State feedback controller design of networked control systems

This paper is concerned with the controller design of networked control systems (NCS). A new model of the NCSs is provided under consideration of both the network-induced delay and the data packet dropout in the transmission. In terms of the given model, a controller design method is proposed based on a delay-dependent approach. The feedback gain of a memoryless controller and the maximum allowable value of the network-induced delay can be derived by solving a set of linear matrix inequalities. Two examples are given to show the effectiveness of our method.     

One-layer neural-network controller with preprocessed inputs for autonomous underwater vehicles

Navigating, guiding, and controlling autonomous underwater vehicles (AUVs) are challenging and difficult tasks compared to the autonomous surface-level operations. Controlling the motion of such vehicles require the estimation of unknown hydrodynamic forces and moments and disturbances acting on these vehicles in the underwater environment. In this paper, a one-layer neural-network (NN) controller with preprocessed input signals is designed to control the vehicle track along a desired trajectory, which is specified in terms of desired position and attitude. In the absence of unknown disturbances and modeling errors, it is shown that the tracking error system is asymptotically stable. In the presence of any bounded ocean currents or wave disturbances, the uniformly ultimately boundedness of the tracking error and NN weight estimates are given. The NN does not require an initial offline training phase and weight initialization is straightforward. Simulation results are shown by using a scaled version of the Naval Post-Graduate School's AUV. Results indicate the superior performance of the NN controller over conventional controllers. Providing offline NN training may improve the transient performance.     

Platform-based embedded software design and system integration for autonomous vehicles

Automatic control systems typically incorporate legacy code and components that were originally designed to operate independently. Furthermore, they operate under stringent safety and timing constraints. Current design strategies deal with these requirements and characteristics with ad hoc approaches. In particular, when designing control laws, implementation constraints are often ignored or cursorily estimated. Indeed, costly redesigns are needed after a prototype of the control system is built because of missed timing constraints and subtle transient errors. In this paper, we use the concepts of platform-based design to develop a methodology for the design of automatic control systems that builds in modularity and correct-by-construction procedures. We illustrate our strategy by describing the (successful) application of the methodology to the design of a time-based control system for a helicopter-based uninhabited aerial vehicle.     

Sensitivity reduction in feedback eigenvalue controller design

The problem of reducing sensitivity to variations of the open-loop system parameters is considered for the case where the objective is to design a feedback controller which drives the open-loop eigenvalues to desired positions. The results are based on the assumption that the open-loop multivariable system is transformed to a phase-variable canonical form prior to the application of the control design procedure.     

Model-based feedback controller design for dual actuated atomic force microscopy

In atomic force microscopy (AFM) the imaging speed is strongly limited by the bandwidth of the feedback loop that controls the interaction force between the measurement tip and the sample. A significant increase in closed-loop bandwidth without sacrificing positioning range can be achieved by combining a long-range, low-bandwidth actuator with a short-range, high-bandwidth actuator, forming a dual actuated system. This contribution discusses the design of a model-based feedback controller that controls the tip-sample force in dual actuated AFM. Special emphasis is given on guaranteeing robust stability of the feedback loop under influence of variations in the dynamical behavior of the system, and to prevent strong destructive interference between both actuators. To prevent instability of the feedback loop due to saturation of the short-range actuator, an anti-windup controller is presented that robustly stabilizes the system under all imaging conditions. The designed feedback controller is implemented on a prototype dual actuated AFM system, and demonstrates a disturbance rejection bandwidth of 20 kHz, which is about 20 times faster than the model-based controlled single actuated system. AFM images are obtained verifying a significant reduction of force variations between the tip and the sample while imaging. The faster control of the tip-sample force reduces the residual tracking error and, thus, reduces the chance of damage or wear of the tip and the sample, and allows for faster imaging.     

Integrated design of speed-sensorless and adaptive speed controller for a brushless DC motor

The study develops a design of an integrated new speed-sensorless approach that involves a torque observer and an adaptive speed controller for a brushless dc motor (BLDCM). The system is based on the vector control drive strategy. The speed-sensorless approach first employs a load observer to estimate the disturbed load torque, and then the estimated load torque is substituted into the mechanical dynamic equation to determine the rotor speed, and thus develop a speed-sensorless algorithm. Additionally, the mechanical rotor inertia constant and the friction coefficient, which are the inputs of the load observer, are estimated using the recursive least-square rule. Therefore, the proposed speed-sensorless approach is unaffected by the time-variant motor parameters nor is affected by the integrator drift problem. It also has a simpler computing algorithm than the extended Kalman filter for estimating the speed. The modified model reference adaptive system algorithm, an adaptive control algorithm, is adopted as a speed controller of the BLDCM to improve the performance of the speed-sensorless approach. Simulation and experimental results confirm that the performance of the design of a new integrated speed-sensorless approach and the adaptive speed controller is good.     

Robust controller design for a series resonant converter viaduty-cycle control

Robust controller design for a series resonant power converter is presented when load variation and unregulated input line voltage perturbation are taken into consideration. The perturbation of unregulated line voltage is treated as an exogenous disturbance and the load variation as a structured uncertainty of the converter. An averaged model, including disturbance and model uncertainty, is then derived. Two kinds of μ synthesis-D-K and μ-K iteration schemes-are applied to design robust controllers to diminish the susceptibility of the regulated voltage to perturbations of load variation and unregulated line voltage. In addition, a classical controller is also designed for performance comparison. Finally, simulations and experimental results are presented to verify the feasibility of the robust control theory     

Buck-boost converter feedback controller design via evolutionary search

Buck-boost converters are switched power converters. The model of the converter system varies from the ON state to the OFF state and hence traditional methods of controller design based on approximate transfer function models do not yield good dynamic response at different operating points of the converter system. This article attempts to design a feedback controller for a buck-boost type dc–dc converter using a genetic algorithm. The feedback controller design is perceived as an optimisation problem and a robust controller is estimated through an evolutionary search. Extensive simulation and experimental results provided in the article show the effectiveness of the new approach.     

Reinforcement learning and adaptive dynamic programming for feedback control

Living organisms learn by acting on their environment, observing the resulting reward stimulus, and adjusting their actions accordingly to improve the reward. This actionbased or Reinforcement Learning can capture notions of optimal behavior occurring in natural systems. We describe mathematical formulations for Reinforcement Learning and a practical implementation method known as Adaptive Dynamic Programming. These give us insight into the design of controllers for man-made engineered systems that both learn and exhibit optimal behavior.     

Modeling and control of steering system of heavy vehicles for automated highway systems

This work presents modeling, analysis, and controller design of the steering subsystem of heavy vehicles as a subsystem of vehicle lateral control system for the automated highway systems. A physical model of the steering subsystem is derived where the hydraulic power assist unit is modeled as a family of static nonlinear boost curves. Based on open-loop frequency tests and analysis of the physical model structure and its dynamical characteristics, a nominal second order linear model of the steering subsystem is obtained. Then, a linear robust loop-shaping controller is designed to provide a good tracking performance of the closed-loop dynamics of the steering subsystem for varying gain cross over frequencies which is a result of the nonlinear characteristics of the hydraulic power assist. The controller has been successfully incorporated as an inner-loop controller into the nested lateral control architecture for autonomous driving and its efficacy has been demonstrated experimentally.     

Totally invariant state feedback controller for position control ofsynchronous reluctance motor

A new totally invariant state feedback controller is designed by combining the classical state feedback controller and the variable-structure control (VSC). The combination of these two different control methods has the advantages of both their merits: (1) the easy design of the state feedback and (2) the strong robustness of the VSC. In other words, the system performance can be simply designed for the nominal system by using the classical state feedback, which includes such well-known techniques as the pole placement or the linear quadratic method. Then, VSC is used to ensure the control effect. To demonstrate the effectiveness of the totally invariant state feedback controller, it is applied to the position control of a synchronous reluctance motor. Simulation results are first given. In addition, a prototype hardware system is built and experimentally evaluated     

A beacon navigation method for autonomous vehicles

A method for navigating autonomous vehicles is presented. Based on the three-point problem from land surveying, this navigational technique makes use of angular measurements between fixed beacon pairs. Extremely accurate position information can be obtained over a large area with simple trigonometric or analytic geometry calculations. Typical worst-case errors are of the order of 10 cm throughout a 2500 m² workspace. An experimental position-measuring system has been built and tested, and it demonstrated the ability of this technique to function as a key element in a navigation system for autonomous vehicles     

AQM controller design for TCP networks based on a new control strategy

When the network suffers from congestion, the core or edge routers signal the incidence of congestion through the active queue management (AQM) to the sources. The time-varying nature of the network dynamics and the complex process of retuning the current AQM algorithms for different operating points necessitate the development of a new AQM algorithm. Since the non-minimum phase characteristics of the network dynamics restrict direct application of the proportional-integral-derivative (PID) controller, we propose a compensated PID controller based on a new control strategy addressing the phase-lag and restrictions caused by the delay. Based on the unstable internal dynamics caused by the non-minimum phase characteristics, a dynamic compensator is designed and a PID controller is then allowed to meet the desired performance objectives by specifying appropriate dynamics for the tracking error. Since the controller gains are obtained directly from the dynamic model, the designed controller does not require to be tuned over the system operating envelop. Moreover, simulation results using ns2 show improvements over previous works especially when the range of variation of delay and model parameters are drastic. Simplicity, low computational cost, self-tuning structure and yet considerable improvement in performance are exclusive features of the proposed AQM for the edge or core routers.     

Asymptotic analysis of adaptive rate control for diverse sourceswith delayed feedback

This paper analyzes the effectiveness of a class of adaptive algorithms for rate control in a data network with the following two elements: many sources with diverse characteristics (e.g., nonadaptive and adaptive sources with different feedback delays, different constraints on transmission rates) and a switch, based on ATM or cell-relay technology, with finite buffers. Several adaptive sources compete among themselves as well as with other nonadaptive sources for bandwidth at a single queue. We first model random fluctuations in the queue-length process due to the nonadaptive sources as Brownian motion, and we show, for a large class of adaptive strategies, how the amount of bandwidth wasted because of idleness and the amount of offered traffic lost because of overflowing buffers scale with the speed of the network. We then model the arrival process of nonadaptive traffic more realistically as a general stochastic fluid with bounded, positive rates. For a class of adaptive strategies with linear adaptation functions, we prove that the results obtained from the Brownian model of randomness extend to cover the more realistic model. This occurs because the adaptive sources induce heavy-traffic conditions (corresponding to the power-maximizing regime of Mitra (1990)) by accurately estimating and using the residual bandwidth not occupied by the nonadaptive traffic. Our analysis gives new insight about how performance measures scale with the variability of the nonadaptive traffic. We illustrate through simulations that queue fluctuations behave as predicted     

An adaptive controller for a direct-drive SCARA robot

A direct adaptive controller for trajectory tracking of high-speed robots such as a direct-drive SCARA robot is presented. In this robot, nonlinear effects due to centrifugal, Coriolis, and inertial forces are more important than friction and gravity forces, unlike most industrial robots. The control law of the adaptive scheme consists of a PD regulator plus feedforward compensation of full dynamics. The feedforward terms are adjusted by an adaptation law so that the steady-state position errors are zero. With this adaptive controller, the joint acceleration measurement is not required and no inversion of the estimated mass matrix is involved. The tracking performances of the controller applied to a two-degree-of-freedom SCARA is illustrated by a real-time implementation based on a single-chip digital signal processor (DSP)     

An optimal and adaptive design of the feedforward motion controller

The zero phase error tracking controller (ZPETC) in motion control, as proposed by Tomizuka (1987) , renders the desirable zero phase error, but with a limited gain response. Moreover, a ZPETC, which is basically in a feedforward control structure, is very sensitive to modeling error. To improve the tracking accuracy of the ZPETC, this paper presents an optimal ZPETC design with a concise polynomial digital prefilter (DPF). The parameters of this well-designed DPF are obtained through the derived L₂-norm optimization. By cascading the developed DPF to the ZPETC, the resultant optimal ZPETC greatly improves the bandwidth of the tracking control systems while maintaining the zero phase error. Compared with other optimal approaches, the present design leads to much simpler procedures and fewer computations. Furthermore, the proposed optimal ZPETC can be adequately implemented as an adaptive ZPETC by including real-time estimation technique to cope with the external load perturbation and parameter variation. Compared with the other adaptive approaches, the optimal concept is used in the present adaptive ZPETC, and it also renders more accurate results because of its improved magnitude response. Experimental results on a DC servo table with different controllers indicate that when there is no loading, the present optimal ZPETC achieves the best tracking performance. Moreover, the adaptive ZPETC achieves the most satisfactory results when an external load is applied     

Commutative controller: a new technique for the design of multivariable control systems

If a linear time-invariant multiple-input multiple-output plant is represented by a square transfer-function matrix G(s), a spectral analysis may be carried out to determine a set of system characteristic transfer functions. A multivariable feedback controller may then be synthetised by first designing a set of single-loop controllers for these characteristic systems, and then transforming the results to obtain the required multivariable controller.     

Robust feedback linearization using an adaptive PD regulator for a sensorless control of a throttle valve

With classic gasoline injection systems, engine efficiency and emissions are affected by the control of the throttle plate, in particular its angular position. Depending on the current engine load, the angular position must track a trajectory as determined by the accelerator. This paper considers two problems. The first one is the design of a state observer. A velocity estimator is proposed based on measurements of current. If the effect of the noise is minimized, the angular position can be achieved through a cascade structure between a particular velocity estimator and an inversion of the electrical system. This approach allows us to avoid a more complex structure for the observer, and yields an acceptable performance and the elimination of bulky position sensor systems. The elimination of the position sensor system simplifies the production system of the valve. The second problem, the robustness of the tracking, is addressed using a minimum variance control approach. This paper presents feasible real-time self-tuning of an approximated proportional derivative (PD) regulator, which compensates for the tracking error caused by inexact feedback linearization. It is interesting to note that the structure of the approximated PD regulator is similar to the velocity estimator. Robustness in the proposed loop control is achieved. Measured results on a real experimental setup with hardware-in-the-loop are shown.     

Full-state feedback controller design with “delay scheduling” for cart-and-pendulum dynamics

A new approach is proposed to design fixed full-state feedback controllers for linear-time-invariant (LTI) systems with multiple time-delays. This approach takes advantage of the recently introduced “delay scheduling” concept, which opens a new direction in synthesizing the control. “Delay scheduling” strategy suggests further prolonging the existing (and unavoidable) delays in the feedback in order to recover stability or to improve the control performance features. To be able to do this, however, system should have large (and maybe multiple) stable operating zones in the domain of the delays. The main contribution of this paper is to develop a methodology for designing a control law to create this feature. The operation starts with a selection of the feedback gains for a stable non-delayed system. We then utilize a recent paradigm, Cluster Treatment of Characteristic Roots (CTCR), to examine the stability outlook when the delays are present in the dynamics. A scheme is also introduced to modify this gain structure so that the system exhibits a desirably large stable pocket(s) to enable the “delay scheduling”. The paper describes the methodology, without loss of generality, on a fully-actuated cart-pendulum system. Relevant experiments are carried out to show the viability of the proposed idea.