Tracking Performance Of Control System Research Articles

A frequency-domain approach for enhanced performance and task flexibility in finite-time ILC

Iterative learning control (ILC) techniques are capable of improving the tracking performance of control systems that repeatedly perform similar tasks by utilizing data from past iterations. The aim of this paper is to achieve both the task flexibility enabled by ILC with basis functions and the performance of frequency-domain ILC, with an intuitive design procedure. The cost function of norm-optimal ILC is determined that recovers frequency-domain ILC, and consequently, the feedforward signal is parameterized in terms of basis functions and frequency-domain ILC. The resulting method has the performance and design procedure of frequency-domain ILC and the task flexibility of basis functions ILC, and are complimentary to each other. Validation on a benchmark example confirms the capabilities of the framework.

Prescribed Performance Adaptive Neural Compensation Control for Intermittent Actuator Faults by State and Output Feedback.

Due to the existing effects of intermittent jumps of unknown parameters during operation, effectively establishing transient and steady-state tracking performances in control systems with unknown intermittent actuator faults is very important. In this article, two prescribed performance adaptive neural control schemes based on command-filtered backstepping are developed for a class of uncertain strict-feedback nonlinear systems. Under the condition of system states being available for feedback, the state feedback control scheme is investigated. When the system states are not directly measured, a cascade high-gain observer is designed to reconstruct the system states, and in turn, the output feedback control scheme is presented. Since the projection operator and modified Lyapunov function are, respectively, used in the adaptive law design and stability analysis, it is proven that both schemes can not only ensure the boundedness of all closed-loop signals but also confine the tracking errors within prescribed arbitrarily small residual sets for all the time even if there exist the effects of intermittent jumps of unknown parameters. Thus, the prescribed system transient and steady-state performances in the sense of the tracking errors are established. Furthermore, we also prove that the tracking performance under output feedback is able to recover the tracking performance under state feedback as the observer gain decreases. Simulation studies are done to verify the effectiveness of the theoretical discussions.

Optimal design of robust feedforward compensator with gain and phase specifications

SummaryThis paper deals with the design of the robust feedforward compensator for improving the tracking performance of control systems with gain and phase specifications. The feedforward compensator is designed for single‐input–single‐output continuous‐time linear systems with constrained input and model uncertainty. The design objective is to make the transfer characteristic from command to output be one in the presence of the input saturation and the model uncertainty. To do that, the design of the feedforward compensator is formulated as a new gain‐phase optimization problem with both the gain and phase specifications. Then, the design procedures are proposed by using frequency‐matching method based on the closed‐loop frequency response. The proposed method provides a good trade‐off between system performance and control input to overcome performance reduction due to input saturation, and guarantees the robustness of the overall system in the presence of the model uncertainty. Two design examples illustrate that the frequency characteristics and the transient response of the control system are improved by the proposed method.

Optimal tracking performance of control systems with two-channel constraints

This paper focuses on the tracking performance limitation for a class of networked control systems (NCSs) with two-channel constraints. In communication channels, we consider bandwidth, energy constraints and additive colored Gaussian noise (ACGN) simultaneously. In plant, non-minimal zeros and unstable poles are considered; multi-repeated zeros and poles are also applicable. To obtain the optimal performance, the two-parameter controller is adopted. The theoretical results show that the optimal tracking performance is influenced by the non-minimum phase zeros, unstable poles, gain at all frequencies of the given plant, and the reference input signal for NCSs. Moreover, the performance limitation is also affected by the limited bandwidth, additive colored Gaussian noise, and the corresponding multiples for the non-minimum phase zeros and unstable poles. Additionally, the channel minimal input power constraints are given under the condition ensuring the stability of the system and acquiring system performance limitation. Finally, simulation examples are given to illustrate the theoretical results.

Optimal tracking performance of networked control systems with communication delays under channel input power constraint

The optimal tracking performance of networked control systems with communication delay and white Gaussian noise under the consideration of the channel input power constraint is studied in this paper. The tracking performance is measured by the energy of the system’s error signal and channel input power. The tracking performance is minimized by considering the channel input power constraint searching through all stabilizing two-parameter controllers. The optimal tracking performance of networked control systems under the communication delays, packet dropout and white Gaussian noise of the communication channel has been studied. The explicit expressions of the optimal tracking performance are obtained by applying the spectral factorization and inner–outer factorization techniques. It is shown that the optimal tracking performance depends on the non-minimum phase zeros, unstable poles of the given plant, communication delay, packet dropouts probability and white Gaussian noise. It is also shown that if the constraint of the communication channel does not exist, the optimal tracking performance reduces to the existing tracking performance of the control system without communication. The result shows how the communication delay, packet dropout probability and white Gaussian noise may fundamentally constrain a networked system’s tracking capability. Finally, some typical examples are given to illustrate the theoretical results.

Finite-time convergent continuous control design based on sliding mode algorithms with application to a hydraulic drive

Sliding modes impose strong robustness toward parametric plant uncertainties and disturbances and provide for accurate tracking performance in control systems. However, in physical systems the application of sliding modes may give rise to undesirable chattering of the control signal due to actuator dynamics, possible excitation of unmodelled dynamics and structural resonant modes of load systems, etc. This may be avoided by application of smoothing functions imposing boundary layers on the control constraint, or by carrying out the design in relation to the control derivative. However, such boundary layers introduce additional design parameters and actuator dynamics may not allow the desired control accuracy to be reached. In this paper continuous controllers are proposed, with the designs taking their offset in some well-known sliding controllers. The proposed controllers preserve the finite-time convergence properties known from sliding control while at the same time avoiding control chattering, however, on the cost of robustness. Experimental results confirm the announced properties when applied to a hydraulic valve-cylinder drive, and demonstrates superior performance over conventional linear controllers.

Best Tracking Performance of Networked Control Systems Based on Communication Constraints

ABSTRACTThe best tracking problem for a single‐input‐single‐output (SISO) networked control system with communication constraints is studied in this paper. The tracking performance is measured by the energy of the error signal between the output of the plant and the reference signal. The communication constraints under consideration are finite bandwidth and networked induced‐delay. Explicit expressions of the minimal tracking error have been obtained for networked control systems with or without communication constraints. It is shown that the best tracking performance dependents on the nonminimum phase zeros, and unstable poles of the given plant, as well as the bandwidth and networked induced‐delay. It is also shown that, if the constraints of the communication channel do not exist, the best tracking performance reduces to the existing tracking performance of the control system without communication constraints. The result shows how the bandwidth and networked induced‐delay of a communication channel may fundamentally constrain a control system's tracking capability. Some typical examples are given to illustrate the theoretical results.

Optimal tracking performance and design of networked control systems with packet dropouts

The optimal tracking problem for single-input–single-output (SISO) networked control system over a communication channel with packet dropouts is studied in this paper. The tracking performance is measured by the energy of the error signal between the output of the plant and the reference signal. It is shown that the optimal tracking performance is constrained by nonminimum phase zeros, unstable poles, the characteristics of the reference signal and packet dropout probability, and the optimal controller is obtained. It is also shown that when the communication constraint does not exist, the optimal tracking performance reduces to the existing normal tracking performance of the control system without a communication channel. The result shows how the packet dropouts probability of a communication channel may fundamentally constrain a control system's tracking ability. Some typical examples and simulations are given to illustrate the theoretical results.

Optimal tracking performance of MIMO control systems with communication constraints and a code scheme

This paper investigates the issue of the optimal tracking performance for multiple-input multiple-output linear time-invariant continuous-time systems with power constrained. An H2 criterion of the error signal and the signal of the input channel are used as a measure for the tracking performance. A code scheme is introduced as a means of integrating controller and channel design to obtain the optimal tracking performance. It is shown that the optimal tracking performance index consists of two parts, one depends on the non-minimum phase zeros and zero direction of the given plant, as well as the reference input signal, while the other depends on the unstable poles and pole direction of the given plant, as well as on the bandwidth and additive white noise of a communication channel. It is also shown that when the communication does not exist, the optimal tracking performance reduces to the existing normal tracking performance of the control system. The results show how the optimal tracking performance is limited by the bandwidth and additive white noise of the communication channel. A typical example is given to illustrate the theoretical results.

REMOVED: Favorable effects of time delays on tracking performance of control systems

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Generalized Holds, Ripple Attenuation, and Tracking Additional Outputs in Learning Control

Iterative discrete-time learning control can be very effective at improving the tracking performance of control systems. Three different limitations or potential dife culties of discrete-time learning control are addressed. 1 ) The number of output variables for which zero tracking error can be achieved is limited by the number of input variables. 2 ) Every variable for which zero tracking error is sought must be a measured variable. 3 ) Because the control action is digital, the intersample behavior may have undesirable error from ripple. The e rst issue is addressed by two approaches, either by seeking zero error for different output variables at alternating time steps or by skipping time steps. The latter corresponds to using a generalized hold device. To address the second issue, it isshown howthesetechniques can becombined with an observerwhen onewishesto haveimproved tracking ofnot only measured outputs but also unmeasured output variables. To improve ripple, one can ask for good tracking of theoutput,andinadditiongoodtrackingofitsderivativeorderivatives,anditisshownhowmethodsdevelopedhere can accomplish this. These generalizations are made for three different effective learning control laws: integral control-based learning with zero phase e ltering, which is particularly simple; a contraction mapping learning control, which is particularly robust; and a phase cancellation learning control, which is particularly effective at producing small e nal error levels in experiments.