen for leveling control of platform. The digital simulation and practical experiment of single joint space actuator are carried out, and the results show high precision servo control of joint space. On the basis of this, the platform leveling control simulation relies on the hardware-in-loop system. The results indicate that the proposed controller can effectively restrain the influence from system parameter uncertainties and external disturbance to realize high precision leveling control of the underwater platform.
FENG Ling-ling; ZHANG Wei
This paper proposes an indirect adaptive neural control scheme for a class of nonlinear systems with time delays. Based on the backstepping technique and Lyapunov–Krasovskii functional method are combined to construct the indirect adaptive neural controller. The proposed indirect adaptive neural controller guarantees that the state variables converge to a small neighborhood of the origin and all the signals of the closed-loop system are bounded. Finally, an example is used to show the effectiveness of the proposed control strategy.
Casellato, Claudia; Antonietti, Alberto; Garrido, Jesus A; Carrillo, Richard R; Luque, Niceto R; Ros, Eduardo; Pedrocchi, Alessandra; D'Angelo, Egidio
The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN) with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning), a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions. PMID:25390365
To satisfy the need for high-speed and high-accuracy machining of NURBS curve. Firstly the form of NURBS curve is analyzed and Talor's expansion of the parameter u with respect to time t is used to obtain the algorithm of the first order approximation interpolation. Secondly, based on the algorithm of the controlled chord error interpolator, an intelligent interpolation algorithm of the adaptive feedrate control is proposed. According to the actual machining capacity of machine tools, this algorithm uses look-ahead method, which dispenses with the complicated computation of the end point estimation of NURBS curve, to analyze the curve segment required by the maximum deceleration distance. Thus, the feedrate could decrease in advance and vary with the curvature and the variation ratio of curvature, which makes machining motion quite smooth. Not only could high accuracy and frne surface quality be achieved during high-speed machining, but also the overload of cutter tools is avoided on corners. Finally, in order to facilitate the calculation of interpolation, the dynamic matrix representation and efficient algorithm of curvature computation of the NURBS curve are presented.
Wu, Zhenhui; Dong, Chaoyang
Because of nonlinearity and strong coupling of reaction-jet and aerodynamics compound control missile, a missile autopilot design method based on adaptive fuzzy sliding mode control (AFSMC) is proposed in this paper. The universal approximation ability of adaptive fuzzy system is used to approximate the nonlinear function in missile dynamics equation during the flight of high angle of attack. And because the sliding mode control is robustness to external disturbance strongly, the sliding mode surface of the error system is constructed to overcome the influence of approximation error and external disturbance so that the actual overload can track the maneuvering command with high precision. Simulation results show that the missile autopilot designed in this paper not only can track large overload command with higher precision than traditional method, but also is robust to model uncertainty and external disturbance strongly.
This paper presents the optimal control modification for linear uncertain plants. The Lyapunov analysis shows that the modification parameter has a limiting value depending on the nature of the uncertainty. The optimal control modification exhibits a linear asymptotic property that enables it to be analyzed in a linear time invariant framework for linear uncertain plants. The linear asymptotic property shows that the closed-loop plants in the limit possess a scaled input-output mapping. Using this property, we can derive an analytical closed-loop transfer function in the limit as the adaptive gain tends to infinity. The paper revisits the Rohrs counterexample problem that illustrates the nature of non-robustness of model-reference adaptive control in the presence of unmodeled dynamics. An analytical approach is developed to compute exactly the modification parameter for the optimal control modification that stabilizes the plant in the Rohrs counterexample. The linear asymptotic property is also used to address output feedback adaptive control for non-minimum phase plants with a relative degree 1.
张家树; 肖先赐; 万继宏
An adaptive nonlinear feedback-control method is proposed to control continuous-time chaotic dynamical systems,where the adaptive nonlinear controller acts on only one-dimensional error signals between the desired state and the observed chaotic state of a system. The reduced parameter adaptive quadratic predictor used in adaptive feedback cancellation of the nonlinear terms can control the system at any desired state. Computer simulation results on the Lorenz system are shown to demonstrate the effectiveness of this feedback-control method.
WEI Jiahua; WANG Guangqian; WENG Wenbin; CAI Zhiguo; CHEN Liangcheng
According to the principle of procedure control and the characteristic of stochastic of inflow and water demands, this paper deals with the application of adaptive control to a water resources regulation system. The main control objective is to approach the vested target of water resources allocation by controlling the reservoir discharge and water demand. The adaptive control implemented is based on the linear quadratic control approach. Models of water balance, reservoir adjusted model and allocation model are used for the control purposes. The results show the performance of this adaptive scheme and its ability to control the water resources allocation process.
Jian Cao; Yumin Su; Jinxin Zhao
Underwater vehicles operating in complex ocean conditions present difficulties in determining accurate dynamic models.To guarantee robustness against parameter uncertainty,an adaptive controller for dive-plane control,based on Lyapunov theory and back-stepping techniques,was proposed.In the closed-loop system,asymptotic tracking of the reference depth and pitch angle trajectories was accomplished.Simulation results were presented which show effective dive-plane control in spite of the uncertainties in the system parameters.
We use the approach of "optimal" switching to design the adaptive control because the design among multiple models is intuitively more practically feasible than the traditional adaptive control in improving the performances. We prove that for a typical class of nonlinear systems disturbed by random noise, the multiple model adaptive switching control based on WLS(Weighted Least Squares) or projected-LS (Least Squares) is stable and convergent.
Vehicle Dynamics and Control provides a comprehensive coverage of vehicle control systems and the dynamic models used in the development of these control systems. The control system applications covered in the book include cruise control, adaptive cruise control, ABS, automated lane keeping, automated highway systems, yaw stability control, engine control, passive, active and semi-active suspensions, tire-road friction coefficient estimation, rollover prevention, and hybrid electric vehicle. In developing the dynamic model for each application, an effort is made to both keep the model simple enough for control system design but at the same time rich enough to capture the essential features of the dynamics. A special effort has been made to explain the several different tire models commonly used in literature and to interpret them physically. In the second edition of the book, chapters on roll dynamics, rollover prevention and hybrid electric vehicles have been added, and the chapter on electronic stability co...
许海波; 王光瑞; 陈式刚
The method for controlling Hamiltonian chaos by adaptive integrable mode coupling is extended to controlling strong chaos by adaptive integrable and near-integrable mode coupling. We illustrate this method with a highly chaotic system, the perturbed cat map. All orbits can be effectively controlled to the periodic or quasiperiodic orbits. The method is robust against the presence of weak external noise.
Choi, Julia T.; Vining, Eileen P. G.; Reisman, Darcy S.; Bastian, Amy J.
Walking flexibility depends on use of feedback or reactive control to respond to unexpected changes in the environment, and the ability to adapt feedforward or predictive control for sustained alterations. Recent work has demonstrated that cerebellar damage impairs feedforward adaptation, but not feedback control, during human split-belt treadmill…
Henselmans, Inge; Sanderman, Robbert; Helgeson, Vicki S; de Vries, J; Smink, Ans; Ranchor, Adelita V
OBJECTIVES: Although cognitive adaptation theory suggests that personal control acts as a stress buffer when facing adversity, maladaptive outcomes might occur when control is disconfirmed. The moderating effect of disappointing news on the adaptiveness of personal control over cure in women with br
Full Text Available In this paper, based on fuzzy neural networks, we develop an adaptive sliding mode controller for chaos suppression and tracking control in a chaotic permanent magnet synchronous motor (PMSM drive system. The proposed controller consists of two parts. The first is an adaptive sliding mode controller which employs a fuzzy neural network to estimate the unknown nonlinear models for constructing the sliding mode controller. The second is a compensational controller which adaptively compensates estimation errors. For stability analysis, the Lyapunov synthesis approach is used to ensure the stability of controlled systems. Finally, simulation results are provided to verify the validity and superiority of the proposed method.
The use of concentrating photovoltaic (CPV) technology has been the most promising method of harvesting solar radiation. These CPV systems often require motor-driven tracking devices to steer the sun's beams onto solar cells. The cost of maintaining these tracking systems is the primary inhibitor for widespread application. We aim to overcome the need for mechanical trackers through the use of an electrowetting-driven solar tracking (EWST) system. The electrowetting-driven solar tracking system consists of an array of novel electrowetting-controlled dual liquid prisms, which are filled with immiscible fluids that have large differences in refractive indices. The naturally formed meniscus between the fluids can function as a dynamic optical prism. Via the full-range modulation of the liquid prisms, incident sunlight can be adaptively tracked, steered, and focused onto CPV cells through a fixed optical condenser. Furthermore, unlike the conventional and cumbersome motor-driven tracking systems used today, the liquid prism system would be suitable for rooftop applications. The results of this project reveal that the EWST system has the potential to generate ~ 70% more green energy at 50% of the conventional capital cost.
Full Text Available The endothelium is nowadays described as an entire organ that regulates various processes: vascular tone, coagulation, inflammation, and immune cell trafficking, depending on the vascular site and its specific microenvironment as well as on endothelial cell-intrinsic mechanisms like epigenetic changes. In this review, we will focus on the control of the adaptive immune response by the tumor vasculature. In physiological conditions, the endothelium acts as a barrier regulating cell trafficking by specific expression of adhesion molecules enabling adhesion of immune cells on the vessel, and subsequent extravasation. This process is also dependent on chemokine and integrin expression, and on the type of junctions defining the permeability of the endothelium. Endothelial cells can also regulate immune cell activation. In fact, the endothelial layer can constitute immunological synapses due to its close interactions with immune cells, and the delivery of co-stimulatory or co-inhibitory signals. In tumor conditions, the vasculature is characterized by abnormal vessel structure and permeability, and by specific phenotype of endothelial cells. All these abnormalities lead to a modulation of intratumoral immune responses and contribute to the development of intratumoral immunosuppression, which is a major mechanism for promoting the development, progression and treatment resistance of tumors. The in-depth analysis of these various abnormalities will help defining novel targets for the development of antitumoral treatments. Furthermore, eventual changes of the endothelial cell phenotype identified by plasma biomarkers could secondarily be selected to monitor treatment efficacy.
This book presents a mechatronic approach to Active Noise Control (ANC). It describes the required elements of system theory, engineering acoustics, electroacoustics and adaptive signal processing in a comprehensive, consistent and systematic manner using a unified notation. Furthermore, it includes a design methodology for ANC-systems, explains its application and describes tools to be used for ANC-system design. From the research point of view, the book presents new approaches to sound source localization in weakly damped interiors. One is based on the inverse finite element method, the other is based on a sound intensity probe with an active free field. Furthermore, a prototype of an ANC-system able to reach the physical limits of local (feed-forward) ANC is described. This is one example for applied research in ANC-system design. Other examples are given for (i) local ANC in a semi-enclosed subspace of an aircraft cargo hold and (ii) for the combination of audio entertainment with ANC.
Bieniawski, Stefan; Wolpert, David H.
Product Distribution (PO) theory was recently developed as a broad framework for analyzing and optimizing distributed systems. Here we demonstrate its use for adaptive distributed control of Multi-Agent Systems (MASS), i.e., for distributed stochastic optimization using MAS s. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (Probability dist&&on on the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. One common way to find that equilibrium is to have each agent run a Reinforcement Learning (E) algorithm. PD theory reveals this to be a particular type of search algorithm for minimizing the Lagrangian. Typically that algorithm i s quite inefficient. A more principled alternative is to use a variant of Newton's method to minimize the Lagrangian. Here we compare this alternative to RL-based search in three sets of computer experiments. These are the N Queen s problem and bin-packing problem from the optimization literature, and the Bar problem from the distributed RL literature. Our results confirm that the PD-theory-based approach outperforms the RL-based scheme in all three domains.
Full Text Available This paper presents the implementation of an adaptive supervisory sliding fuzzy cerebellar model articulation controller (FCMAC in the speed sensorless vector control of an induction motor (IM drive system. The proposed adaptive supervisory sliding FCMAC comprised a supervisory controller, integral sliding surface, and an adaptive FCMAC. The integral sliding surface was employed to eliminate steady-state errors and enhance the responsiveness of the system. The adaptive FCMAC incorporated an FCMAC with a compensating controller to perform a desired control action. The proposed controller was derived using the Lyapunov approach, which guarantees learning-error convergence. The implementation of three intelligent control schemes—the adaptive supervisory sliding FCMAC, adaptive sliding FCMAC, and adaptive sliding CMAC—were experimentally investigated under various conditions in a realistic sensorless vector-controlled IM drive system. The root mean square error (RMSE was used as a performance index to evaluate the experimental results of each control scheme. The analysis results indicated that the proposed adaptive supervisory sliding FCMAC substantially improved the system performance compared with the other control schemes.
Mizumoto, Ikuro; Takagi, Taro; Fukui, Sota; Shah, Sirish L.
This paper deals with a design problem of an adaptive output feedback control for discrete-time systems with a parallel feedforward compensator (PFC) which is designed for making the augmented controlled system ASPR. A PFC design scheme by a FRIT approach with only using an input/output experimental data set will be proposed for discrete-time systems in order to design an adaptive output feedback control system. Furthermore, the effectiveness of the proposed PFC design method will be confirmed through numerical simulations by designing adaptive control system with adaptive NN (Neural Network) for an uncertain discrete-time system.
管继富; 侯朝桢; 顾亮; 武云鹏
The LQG control system is employed as vehicle suspension's optimal target system, which has an adaptive ability to the road conditions and vehicle speed in a limited bandwidth. In order to keep the optimal performances when the suspension parameters change, a model reference adaptive fuzzy control (MRAFC) strategy is presented. The LQG control system serves as the reference model in the MRAFC system. The simulation results indicate that the presented MRAFC system can adapt to the parameters variation of vehicle suspension and track the optimality of the LQG control system, the presented vehicle suspension MRAFC system has the ability to adapt to road conditions and suspension parameters change.
黄伟红; 张福炎; 孙正兴
An approach based on adaptive congestion control and adaptive error recovery with RS (Reed-Solomon) coding method is presented for efficient video transmission over the Internet.Featured by weighted moving average rate control and TCP-fdendliness,AVSP,a novel adaptive video streaming protocol,is designed with adjustable rate control parameters so as to respond quickly to the QoS status fluctuation during video transmission over the Internet.Combined with congestion control policy,an adaptive RS coding error recovery scheme with variable parameters is presented to enhance the robustness of MPEG video transmission over the Intemet with restriction to the total system bandwidth.``
Keymeulen, D.; Yiu, P.; Berisford, D. F.; Hand, K. P.; Carlson, R. W.; Conroy, M.
Here we present noise mitigation techniques developed as part of an adaptive controller for a very compact Compositional InfraRed Interferometric Spectrometer (CIRIS) implemented on a stand-alone field programmable gate array (FPGA) architecture with emphasis on space applications in high radiation environments such as Europa. CIRIS is a novel take on traditional Fourier Transform Spectrometers (FTS) and replaces linearly moving mirrors (characteristic of Michelson interferometers) with a constant-velocity rotating refractor to variably phase shift and alter the path length of incoming light. The design eschews a monochromatic reference laser typically used for sampling clock generation and instead utilizes constant time-sampling via internally generated clocks. This allows for a compact and robust device, making it ideal for spaceborne measurements in the near-IR to thermal-IR band (2-12 µm) on planetary exploration missions. The instrument's embedded microcontroller is implemented on a VIRTEX-5 FPGA and a PowerPC with the aim of sampling the instrument's detector and optical rotary encoder in order to construct interferograms. Subsequent onboard signal processing provides spectral immunity from the noise effects introduced by the compact design's removal of a reference laser and by the radiation encountered during space flight to destinations such as Europa. A variety of signal processing techniques including resampling, radiation peak removal, Fast Fourier Transform (FFT), spectral feature alignment, dispersion correction and calibration processes are applied to compose the sample spectrum in real-time with signal-to-noise-ratio (SNR) performance comparable to laser-based FTS designs in radiation-free environments. The instrument's FPGA controller is demonstrated with the FTS to characterize its noise mitigation techniques and highlight its suitability for implementation in space systems.
Rasmussen, Henrik; Vadstrup, P.; Børsting, H.
This paper presents an adaptive observer for extimating the rotor position and speed of a permanent magnet synchronous motors (PMSM). The observer compensates for voltage offsets and permanent magnet strength variations. The adaptation structure for estimating the strength of the permanent magnet...
Jelsma, Otto; Merrienboer, van Jeroen J.G.; Bijlstra, Jim P.
This paper presents a detailed description of the ADAPT (Apply Delayed Automatization for Positive Transfer) design model. ADAPT is based upon production system models of learning and provides guidelines for developing instructional systems that offer transfer of leamed skills. The model suggests th
The twin-roll strip casting process is a steel-strip production method which combines continuous casting and hot rolling processes. The production line from molten liquid steel to the final steel-strip is shortened and the production cost is reduced significantly as compared to conventional continuous casting. The quality of strip casting process depends on many process parameters, such as molten steel level in the pool, solidification position, and roll gap. Their relationships are complex and the strip casting process has the properties of nonlinear uncertainty and time-varying characteristics. It is difficult to establish an accurate process model for designing a model-based controller to monitor the strip quality. In this paper, a model-free adaptive neural network controller is developed to overcome this problem. The proposed control strategy is based on a neural network structure combined with a sliding-mode control scheme. An adaptive rule is employed to on-line adjust the weights of radial basis functions by using the reaching condition of a specified sliding surface. This surface has the on-line learning ability to respond to the system's nonlinear and time-varying behaviors. Since this model-free controller has a simple control structure and small number of control parameters, it is easy to implement. Simulation results, based on a semi experimental system dynamic model and parameters, are executed to show the control performance of the proposed intelligent controller. In addition, the control performance is compared with that of a traditional Pid controller
He, Jinwei; Li, Yun Wei; Blaabjerg, Frede
To accomplish superior harmonic compensation performance using distributed generation (DG) unit power electronics interfaces, an adaptive hybrid voltage and current controlled method (HCM) is proposed in this paper. It shows that the proposed adaptive HCM can reduce the numbers of low-pass/bandpa......To accomplish superior harmonic compensation performance using distributed generation (DG) unit power electronics interfaces, an adaptive hybrid voltage and current controlled method (HCM) is proposed in this paper. It shows that the proposed adaptive HCM can reduce the numbers of low...... harmonic compensation performance. Comprehensive simulated and experimental results from a single-phase microgrid are provided to verify the feasibility of the proposed adaptive HCM approach....
Hayder S. Abd Al-Amir
Full Text Available An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO. The structure of the controller consists of two models :the modified Elman neural network (MENN and the feed forward multi-layer Perceptron (MLP. The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. The feed forward neural controller is trained off-line and adaptive weights are implemented on-line to find the flap angles, which controls the plunge and pitch motion of the wing. The general back propagation algorithm is used to learn the feed forward neural controller and the neural identifier. The simulation results show the effectiveness of the proposed control algorithm; this is demonstrated by the minimized tracking error to zero approximation with very acceptable settling time even with the existence of bounded external disturbances.
Ehsan Maani Miandoab
Full Text Available Two different control methods, namely, adaptive sliding mode control and impulse damper, are used to control the chaotic vibration of a block on a belt system due to the rate-dependent friction. In the first method, using the sliding mode control technique and based on the Lyapunov stability theory, a sliding surface is determined, and an adaptive control law is established which stabilizes the chaotic response of the system. In the second control method, the vibration of this system is controlled by an impulse damper. In this method, an impulsive force is applied to the system by expanding and contracting the PZT stack according to efficient control law. Numerical simulations demonstrate the effectiveness of both methods in controlling the chaotic vibration of the system. It is shown that the settling time of the controlled system using impulse damper is less than that one controlled by adaptive sliding mode control; however, it needs more control effort.
Ge, Shuzhi Sam; Hong, Fan; Lee, Tong Heng
In this paper, adaptive neural control is presented for a class of strict-feedback nonlinear systems with unknown time delays. The proposed design method does not require a priori knowledge of the signs of the unknown virtual control coefficients. The unknown time delays are compensated for using appropriate Lyapunov-Krasovskii functionals in the design. It is proved that the proposed backstepping design method is able to guarantee semiglobal uniformly ultimately boundedness of all the signals in the closed-loop. In addition, the output of the system is proven to converge to a small neighborhood of the origin. Simulation results are provided to show the effectiveness of the proposed approach.
Kosut, Robert L.
Adaptive systems under slow parameter adaption can be analyzed by the method of averaging. This provides a means to assess stability (and instability) properties of most adaptive systems, either continuous-time or (more importantly for practice) discrete-time, as well as providing an estimate of the region of attraction. Although the method of averaging is conceptually straightforward, even simple examples are well beyond hand calculations. Specific software tools are proposed which can provide the basis for user-friendly environment to perform the necessary computations involved in the averaging analysis.
Full Text Available Living creatures, like walking animals, have found fascinating solutions for the problem of locomotion control. Their movements show the impression of elegance including versatile, energy-efficient, and adaptable locomotion. During the last few decades, roboticists have tried to imitate such natural properties with artificial legged locomotion systems by using different approaches including machine learning algorithms, classical engineering control techniques, and biologically-inspired control mechanisms. However, their levels of performance are still far from the natural ones. By contrast, animal locomotion mechanisms seem to largely depend not only on central mechanisms (central pattern generators, CPGs and sensory feedback (afferent-based control but also on internal forward models (efference copies. They are used to a different degree in different animals. Generally, CPGs organize basic rhythmic motions which are shaped by sensory feedback while internal models are used for sensory prediction and state estimations. According to this concept, we present here adaptive neural locomotion control consisting of a CPG mechanism with neuromodulation and local leg control mechanisms based on sensory feedback and adaptive neural forward models with efference copies. This neural closed-loop controller enables a walking machine to perform a multitude of different walking patterns including insect-like leg movements and gaits as well as energy-efficient locomotion. In addition, the forward models allow the machine to autonomously adapt its locomotion to deal with a change of terrain, losing of ground contact during stance phase, stepping on or hitting an obstacle during swing phase, leg damage, and even to promote cockroach-like climbing behavior. Thus, the results presented here show that the employed embodied neural closed-loop system can be a powerful way for developing robust and adaptable machines.
Li Ning; Yuan Hui-Qun; Sun Hai-Yi; Zhang Qing-Ling
In this paper,the stabilization of a continuous time-delayed system is considered.To control the bifurcation and chaos in a time-delayed system,a parameter perturbation control and a hybrid control are proposed.Then,to ensure the asymptotic stability of the system in the presence of unexpected system parameter changes,the adaptive control idea is introduced,i.e.,the perturbation control parameter and the hybrid control parameter are automatically tuned according to the adaptation laws,respectively.The adaptation algorithms are constructed based on the Lyapunov-Krasovskii stability theorem.The adaptive parameter perturbation control and the adaptive hybrid control methods improve the corresponding constant control methods.They have the advantages of increased stability,adaptability to the changes of the system parameters,control cost saving,and simplicity.Numerical simulations for a well-known chaotic time-delayed system are performed to demonstrate the feasibility and superiority of the proposed control methods.A comparison of the two adaptive control methods is also made in an experimental study.
In this work, an innovative real-time microwave control approach is proposed, to improve the temperature homogeneity under microwave heating. Multiple adaptive or intelligent control structures have been developed, including the model predictive control, neural network control and reinforcement learning control methods. Experimental results prove that these advanced control methods can effectively reduce the final temperature derivations and improve the temperature homogeneity.
Bargatze, L. F.
Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted
Full Text Available Adaptive assistive control for a haptic interface system is proposed in the present paper. The assistive control system consists of three subsystems: a servo controller to match the response of the controlled machine to the virtual model, an online identifier of the operator’s control characteristics, and a variable dynamics control using adaptive mechanism. The adaptive mechanism tunes an impedance of the virtual model for the haptic device according to the identified operator’s characteristics so as to enhance the operator’s control performance. The adaptive law is derived by utilizing a Lyapunov candidate function. Using a haptic interface device composed by a xy-stage, an effectiveness of the proposed control method was evaluated experimentally. As a result, it was confirmed that the operator’s characteristics can be estimated sufficiently and that performance of the operation was enhanced by the variable dynamics assistive control.
XiaoJing Wang; ChangFu Xian; CaoLei Wan; JinBao Zhao; LiWei Xiu; AnCai Yu
In order to consider the influence of the continuous rotary motor electro-hydraulic servo system parameters change on its performance, the design method of backstepping adaptive controller is put forward. The mathematical model of electro-hydraulic servo system of continuous rotary motor is established, and the whole system is decomposed into several lower order subsystems, and the virtual control signal is designed for each subsystem from the final subsystem with motor angular displacement to the subsystem with system control input voltage. Based on Lyapunov method and the backstepping theory, an adaptive backstepping controller is designed with the changed parameters adaptive law. It is proved that the system reaches the global asymptotic stability, and the system tracking error asymptotically tends to zero. The simulation results show that the backstepping adaptive controller based on the adaptive law of the changed parameters can improve the performance of continuous rotary motor, and the proposed control strategy is feasible.
Lehnert, J.; Hövel, P.; Flunkert, V.; Guzenko, P. Yu.; Fradkov, A. L.; Schöll, E.
We demonstrate that time-delayed feedback control can be improved by adaptively tuning the feedback gain. This adaptive controller is applied to the stabilization of an unstable fixed point and an unstable periodic orbit embedded in a chaotic attractor. The adaptation algorithm is constructed using the speed-gradient method of control theory. Our computer simulations show that the adaptation algorithm can find an appropriate value of the feedback gain for single and multiple delays. Furthermore, we show that our method is robust to noise and different initial conditions.
Full Text Available The present paper addresses an attitude tracking control problem of a ducted fan microaerial vehicle. The proposed indirect adaptive controller can greatly reduce tracking error in the initial stage of the adaptive learning process by using an error compensation strategy and can achieve good capability to eliminate the adverse effect of measurement noises on the convergence of adjustable parameters. Moreover, the learning rate adaptation strategy is proposed to further minimize the adverse effect of large learning rates on the convergence of adjustable parameters. The experimental tests have illustrated the effectiveness of the proposed adaptive controller.
ZHANG Dong-yan; LIU Ya-qiu; CAO Jun
The paper presents a method of using single neuron adaptive PID control for adjusting system or servo system to implement timber drying process control, which combines the thought of parameter adaptive PID control and the character of neural network on exactly describing nonlinear and uncertainty dynamic process organically. The method implements functions of adaptive and self-learning by adjusting weighting parameters. Adaptive neural network can make some output trail given hoping value to decouple in static state. The simulation result indicates the validity, veracity and robustness of the method used in the timber drying process
This paper presents an improved observer-based indirect adaptive fuzzy control scheme for multiinput-multioutput (MIMO) nonlinear time-delay systems.The control scheme synthesizes adaptive fuzzy control with adaptive fuzzy identification.An observer is designed to observe the system state,and an identifier is developed to identify the unknown parts of the system.The update laws for parameters utilize two types of errors in the adaptive time-delay fuzzy logic systems,the observation error and the identificat...
Edwards, Christopher; Shtessel, Yuri
In this paper, a super-twisting-like structure with adaptive gains is proposed. The structure is parameterised by two scalar gains, both of which adapt, and by an additional time-varying term. The magnitudes of the adaptive terms are allowed to both increase and decrease as appropriate so that they are as small as possible, in the sense that they do not unnecessarily over-bound the uncertainty, and yet are large enough to sustain a sliding motion. In the paper, a new time varying gain is incorporated into the traditional super-twisting architecture. The proposed adaption law has a dual-layer structure which is formally analyzed using Lyapunov techniques. The additional term has the effect of simplifying the stability analysis whilst guaranteeing the second-order sliding mode properties of the traditional super-twisting scheme.
Rinderle, S.B.; Reichert, M.U.; Spaccapietra, S.
For several reasons enterprises are frequently subject to organizational change. Respective adaptations may concern business processes, but also other components of an enterprise architecture. In particular, changes of organizational structures often become necessary. The information about organizat
Milan Manojle Šunjevarić
Full Text Available In this paper, an overview of the algorithms for access control in mobile wireless networks is presented. A review of adaptive control methods of accepting a call in WCDMA networks is discussed, based on the overview of the algorithms used for this purpose, and their comparison. Appropriate comments and conculsions in comparison with the basic characteristics of these algorithms are given. The OVSF codes are explained as well as how the allocation method influences the capacity and probability of blocking.. Introduction We are witnessing a steady increase in the number of demands placed upon modern wireless networks. New applications and an increasing number of users as well as user activities growth in recent years reinforce the need for an efficient use of the spectrum and its proper distribution among different applications and classes of services. Besides humans, the last few years saw different computers, machines, applications, and, in the future, many other devices, RFID applications, and finally networked objects, as a new kind of wireless networks "users". Because of the exceptional rise in the number of users, the demands placed upon modern wireless networks are becoming larger, and spectrum management plays an important role. For these reasons, choosing an appropriate call admission control algorithm is of great importance. Multiple access and resource management in wireless networks Radio resource management of mobile networks is a set of algorithms to manage the use of radio resources with the aim is to maximize the total capacity of wireless systems with equal distribution of resources to users. Management of radio resources in cellular networks is usually located in the base station controller, the base station and the mobile terminal, and is based on decisions made on appropriate measurement and feedback. It is often defined as the maximum volume of traffic load that the system can provide for some of the requirements for the
Dalia Kass Hanna
Full Text Available This paper presents a newly developed approach for Differential Drive Mobile Robot (DDMR. The main goal is to provide a high dynamic system response in the joint space level, the low level control, as well as to enhance the DDMR localization. The proposed approach depends on a Linear Quadratic Regulator (LQR for the low level control and an Adaptive LQR for the high level control. The investigated DDMR is considered highly nonlinear system due to uncertainty exhibited by the mobile robot incorporated with actuators nonlinearity. DDMR’s uncertainty leads to erroneous localization. An Extended Kalman Filter (EKF -based approach with fusion sensors is used to enhance the robot degree of belief for its posture. Intensive simulation results obtained from the developed uncertain model and the proposed approach have shown very good dynamic performance on the low level control and very good convergence to the desired posture of the mobile robot path with the presence of robot uncertainty.
Full Text Available Low Frequency Oscillations (LFO occur inpower systems because of lack of the damping torque inorder to dominance to power system disturbances aschange in mechanical input power. In the recent pastPower System Stabilizer (PSS was used to damp LFO.FACTs devices, such as Unified Power Flow Controller(UPFC, can control power flow and increase transientstability. So UPFC may be used to damp LFO instead ofPSS. UPFC damps LFO through direct control of voltageand power. In this research the linearized model ofsynchronous machine (Heffron-Philips connected toinfinite bus (Single Machine-Infinite Bus: SMIB withUPFC is used and also in order to damp LFO, adaptiveANN damping controller for UPFC is designed andsimulated. Simulation is performed for various types ofloads and for different disturbances. Simulation resultsdemonstrate that the developed ANN damping controllerwould be more effective in damping electromechanicaloscillations in comparison with the conventional lead-lagcontroller.
Full Text Available Adaptive control of the time-delay systems is presented in the paper. Despite the use of MRAC based design, only the model following (not perfect model following is considered. The methods of a classical MRAC design are preserved to the maximum extent which allows further extensions of the algorithm such as the robust adaptive control modifications. The adaptive algorithm effectiveness is presented by means of illustrative examples.
This paper attempts to study a optimal adaptive con tr ol problem using game theory, and proposes an important practical result that an adaptive processes is a set of sufficient conditions under which pure strategy is essentially complete, and thus the fact that yield a very useful desirable pu re optimal control rule.Optimal Adaptive Control of a Class of Stochastic Systems Using Game Theory
Li Huiguang; Zhang Xinying; Guan Xinping
The synchronization problem under two cases is considered. One is that the bound on the uncertainty existing in the controller is known, the other is that the bound is unknown. In the latter case, the simple adaptation laws for upper bound on the norm of the uncertainty is proposed. Using this adaptive upper bound, a variable structure control is designed. The proposed method does not guarantee the convergence of the adaptive upper bound to the real one but makes the system asymptotically stable.
Cao, Chengyu (Inventor); Hovakimyan, Naira (Inventor); Xargay, Enric (Inventor)
Systems and methods of adaptive control for uncertain nonlinear multi-input multi-output systems in the presence of significant unmatched uncertainty with assured performance are provided. The need for gain-scheduling is eliminated through the use of bandwidth-limited (low-pass) filtering in the control channel, which appropriately attenuates the high frequencies typically appearing in fast adaptation situations and preserves the robustness margins in the presence of fast adaptation.
Xie, Haibo; Liu, Zhibin; Yang, Huayong
Most current studies about shield tunneling machine focus on the construction safety and tunnel structure stability during the excavation. Behaviors of the machine itself are also studied, like some tracking control of the machine. Yet, few works concern about the hydraulic components, especially the pressure and flow rate regulation components. This research focuses on pressure control strategies by using proportional pressure relief valve, which is widely applied on typical shield tunneling machines. Modeling of a commercial pressure relief valve is done. The modeling centers on the main valve, because the dynamic performance is determined by the main valve. To validate such modeling, a frequency-experiment result of the pressure relief valve, whose bandwidth is about 3 Hz, is presented as comparison. The modeling and the frequency experimental result show that it is reasonable to regard the pressure relief valve as a second-order system with two low corner frequencies. PID control, dead band compensation control and adaptive robust control (ARC) are proposed and simulation results are presented. For the ARC, implements by using first order approximation and second order approximation are presented. The simulation results show that the second order approximation implement with ARC can track 4 Hz sine signal very well, and the two ARC simulation errors are within 0.2 MPa. Finally, experiment results of dead band compensation control and adaptive robust control are given. The results show that dead band compensation had about 30° phase lag and about 20% off of the amplitude attenuation. ARC is tracking with little phase lag and almost no amplitude attenuation. In this research, ARC has been tested on a pressure relief valve. It is able to improve the valve's dynamic performances greatly, and it is capable of the pressure control of shield machine excavation.
Heydari, Ali; Balakrishnan, Sivasubramanya N
To synthesize fixed-final-time control-constrained optimal controllers for discrete-time nonlinear control-affine systems, a single neural network (NN)-based controller called the Finite-horizon Single Network Adaptive Critic is developed in this paper. Inputs to the NN are the current system states and the time-to-go, and the network outputs are the costates that are used to compute optimal feedback control. Control constraints are handled through a nonquadratic cost function. Convergence proofs of: 1) the reinforcement learning-based training method to the optimal solution; 2) the training error; and 3) the network weights are provided. The resulting controller is shown to solve the associated time-varying Hamilton-Jacobi-Bellman equation and provide the fixed-final-time optimal solution. Performance of the new synthesis technique is demonstrated through different examples including an attitude control problem wherein a rigid spacecraft performs a finite-time attitude maneuver subject to control bounds. The new formulation has great potential for implementation since it consists of only one NN with single set of weights and it provides comprehensive feedback solutions online, though it is trained offline.
Sørensen, Kim L.; Galeazzi, Roberto; Odgaard, Peter F.;
This paper tackles the problem of power regulation for wind turbines operating in the top region by an adaptive passivity based individual pitch control strategy. An adaptive nonlinear controller that ensures passivity of the mapping aerodynamic torque-regulation error is proposed, where the incl...
Di Canio, Giuliano; Stoyanov, Stoyan; Larsen, Jørgen Christian;
also apply adaptive neural control, based on a central pattern generator (CPG) circuit with synaptic plasticity, to autonomously generate a proper stepping frequency of the leg. The controller can also adapt the leg movement to deal with external perturbations within a few steps....
Bhattarai, Bishnu Prasad; Mendaza, Iker Diaz de Cerio; Bak-Jensen, Birgitte;
, such as electric vehicles, electric water heaters (EWHs) etc. An adaptive control using only local measurements for the EWHs and PVs is proposed in this study to alleviate OV as well as UV issues. The adaptive control is designed such that it monitors the voltage at the point of connection and adjusts active...
National Aeronautics and Space Administration — The proposed research focuses on the development of a new adaptive control methodology for active control of wing aerodynamic shape to effect distributed...
Full Text Available Initially a North Atlantic project, the CARINA carbon synthesis was extended to include the Southern Ocean. Carbon and relevant hydrographic and geochemical ancillary data from cruises all across the Arctic Mediterranean Seas, Atlantic and Southern Ocean were released to the public and merged into a new database as part of the CARINA synthesis effort. Of a total of 188 cruises, 37 cruises are part of the Southern Ocean, including 11 from the Atlantic sector. The variables from all Southern Ocean cruises, including dissolved inorganic carbon (TCO2, total alkalinity, oxygen, nitrate, phosphate and silicate, were examined for cruise-to-cruise consistency in one collective effort. Seawater pH and chlorofluorocarbons (CFCs are also part of the database, but the pH quality control (QC is described in another Earth System Science Data publication, while the complexity of the Southern Ocean physics and biogeochemistry prevented a proper QC analysis of the CFCs. The area-specific procedures of quality control, including crossover analysis between stations and inversion analysis of all crossover data (i.e. secondary QC, are briefly described here for the Atlantic sector of the Southern Ocean. Data from an existing, quality controlled database (GLODAP were used as a reference for our computations – however, the reference data were included into the analysis without applying the recommended GLODAP adjustments so the corrections could be independently verified. The outcome of this effort is an internally consistent, high-quality carbon data set for all cruises, including the reference cruises. The suggested corrections by the inversion analysis were allowed to vary within a fixed envelope, thus accounting for natural variability. The percentage of cruises adjusted ranged from 31% (for nitrate to 54% (for phosphate depending on the variable.
Presents a one-grade adaptive controller with one reference model which is built according to δ MRACS adaptive control theorv and used to control an actual high-order hydraulic system, and the whole hard ware system used, which includes a AT89C51 single chip microcomputer, 74Ls373 flip-latch, 6116 store, eight-bit ADC0809, and so on, and the satisfactory results obtained in study on hydraulic control system.
Lu LU; Fagui LIU; Weixiang SHI
In this paper, a novel control law is presented, which uses neural-network techniques to approximate the affine class nonlinear system having unknown or uncertain dynamics and noise disturbances. It adopts an adaptive control law to adjust the network parameters online and adds another control component according to H-infinity control theory to attenuate the disturbance. This control law is applied to the position tracking control of pneumatic servo systems. Simulation and experimental results show that the tracking precision and convergence speed is obviously superior to the results by using the basic BP-network controller and self-tuning adaptive controller.
Balas, Mark; Frost, Susan
Flexible structures containing a large number of modes can benefit from adaptive control techniques which are well suited to applications that have unknown modeling parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend our adaptive control theory to accommodate troublesome modal subsystems of a plant that might inhibit the adaptive controller. In some cases the plant does not satisfy the requirements of Almost Strict Positive Realness. Instead, there maybe be a modal subsystem that inhibits this property. This section will present new results for our adaptive control theory. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for the troublesome modal subsystem, or the Q modes. Here we present the theory for adaptive controllers modified by RMFs, with attention to the issue of disturbances propagating through the Q modes. We apply the theoretical results to a flexible structure example to illustrate the behavior with and without the residual mode filter.
Barkana, Itzhak, E-mail: email@example.com [BARKANA Consulting, Ramat Hasharon (Israel)
Although various adaptive control techniques have been around for a long time and in spite of successful proofs of stability and even successful demonstrations of performance, the eventual use of adaptive control methodologies in practical real world systems has met a rather strong resistance from practitioners and has remained limited. Apparently, it is difficult to guarantee or even understand the conditions that can guarantee stable operations of adaptive control systems under realistic operational environments. Besides, it is difficult to measure the robustness of adaptive control system stability and allow it to be compared with the common and widely used measure of phase margin and gain margin that is utilized by present, mainly LTI, controllers. Furthermore, customary stability analysis methods seem to imply that the mere stability of adaptive systems may be adversely affected by any tiny deviation from the pretty idealistic and assumably required stability conditions. This paper first revisits the fundamental qualities of customary direct adaptive control methodologies, in particular the classical Model Reference Adaptive Control, and shows that some of their basic drawbacks have been addressed and eliminated within the so-called Simple Adaptive Control methodology. Moreover, recent developments in the stability analysis methods of nonlinear systems show that prior conditions that were customarily assumed to be needed for stability are only apparent and can be eliminated. As a result, sufficient conditions that guarantee stability are clearly stated and lead to similarly clear proofs of stability. As many real-world applications show, once robust stability of the adaptive systems can be guaranteed, the added value of using Add-On Adaptive Control along with classical Control design techniques is pushing the desired performance beyond any previous limits.
Although various adaptive control techniques have been around for a long time and in spite of successful proofs of stability and even successful demonstrations of performance, the eventual use of adaptive control methodologies in practical real world systems has met a rather strong resistance from practitioners and has remained limited. Apparently, it is difficult to guarantee or even understand the conditions that can guarantee stable operations of adaptive control systems under realistic operational environments. Besides, it is difficult to measure the robustness of adaptive control system stability and allow it to be compared with the common and widely used measure of phase margin and gain margin that is utilized by present, mainly LTI, controllers. Furthermore, customary stability analysis methods seem to imply that the mere stability of adaptive systems may be adversely affected by any tiny deviation from the pretty idealistic and assumably required stability conditions. This paper first revisits the fundamental qualities of customary direct adaptive control methodologies, in particular the classical Model Reference Adaptive Control, and shows that some of their basic drawbacks have been addressed and eliminated within the so-called Simple Adaptive Control methodology. Moreover, recent developments in the stability analysis methods of nonlinear systems show that prior conditions that were customarily assumed to be needed for stability are only apparent and can be eliminated. As a result, sufficient conditions that guarantee stability are clearly stated and lead to similarly clear proofs of stability. As many real-world applications show, once robust stability of the adaptive systems can be guaranteed, the added value of using Add-On Adaptive Control along with classical Control design techniques is pushing the desired performance beyond any previous limits
Ben Youssef, C.; Dahhou, B.; Roux, G. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Rols, J.L. [Institut National des Sciences Appliquees (INSA), 31 - Toulouse (France)
Controlling the process of a fixed bed bioreactor imply solving filtering and adaptative control problems. Estimation processes have been developed for unmeasurable parameters. An adaptative non linear control has been built, instead of conventional approaches trying to linearize the system and apply a linear control system. (D.L.) 10 refs.
Lin, Tsung-Chih, E-mail: firstname.lastname@example.org [Department of Electronic Engineering, Feng-Chia University, Taichung, Taiwan (China); Lee, Tun-Yuan [Department of Electronic Engineering, Feng-Chia University, Taichung, Taiwan (China); Balas, Valentina E. [Aurel Vlaicu University of Arad, B-dul Revolutiei 77, 310130 Arad (Romania)
Highlights: > We study uncertain fractional order chaotic systems synchronization. > Lyapunov synthesis is used to derive control law and adaptive laws. > Based on sliding mode control, chattering phenomena in the control effort can be reduced. - Abstract: This paper deals with chaos synchronization between two different uncertain fractional order chaotic systems based on adaptive fuzzy sliding mode control (AFSMC). With the definition of fractional derivatives and integrals, a fuzzy Lyapunov synthesis approach is proposed to tune free parameters of the adaptive fuzzy controller on line by output feedback control law and adaptive law. Moreover, chattering phenomena in the control efforts can be reduced. The sliding mode design procedure not only guarantees the stability and robustness of the proposed AFSMC, but also the external disturbance on the synchronization error can be attenuated. The simulation example is included to confirm validity and synchronization performance of the advocated design methodology.
Full Text Available Divisive normalization in primary visual cortex has been linked to adaptation to natural image statistics in accordance to Barlow's redundancy reduction hypothesis. Using recent advances in natural image modeling, we show that the previously studied static model of divisive normalization is rather inefficient in reducing local contrast correlations, but that a simple temporal contrast adaptation mechanism of the half-saturation constant can substantially increase its efficiency. Our findings reveal the experimentally observed temporal dynamics of divisive normalization to be critical for redundancy reduction.
JIA Li; GE Shu-zhi; QIU Ming-sen
An adaptive neuro-fuzzy control is investigated for a class of noa-affine nonlinear systems.To do so,rigorous description and quantification of the approximation error of the neuro-fuzzy controller are firstly discussed.Applying this result and Lyapunov stability theory,a novel updating algorithm to adapt the weights,centers,and widths of the neuro-fuzzy controller is presented.Consequently,the proposed design method is able to guaranteg the stability of the closed-loop system and the convergence of the tracking error.Simulation results illustrate the effectiveness of the proposed adaptive neuro-fuzzy control scheme.
A discrete model reference adaptive controller of robot arm is obtained by integrating the reduced dynamic model of robot, model reference adaptive control (MRAC) and digital signal processing (DSP) computer system into an electromechanical system. With the DSP computer system, the control signal of each joint of the robot arm can be processed in real time and independently. The simulation and experiment results show that with the control strategy, the robot achieved a good trajectory following precision, a good decoupling performance and a high real-time adaptivity.
Full Text Available There is a belief that complexity and chaos are essential for adaptability. But life deals with complexity every moment, without the chaos that engineers fear so, by invoking goal-directed behaviour. Goals can be programmed. That is why living organisms give us hope to achieve adaptability in robots. In this paper a method for the description of a goal-directed, or programmed, behaviour, interacting with uncertainty of environment, is described. We suggest reducing the structural (goals, intentions and stochastic components (probability to realise the goal of individual behaviour to random variables with nominal values to apply probabilistic approach. This allowed us to use a Normalized Entropy Index to detect the system state by estimating the contribution of each agent to the group behaviour. The number of possible group states is 27. We argue that adaptation has a limited number of possible paths between these 27 states. Paths and states can be programmed so that after adjustment to any particular case of task and conditions, adaptability will never involve chaos. We suggest the application of the model to operation of robots or other devices in remote and/or dangerous places.
Sampson, J. N.
The Lasso shrinkage procedure achieved its popularity, in part, by its tendency to shrink estimated coefficients to zero, and its ability to serve as a variable selection procedure. Using data-adaptive weights, the adaptive Lasso modified the original procedure to increase the penalty terms for those variables estimated to be less important by ordinary least squares. Although this modified procedure attained the oracle properties, the resulting models tend to include a large number of "false positives" in practice. Here, we adapt the concept of local false discovery rates (lFDRs) so that it applies to the sequence, λn, of smoothing parameters for the adaptive Lasso. We define the lFDR for a given λn to be the probability that the variable added to the model by decreasing λn to λn-δ is not associated with the outcome, where δ is a small value. We derive the relationship between the lFDR and λn, show lFDR =1 for traditional smoothing parameters, and show how to select λn so as to achieve a desired lFDR. We compare the smoothing parameters chosen to achieve a specified lFDR and those chosen to achieve the oracle properties, as well as their resulting estimates for model coefficients, with both simulation and an example from a genetic study of prostate specific antigen.
Hamanaka, M.; Yamada, K.
Online character recognition which can adapt to handwriting quality is proposed. In character recognition, it is difficult to recognize both clearly and roughly written characters accurately. For Japanese characters, the number of strokes is often slightly varied when characters are written roughly
Adaptive optics (AO) is a technique to actively correct the wavefront distortions introduced in a light beam as it propagates through a turbulent medium. Nowadays, it is commonly applied in ground-based telescopes to counteract the devastating effect of atmospheric turbulence. This thesis focuses on
Full Text Available Abstract: An adaptive PID controller is used to control of a two degrees of freedom under actuated manipulator. An actor-critic based reinforcement learning is employed for tuning of parameters of the adaptive PID controller. Reinforcement learning is an unsupervised scheme wherein no reference exists to which convergence of algorithm is anticipated. Thus, it is appropriate for real time applications. Controller structure and learning equations as well as update rules are provided. Simulations are performed in SIMULINK and performance of the controller is compared with NARMA-L2 controller. The results verified good performance of the controller in tracking and disturbance rejection tests.
Full Text Available This paper investigates the distributed consensus-based robust adaptive formation control for nonholonomic mobile robots with partially known dynamics. Firstly, multirobot formation control problem has been converted into a state consensus problem. Secondly, the practical control strategies, which incorporate the distributed kinematic controllers and the robust adaptive torque controllers, are designed for solving the formation control problem. Thirdly, the specified reference trajectory for the geometric centroid of the formation is assumed as the trajectory of a virtual leader, whose information is available to only a subset of the followers. Finally, numerical results are provided to illustrate the effectiveness of the proposed control approaches.
Qin Yong; Zang Xizhe; Wang Xiaoyu; Li Tian; Zhao Jie
Wheeled mobile robot is one of the well-known nonholonomic systems. A two-wheeled self-balance robot is taken as the research objective. This paper carried out a detailed force analysis of the robot and established a non-linear dynamics model. An adaptive tracking controller for the kinematic model of a nonholonomic mobile robot with unknown parameters is also proposed. Using control Lyapunov function (CLF), the controller's global asymptotic stability has been proven. The adaptive trajectory tracking controller decreases the disturbance in the course of tracking control and enhances the real-time control characteristics. The simulation result indicated that the wheeled mobile robot tracking can be effectively controlled.
Ghasemi-Nejhad, Mehrdad N.
This paper presents design of smart composite platforms for adaptive trust vector control (TVC) and adaptive laser telescope for satellite applications. To eliminate disturbances, the proposed adaptive TVC and telescope systems will be mounted on two analogous smart composite platform with simultaneous precision positioning (pointing) and vibration suppression (stabilizing), SPPVS, with micro-radian pointing resolution, and then mounted on a satellite in two different locations. The adaptive TVC system provides SPPVS with large tip-tilt to potentially eliminate the gimbals systems. The smart composite telescope will be mounted on a smart composite platform with SPPVS and then mounted on a satellite. The laser communication is intended for the Geosynchronous orbit. The high degree of directionality increases the security of the laser communication signal (as opposed to a diffused RF signal), but also requires sophisticated subsystems for transmission and acquisition. The shorter wavelength of the optical spectrum increases the data transmission rates, but laser systems require large amounts of power, which increases the mass and complexity of the supporting systems. In addition, the laser communication on the Geosynchronous orbit requires an accurate platform with SPPVS capabilities. Therefore, this work also addresses the design of an active composite platform to be used to simultaneously point and stabilize an intersatellite laser communication telescope with micro-radian pointing resolution. The telescope is a Cassegrain receiver that employs two mirrors, one convex (primary) and the other concave (secondary). The distance, as well as the horizontal and axial alignment of the mirrors, must be precisely maintained or else the optical properties of the system will be severely degraded. The alignment will also have to be maintained during thruster firings, which will require vibration suppression capabilities of the system as well. The innovative platform has been
Full Text Available In this paper, a neural network adaptive sliding mode control is proposed for an MEMS triaxial gyroscope with unknown system nonlinearities. An input‐output linearization technique is incorporated into the neural adaptive tracking control to cancel the nonlinearities, and the neural network whose parameters are updated from the Lyapunov approach is used to perform the linearization control law. The sliding mode control is utilized to\tcompensate the neural network’s approximation errors. The stability of the closed‐loop system can be guaranteed with the proposed adaptive neural sliding mode control. Numerical simulations are investigated to verify the effectiveness of the proposed adaptive neural sliding mode control scheme.
Frost, Susan A.; Balas, Mark J.; Wright, Alan D.
Adaptive control techniques are well suited to nonlinear applications, such as wind turbines, which are difficult to accurately model and which have effects from poorly known operating environments. The turbulent and unpredictable conditions in which wind turbines operate create many challenges for their operation. In this paper, we design an adaptive collective pitch controller for a high-fidelity simulation of a utility scale, variable-speed horizontal axis wind turbine. The objective of the adaptive pitch controller in Region 3 is to regulate generator speed and reject step disturbances. The control objective is accomplished by collectively pitching the turbine blades. We use an extension of the Direct Model Reference Adaptive Control (DMRAC) approach to track a reference point and to reject persistent disturbances. The turbine simulation models the Controls Advanced Research Turbine (CART) of the National Renewable Energy Laboratory in Golden, Colorado. The CART is a utility-scale wind turbine which has a well-developed and extensively verified simulator. The adaptive collective pitch controller for Region 3 was compared in simulations with a bas celliansesical Proportional Integrator (PI) collective pitch controller. In the simulations, the adaptive pitch controller showed improved speed regulation in Region 3 when compared with the baseline PI pitch controller and it demonstrated robustness to modeling errors.
Guo, Qing; Sun, Ping; Yin, Jing-Min; Yu, Tian; Jiang, Dan
Some unknown parameter estimation of electro-hydraulic system (EHS) should be considered in hydraulic controller design due to many parameter uncertainties in practice. In this study, a parametric adaptive backstepping control method is proposed to improve the dynamic behavior of EHS under parametric uncertainties and unknown disturbance (i.e., hydraulic parameters and external load). The unknown parameters of EHS model are estimated by the parametric adaptive estimation law. Then the recursive backstepping controller is designed by Lyapunov technique to realize the displacement control of EHS. To avoid explosion of virtual control in traditional backstepping, a decayed memory filter is presented to re-estimate the virtual control and the dynamic external load. The effectiveness of the proposed controller has been demonstrated by comparison with the controller without adaptive and filter estimation. The comparative experimental results in critical working conditions indicate the proposed approach can achieve better dynamic performance on the motion control of Two-DOF robotic arm.
Guo, Qing; Sun, Ping; Yin, Jing-Min; Yu, Tian; Jiang, Dan
Some unknown parameter estimation of electro-hydraulic system (EHS) should be considered in hydraulic controller design due to many parameter uncertainties in practice. In this study, a parametric adaptive backstepping control method is proposed to improve the dynamic behavior of EHS under parametric uncertainties and unknown disturbance (i.e., hydraulic parameters and external load). The unknown parameters of EHS model are estimated by the parametric adaptive estimation law. Then the recursive backstepping controller is designed by Lyapunov technique to realize the displacement control of EHS. To avoid explosion of virtual control in traditional backstepping, a decayed memory filter is presented to re-estimate the virtual control and the dynamic external load. The effectiveness of the proposed controller has been demonstrated by comparison with the controller without adaptive and filter estimation. The comparative experimental results in critical working conditions indicate the proposed approach can achieve better dynamic performance on the motion control of Two-DOF robotic arm. PMID:26920086
Yu Hai-Tao; Wang Jiang; Deng Bin; Wei Xi-Le; Chen Ying-Yuan
In this paper we present a combined algorithm for the synchronization control of two gap junction coupled chaotic FitzHugh-Nagumo (FHN) neurons in an external electrical stimulation.The controller consists of a combination of dynamical sliding mode control and adaptive backstepping control.The combined algorithm yields an adaptive dynamical sliding mode control law which has the advantage over static sliding mode-based controllers of being chattering-free,i.e.,a sufficiently smooth control input signal is generated.It is shown that the proposed control scheme can not only compensate for the system uncertainty,but also guarantee the stability of the synchronized error system.In addition,numerical simulations are also performed to demonstrate the effectiveness of the proposed adaptive controller.
Full Text Available An adaptive global sliding mode control (AGSMC using RBF neural network (RBFNN is proposed for the system identification and tracking control of micro-electro-mechanical system (MEMS gyroscope. Firstly, a new kind of adaptive identification method based on the global sliding mode controller is designed to update and estimate angular velocity and other system parameters of MEMS gyroscope online. Moreover, the output of adaptive neural network control is used to adjust the switch gain of sliding mode control dynamically to approach the upper bound of unknown disturbances. In this way, the switch item of sliding mode control can be converted to the output of continuous neural network which can weaken the chattering in the sliding mode control in contrast to the conventional fixed gain sliding mode control. Simulation results show that the designed control system can get satisfactory tracking performance and effective estimation of unknown parameters of MEMS gyroscope.
R.R. Joshi; R.A. Gupta; A.K. Wadhwani
A systematic controller design and implementation for a matrix-converter-based induction motor drive system is proposed. A nonlinear adaptive backstepping controller is proposed to improve the speed and position responses of the induction motor system. By using the proposed adaptive backstepping controller, the system can track a time-varying speed command and a time-varying position command well. Moreover, the system has a good load disturbance rejection capability. The realization of the co...
Qing ZHU; Shumin FEI; Tao Li; Tianping ZHANG
In this paper,a robust adaptive control scheme is proposed for the stabilization of uncertain linear systems with discrete and distributed delays and bounded peturbaturbations.The uncertainty is assumed to be an unknown continuous function with norm-bounded restriction.The perturbation is sector-bounded.Combining with the liner matrix inequality method,neural networks and adaptive control,the control scheme ensures the exponential stability of the closed-loop system for any admissible uncertainty.
Virden, D.; Wagg, D.J.
A single degree of freedom mechanical spring-mass system was considered where the motion of the mass is constrained by an adjustable rigid impact stop. A model reference adaptive control algorithm combined with interspike interval techniques was used to consider the viability of identifying system parameters when impacts are present. The unmodified adaptive control algorithm destabilizes during vibro-impact motion, so three modified control algorithms were tested experimentally. The first, th...
Full Text Available The attitude tracking problem of spacecraft in the presence of unknown disturbance is investigated. By using the adaptive control technique and the Lyapunov stability theory, a chattering-free adaptive sliding mode control law is proposed for the attitude tracking problem of spacecraft with unknown disturbance. Simulation results are employed to demonstrate the effectiveness of the proposed control design technique in this paper.
The School of Electrical, Electronic and Computer Engineering at the North-West University in Potchefstroom has established an active magnetic bearing (AMB) research group called McTronX. This group provides extensive knowledge and experience in the theory and application of AMBs. By making use of the expertise contained within McTronX and the rest of the control engineering community, an adaptive controller for an AMB flywheel system is implemented. The adaptive controller is ...
CHENG Shi-lun; YANG Zhen
To maximize throughput and to satisfy users' requirements in cognitive radios, a cross-layer optimization problem combining adaptive modulation and power control at the physical layer and truncated automatic repeat request at the medium access control layer is proposed. Simulation results show the combination of power control, adaptive modulation, and truncated automatic repeat request can regulate transmitter powers and increase the total throughput effectively.
Full Text Available Sea-skim~ing cruise missiles pose the greatest threat to a surface ship in the present-day war scenario. The convenitional close-in-weapon-systems (CIWSs are becoming less reliable against these new challenges requiring extremely fast reaction time. Naval Forces see a high energy laser as a feasible andjeffective directed energy weapon against sea-skimming antiship cruise missiles becauseof its .ability to deliver destructive energy at the speed of light on to a distant target. The paper comparesthe technology and capability of deuterium fluoride (DF and chemical-oxygen-iodine laser (COIL in effectively performing the role of a shipborne CIWS altainst sea-skimming missiles. Out of these twolasers, it is argued that DF laser wo.uld be more effective a,s a shipborne weapon for defence against sea-skimmin,g cruise missiles. Besides the high energy laser as the primary (killing laser, othersub-systems required in the complete weapon system would be: A beacon laser to sense phase distor'ions in the primary laser, adaptive optics to compensate the atmospheric distortions, beam-directing optics, illuminating lasers, IRST sensors, surveillance and tracking radars, interfacing system, etc.
Athans, M.; Willner, D.
A flight control system design is presented, that can be implemented by analog hardware, to be used to control an aircraft with uncertain parameters. The design is based upon the use of modern control theory. The ideas are illustrated by considering control of STOL longitudinal dynamics.
WANG Xin; YANG Hui; ZHENG YiHui
In this paper, a multivariable direct adaptive controller using multiple models without minimum phase assumption is presented to improve the transient response when the parameters of the system jump abruptly. The controller is composed of multiple fixed controller models, a free-running adaptive controller model and a re-initialized adaptive controller model. The fixed controller models are derived from the corresponding fixed system models directly. The adaptive controller models adopt the direct adaptive algorithm to reduce the design calculation. At every instant, the optimal controller is chosen out according to the switching index. The interaction of the system is viewed as the measured disturbance which is eliminated by the choice of the weighing polynomial matrix. The global convergence is obtained. Finally, several simulation examples in a wind tunnel experiment are given to show both effectiveness and practicality of the proposed method. The significance of the proposed method is that it is applicable to a non-minimum phase system, adopting direct adaptive algorithm to overcome the singularity problem during the matrix calculation and realizing decoupling control for a multivariable system.
Gardan, Julien; DANESI, Frédéric; Roucoules, Lionel; Schneider, A
This article presents the development of a 3D printing device for the additive manufacturing adapted to a CNC machining. The application involves the integration of a specific printing head. Additive manufacturing technology is most commonly used for modeling, prototyping, tooling through an exclusive machine or 3D printer. A global review and analysis of technologies show the additive manufacturing presents little independent solutions . The problem studied especially the additive manu...
Animals move through a complex environment and therefore constantly need to adapt their behavior to the surroundings. For this purpose, they use sensory information of various kind. As one strategy to gain tactile cues, animals perform leg searching movements when loosing foothold. The kinematics of these searching movements have been well investigated in the stick insect. In this thesis, the modification of stick insect searching movements following a tactile cue are explored as an example o...
A recurrent theme in bacterial pathogenicity is the understanding of the regulatory events necessary for a given pathogen to progress through its infection cycle while resisting the host defense mechanisms. This progression typically requires the coordinated expression of defined sub-portions of the virulence repertoire at the same time as others need to be tightly repressed or degraded. This so-called adaptive response is ultimately linked to the ability of the pathogen to sense its direct e...
Highlights: • Photovoltaic generator dynamic resistance online estimation method is proposed. • Control method allowing to achieve nominal performance at all time is presented. • The method is suitable for any type of photovoltaic system. - Abstract: Nonlinear characteristics of photovoltaic generators were recently shown to significantly influence the dynamics of interfacing power stages. Moreover, since the dynamic resistance of photovoltaic generators is both operating point and environmental variables dependent, the combined dynamics exhibits these dependencies as well, burdening control challenge. Typically, linear time invariant input voltage loop controllers (e.g. Proportional-Integrative-Derivative) are utilized in photovoltaic applications, designed according to nominal operating conditions. Nevertheless, since actual dynamics is seldom nominal, closed loop performance of such systems varies as well. In this paper, adaptive control method is proposed, allowing to estimate photovoltaic generator resistance online and utilize it to modify the controller parameters such that closed loop performance remains nominal throughout the whole operation range. Unlike previously proposed method, utilizing double-grid-frequency component for estimation purposes and suffering from various drawbacks such as operation point dependence and applicability to single-phase grid connected systems only, the proposed method is based on harmonic current injection and is independent on operating point and system topology
Thenozhi, Suresh; Yu, Wen
Although fuzzy/adaptive sliding mode control can reduce the chattering problem in structural vibration control applications, they require the equivalent control and the upper bounds of the system uncertainties. In this paper, we used fuzzy logic to approximate the standard sliding surface and designed a dead-zone adaptive law for tuning the switching gain of the sliding mode control. The stability of the proposed controller is established using Lyapunov stability theory. A six-storey building prototype equipped with an active mass damper has been used to demonstrate the effectiveness of the proposed controller towards the wind-induced vibrations.
In this note, a robust adaptive control scheme is proposed for a class of nonlinear systems that have unknown multiplicative terms. Unlike previous results, except for the unknown control directions, we do not require a priori bounds on the unknown parameters. We also allow the unknown parameters to be time-varying provided that they are bounded. Our proposed robust adaptive controller is designed to identify on-line the unknown control directions and is a switching type controller, in which the controller parameters are tuned in a switching manner via a switching logic. Global stability of the closed-loop systems have been proved.
Fiacchini, Mirko; Alamo, Teodoro; Albea-Sanchez, Carolina; Fernandez Camacho, Eduardo
International audience In this paper, an adaptive control scheme for the safe operation of a fuel cell system is presented. The aim of the control design is to guarantee that the oxygen ratio do not reach dangerous values. A first level of control is given by a feedforward control. An improved behavior is obtained using an adaptive predictive controller to determine the voltage to be applied to the air compressor. An admissible robust control invariant set for the PWA model of the system i...
Wei GUAN; Guanghong YANG
This paper studies the problem of designing adaptive fault-tolerant H-infinity controllers for linear timeinvariant systems with actuator saturation. The disturbance tolerance ability of the closed-loop system is measured by an optimal index. The notion of an adaptive H-infinity performance index is proposed to describe the disturbance attenuation performances of closed-loop systems. New methods for designing indirect adaptive fault-tolerant controllers via state feedback are presented for actuator fault compensations. Based on the on-line estimation of eventual faults, the adaptive fault-tolerant controller parameters are updated automatically to compensate for the fault effects on systems. The designs are developed in the framework of the linear matrix inequality (LMI) approach, which can guarantee the disturbance tolerance ability and adaptive H-infinity performances of closed-loop systems in the cases of actuator saturation and actuator failures. An example is given to illustrate the efficiency of the design method.
Cai Guo-Liang; Zheng Song; Tian Li-Xin
This paper is involved with the adaptive control and synchronization problems for an uncertain new hyperchaotic Lorenz system. Based on the Lyapunov stability theory, the adaptive control law is derived such that the trajectory of hyperchaotic Lorenz system with unknown parameters can be globally stabilized to an unstable equilibrium point of the uncontrolled system. Furthermore, an adaptive control approach is presented to the synchronizations between two identical hyperchaotic systems, particularly between two different uncertain hyperchaotic systems. Numerical simulations show the effectiveness of the presented method.
Ying ZHOU; Yuqiang WU; Shumin FEI
A new adaptive control scheme is proposed for multivariable model reference adaptive control(MRAC) systems based on the nonlinear backstepping approach with vector form.The assumption on a priori knowledge of the high frequency gain matrix in existing results is relaxed and the new required condition for the high frequency gain matrix can be easily checked for certain plants so that the proposed method is widely applicable.This control scheme guarantees the global stability of the closed-loop systems and the tracking error can be arbitrary small.The simulation result for an application example shows the validity of the proposed nonlinear adaptive scheme.
Ho, Daniel W C; Li, Junmin; Niu, Yugang
In this paper, an adaptive neural controller for a class of time-delay nonlinear systems with unknown nonlinearities is proposed. Based on a wavelet neural network (WNN) online approximation model, a state feedback adaptive controller is obtained by constructing a novel integral-type Lyapunov-Krasovskii functional, which also efficiently overcomes the controller singularity problem. It is shown that the proposed method guarantees the semiglobal boundedness of all signals in the adaptive closed-loop systems. An example is provided to illustrate the application of the approach.
Wang Xingsong; Hong Henry; Su Chunyi
Adaptive control of a flexible beam system preceded by an unknown dead-zone in the driving motor is investigated in state space form. By introducing an important lemma for simplifying error equation between the flexible beam model and the matching reference model, a robust adaptive control scheme is developed by involving the dead-zone inverse terms. The new adaptive control law ensures global stability of the entire system and achieves desired tracking precision even when the slopes of the dead-zone are not equal. Simulations performed on a typical flexible beam system illustrate and clarify the validity of this approach.
Zhang Tianping; Mei Jiandong
The problem of direct adaptive neural network control for a class of large-scale systems with unknown function control gains and the high-order interconnections is studied in this paper. Based on the principle of sliding mode control and the approximation capability of multilayer neural networks, a design scheme of decentralized direct adaptive sliding mode controller is proposed. The plant dynamic uncertainty and modeling errors are adaptively compensated by adjusted the weights and sliding mode gains on-line for each subsystem using only local information. According to the Lyapunov method, the closed-loop adaptive control system is proven to be globally stable, with tracking errors converging to a neighborhood of zero. Simulation results demonstrate the effectiveness of the proposed approach.
Li, Yongming; Tong, Shaocheng
In this paper, a fuzzy adaptive switched control approach is proposed for a class of uncertain nonholonomic chained systems with input nonsmooth constraint. In the control design, an auxiliary dynamic system is designed to address the input nonsmooth constraint, and an adaptive switched control strategy is constructed to overcome the uncontrollability problem associated with x0(t0) = 0. By using fuzzy logic systems to tackle unknown nonlinear functions, a fuzzy adaptive control approach is explored based on the adaptive backstepping technique. By constructing the combination approximation technique and using Young's inequality scaling technique, the number of the online learning parameters is reduced to n and the 'explosion of complexity' problem is avoid. It is proved that the proposed method can guarantee that all variables of the closed-loop system converge to a small neighbourhood of zero. Two simulation examples are provided to illustrate the effectiveness of the proposed control approach.
Zongyao SUN; Yungang LIU
In this paper, a new approach is successfully addressed to design the state-feedback adaptive stabilizing control law for a class of high-order nonlinear systems in triangular form and with unknown and nonidentical control coefficients, whose stabilizing control has been investigated recently under the knowledge that the lower bounds of the control coefficients are exactly known. In the present paper,without any knowledge of the lower bounds of the control coefficients, based on the adaptive technique and appropriately choosing design parameters, we give the recursive design procedure of the stabilizing control law by utilizing the approach of adding a power integrator together with tuning functions. The state-feedback adaptive control law designed not only preserves the equilibrium at the origin, but also guarantees the global asymptotic stability of the closed-loop states and the uniform boundedness of all the other closed-loop signals.
FANGJin-qing; LUOXiao-shu; WENGJia-qiang; ZHULun-wu
Neural network has some advantages of adaptation, learn-self, self-organization and suitable for high-dimension for various applications in many fields, especially among them the feed-forward back-propagating neural network self-adaptation method is suitable for control of nonlinear systems.
This paper presents a robust model reference adaptive control scheme to deal with uncertain time delay in the dynamical model of a fluidized bed combustor for sewage sludge. The theoretical analysis and simulation results show that the proposed scheme can guarantee not only stability and robustness, but also the adaptive decoupling performance of the system.
Chen, Ching-Huei; Chang, Shu-Wei
The purpose of this study was to explore the effectiveness of adaptive assessment versus learner control in a multimedia learning system designed to help secondary students learn science. Unlike other systems, this paper presents a workflow of adaptive assessment following instructional materials that better align with learners' cognitive…
Emma D. Wilson
Full Text Available The adaptive filter model of the cerebellar microcircuit has been successfully applied to biological motor control problems such as the vestibulo-ocular reflex (VOR and to sensory processing problems such as the adaptive cancellation of reafferent noise. It has also been successfully applied to problems in robotics such as adaptive camera stabilisation and sensor noise cancellation. In previous applications to inverse control problems the algorithm was applied to the velocity control of a plant dominated by viscous and elastic elements. Naive application of the adaptive filter model to the displacement (as opposed to velocity control of this plant results in unstable learning and control. To be more generally useful in engineering problems it is essential to remove this restriction to enable the stable control of plants of any order. We address this problem here by developing a biohybrid model reference adaptive control (MRAC scheme, which stabilises the control algorithm for strictly proper plants. We evaluate the performance of this novel cerebellar inspired algorithm with MRAC scheme in the experimental control of a dielectric electroactive polymer, a class of artificial muscle. The results show that the augmented cerebellar algorithm is able to accurately control the displacement response of the artificial muscle. The proposed solution not only greatly extends the practical applicability of the cerebellar-inspired algorithm, but may also shed light on cerebellar involvement in a wider range of biological control tasks.
National Aeronautics and Space Administration — SSCI proposes to develop and test a framework referred to as the ADVANCE (Algorithm Design and Validation for Adaptive Nonlinear Control Enhancement), within which...
Van Katwijk, R.T.
The objective of this thesis is to create a distributed, multi-agent, approach to traffic control. This PhD thesis' focus is on the control of a network instrumented by traffic signals.A thorough literature study has been performed, reviewing the current state of the art in traffic signal control.
Gunev, Ihsan; Varol, Aydin; Karaman, Sertac; Basdogan, Cagatay
A new approach, called adaptive Q control, for tapping-mode atomic force microscopy (AFM) is introduced and implemented on a homemade AFM setup utilizing a laser Doppler vibrometer and a piezoactuated bimorph probe. In standard Q control, the effective Q factor of the scanning probe is adjusted prior to the scanning depending on the application. However, there is a trade-off in setting the effective Q factor of an AFM probe. The Q factor is either increased to reduce the tapping forces or decreased to increase the maximum achievable scan speed. Realizing these two benefits simultaneously using standard Q control is not possible. In adaptive Q control, the Q factor of the probe is set to an initial value as in standard Q control, but then modified on the fly during scanning when necessary to achieve this goal. In this article, we present the basic theory behind adaptive Q control, the electronics enabling the online modification of the probe's effective Q factor, and the results of the experiments comparing three different methods: scanning (a) without Q control, (b) with standard Q control, and (c) with adaptive Q control. The results show that the performance of adaptive Q control is superior to the other two methods.
Hosseini, S.H.; Etemadi, A.H. [Department of Electrical Engineering, Sharif University of Technology, Tehran (Iran)
Fixed gain controllers for automatic generation control are designed at nominal operating conditions and fail to provide best control performance over a wide range of operating conditions. So, to keep system performance near its optimum, it is desirable to track the operating conditions and use updated parameters to compute control gains. A control scheme based on artificial neuro-fuzzy inference system (ANFIS), which is trained by the results of off-line studies obtained using particle swarm optimization, is proposed in this paper to optimize and update control gains in real-time according to load variations. Also, frequency relaxation is implemented using ANFIS. The efficiency of the proposed method is demonstrated via simulations. Compliance of the proposed method with NERC control performance standard is verified. (author)