Showing papers on "Sliding mode control published in 2004"

Adaptive Sliding Mode Control Design for a Hypersonic Flight Vehicle

Abstract: A multi-input/multi-output adaptive sliding controller is designed and analyzed for the longitudinal dynamics of a generic hypersonic air vehicle. This vehicle model is nonlinear, multivariable, and unstable and includes uncertain parameters. Simulation studies are conducted for trimmed cruise conditions of 110,000 ft and Mach 15 where the responses of the vehicle to a step change in altitude and airspeed are evaluated. The commands are 100-ft/s step velocity and 2000-ft step altitude. The controller is evaluated for robustness with respect to parameter uncertainties using simulations. Simulation studies demonstrate that the proposed controller is robust with respect to parametric uncertainty and meets the performance requirements with relatively low-amplitude control inputs.

Sliding mode control

Abstract: The sliding mode control approach is recognised as an efficient tool to design robust controllers for complex high-order nonlinear dynamic plant operating under uncertain conditions. The research in this area was initiated in the former Soviet Union about 40 years ago, and the sliding mode control methodology has subsequently received much more attention from the international control community within the last two decades.

A continuous asymptotic tracking control strategy for uncertain nonlinear systems

Abstract: In this note, we present a new continuous control mechanism that compensates for uncertainty in a class of high-order, multiple-input-multiple-output nonlinear systems. The control strategy is based on limited assumptions on the structure of the system nonlinearities. A new Lyapunov-based stability argument is employed to prove semiglobal asymptotic tracking.

Design of adaptive sliding mode controller for chaos synchronization with uncertainties

Abstract: In this paper an adaptive sliding mode controller is presented for a class of master–slave chaotic synchronization systems with uncertainties. Using an adaptive technique to estimate the switching gain, an adaptive sliding mode controller is then proposed to ensure that the sliding condition is maintained in finite time. The proposed adaptive sliding mode control scheme can be implemented without the requirement that the bounds of the uncertainties and the disturbances should be known in advance. The concept of extended systems is used such that continuous control input is obtained using a sliding mode design scheme. By comparing with the results in the existed literatures, the results show that the master–slave chaotic systems with uncertainties can be synchronized accurately by this controller. Illustrative examples of chaos synchronization for uncertain Duffing–Holmes system are presented to demonstrate the superiority of the obtained results.

Robust Tracking Control Design for Spacecraft Under Control Input Saturation

Abstract: A continuous globally stable tracking control algorithm is presented for spacecraft in the presence of control input saturation, parametric uncertainty, and external disturbances. The proposed control algorithm has the following properties: 1) fast and accurate response in the presence of bounded disturbances and parametric uncertainty; 2) explicit accounting for control input saturation; and 3) computational simplicity and straightforward tuning. A detailed stability analysis of the resulting closed-loop system is included. It is shown that global stability of the overall system is guaranteed with continuous control even in the presence of bounded disturbances and parametric uncertainty. In the proposed controller a single parameter is adjusted dynamically in such a fashion that it is possible to prove that both attitude and angular velocity errors will tend to zero asymptotically. The stability proof is based on a Lyapunov analysis and the properties of the quaternion representation of spacecraft dynamics. One of the main features of the proposed design is that it establishes a straightforward relationship between the magnitudes of the available control inputs and those of the desired trajectories and disturbances even with continuous control. Numerical simulations are included to illustrate the spacecraft performance obtained using the proposed controller.

Design of a stable sliding-mode controller for a class of second-order underactuated systems

Abstract: A stable hierarchical sliding-mode control method for a class of second-order underactuated systems is presented. The ideas behind the method are as follows. First, the underactuated system is divided into two subsystems. For each part a first-level sliding surface is defined. For these two first-level sliding surfaces, a second-level sliding surface is defined. The sliding-mode control law is derived using Lyapunov law. The control law can drive the subsystems toward their sliding surfaces and attain their desired values, and implement antidisturbance control. The asymptotic stability of all the sliding surfaces is proved theoretically, and simulation results show the controller's validity and its adaptive abilities for all kinds of extraneous disturbances.

Variable structure systems : from Principles to Implementation

Abstract: * Part I: Sliding mode control theory * Chapter 1: Sliding mode control * Chapter 2: Sliding mode regulator design * Chapter 3: Deterministic output noise effects in sliding mode observation * Chapter 4: Stochastic output noise effects in sliding mode observation * Part II: New trends in sliding mode control * Chapter 5: Discrete-time VSS * Chapter 6: Robustness issues of 2-sliding mode control * Chapter 7: Sliding modes, delta-modulation and output feedback control of dynamic systems * Chapter 8: Analysis of sliding modes in the frequency domain * Chapter 9: Output tracking in causal nonminimum-phase systems using sliding modes * Part III: Applications of sliding mode control * Chapter 10: Sliding mode control and chaos * Chapter 11: Sliding modes in fuzzy and neural network systems * Chapter 12: SMC applications in power electronics * Chapter 13: Sliding modes in motion control systems * Chapter 14: Sliding mode control for automobile applications * Chapter 15: The application of sliding mode control algorithms to a diesel generator set * Chapter 16: Motion control of underwater objects by using second order sliding mode techniques * Chapter 17: Semiglobal stabilisation of linear uncertain system via delayed relay control

Adaptive sliding control for single-link flexible-joint robot with mismatched uncertainties

Abstract: An adaptive sliding controller is proposed for a single-link flexible-joint robot with mismatched uncertainties. A backsteppinglike design is used to deal with the mismatched problem and the function approximation technique is employed to transform the uncertainties into finite combinations of orthonormal basis functions. Adaptive laws can thus be derived based on the Lyapunov-like design. Experiment results show that the proposed control strategy gives good tracking performance with all other signals remaining bounded.

A modular control scheme for PMSM speed control with pulsating torque minimization

Abstract: In this paper, a modular control approach is applied to a permanent-magnet synchronous motor (PMSM) speed control. Based on the functioning of the individual module, the modular approach enables the powerfully intelligent and robust control modules to easily replace any existing module which does not perform well, meanwhile retaining other existing modules which are still effective. Property analysis is first conducted for the existing function modules in a conventional PMSM control system: proportional-integral (PI) speed control module, reference current-generating module, and PI current control module. Next, it is shown that the conventional PMSM controller is not able to reject the torque pulsation which is the main hurdle when PMSM is used as a high-performance servo. By virtue of the internal model, to nullify the torque pulsation it is imperative to incorporate an internal model in the feed-through path. This is achieved by replacing the reference current-generating module with an iterative learning control (ILC) module. The ILC module records the cyclic torque and reference current signals over one entire cycle, and then uses those signals to update the reference current for the next cycle. As a consequence, the torque pulsation can be reduced significantly. In order to estimate the torque ripples which may exceed certain bandwidth of a torque transducer, a novel torque estimation module using a gain-shaped sliding-mode observer is further developed to facilitate the implementation of torque learning control. The proposed control system is evaluated through real-time implementation and experimental results validate the effectiveness.

Sliding mode closed-loop control of FES controlling the shank movement

Abstract: Functional electrical stimulation (FES) enables restoration of movement in individuals with spinal cord injury. FES-based devices use electric current pulses to stimulate and excite the intact peripheral nerves. They produce muscle contractions, generate joint torques, and thus, joint movements. Since the underlying neuromuscular-skeletal system is highly nonlinear and time-varying, feedback control is necessary for accurate control of the generated movement. However, classical feedback/closed-loop control algorithms have so far failed to provide satisfactory performance and were not able to guarantee stability of the closed-loop system. Because of this, only open-loop controlled FES devices are in clinical use in spite of their limitations. The purpose of the reported research was to design a novel closed-loop FES controller that achieves good tracking performance and guarantees closed-loop stability. Such a controller was designed based on a mathematical neuromuscular-skeletal model and is founded on a sliding mode control theory. The controller was used to control shank movement and was tested in computer simulations as well as in actual experiments on healthy and spinal cord injured subjects. It demonstrated good robustness, stability, and tracking performance properties.

Sliding mode control of a magnetic levitation system

Abstract: Sliding mode control schemes of the static and dynamic types are proposed for the control of a magnetic levitation system. The proposed controllers guarantee the asymptotic regulation of the statesof the system to their desired values. Simulation results of the proposed controllers are given to illustrate the effectiveness of them. Robustness of the control schemes to changes in the parameters of the system is also investigated.

Control of a Nonlinear Wing Section Using Leading- and Trailing-Edge Surfaces

Abstract: The control of nonlinear aeroelastic response of a wing section with a continuous stiffening-type structural nonlinearity is examined through analytical and experimental studies. Motivated by the limited effectiveness of using a single, trailing-edge control surface for the suppression of limit-cycle oscillations of a typical wing section, improvements in the control of limit-cycle oscillations are investigated through the use of multiple control surfaces, namely, an additional leading-edge control surface. The control methodology consists of a feedback linearization approach that transforms the system equations of motion via Lie algebraic methods and a model reference adaptive control strategy that augments the closed-loop system to account for inexact cancellation of nonlinear terms due to modeling uncertainty. Specifically, uncertainty in the nonlinear pitch stiffness is examined. It is shown through simulations and experiments that globally stabilizing control may be achieved by using two control surfaces.

Adaptive fuzzy decentralized control fora class of large-scale nonlinear systems

Abstract: In this paper, direct and indirect adaptive output-feedback fuzzy decentralized controllers for a class of uncertain large-scale nonlinear systems are developed. The proposed controllers do not need the availability of the state variables. By designing the state observer, the adaptive fuzzy systems, which are used to model the unknown functions, can be constructed using the state estimations, and a new hybrid adaptive fuzzy control methodology is proposed by combining the adaptive fuzzy systems with H/sup /spl infin// control and the sliding mode control techniques. Based on Lyapunov stability theorem, the stability of the closed-loop systems can be verified. Moreover, the proposed overall control schemes guarantee that all the signals involved are bounded and achieve the H/sup /spl infin//-tracking performance. To demonstrate the effectiveness of the proposed methods, simulation results are illustrated in this paper.

Supervisory recurrent fuzzy neural network control of wing rock for slender delta wings

Abstract: Wing rock is a highly nonlinear phenomenon in which an aircraft undergoes limit cycle roll oscillations at high angles of attack. In this paper, a supervisory recurrent fuzzy neural network control (SRFNNC) system is developed to control the wing rock system. This SRFNNC system is comprised of a recurrent fuzzy neural network (RFNN) controller and a supervisory controller. The RFNN controller is investigated to mimic an ideal controller and the supervisory controller is designed to compensate for the approximation error between the RFNN controller and the ideal controller. The RFNN is inherently a recurrent multilayered neural network for realizing fuzzy inference using dynamic fuzzy rules. Moreover, an on-line parameter training methodology, using the gradient descent method and the Lyapunov stability theorem, is proposed to increase the learning capability. Finally, a comparison between the sliding-mode control, the fuzzy sliding control and the proposed SRFNNC of a wing rock system is presented to illustrate the effectiveness of the SRFNNC system. Simulation results demonstrate that the proposed design method can achieve favorable control performance for the wing rock system without the knowledge of system dynamic functions.

Observer-based sliding mode control for nonlinear state-delayed systems

Abstract: An observer-based sliding mode control problem is studied for state-delayed systems with unmeasurable states and nonlinear uncertainties. The main advantage of the proposed scheme is that it eliminates the need for state variables to be fully accessible for its control. This is possible through the use of a sliding mode controller, which performs its control by employing state estimates obtained from the sliding mode observer. By means of linear matrix inequalities, a sufficient condition is then given to ensure the asymptotic stability of the overall closed-loop state-delayed system composed of the observer dynamics and the estimation error dynamics. Furthermore, it is shown that the proposed control scheme ensures the reachability of the sliding surfaces in both the state estimate space and the estimation error space.

Second-order sliding-mode control of DC drives

Abstract: One of the most recent topics in variable-structure systems theory is represented by the second-order sliding-mode control (2-SMC) methodology. This approach guarantees the same robustness and dynamic performance of traditional first-order SMC algorithms, and, at the same time, attenuates the chattering phenomenon, which is the main drawback in the actual implementation of this technique. In the present paper, a recently-proposed 2-SMC algorithm is used to synthesize a robust dc-drive control system which does not require current feedback and demands only rough information about the actual motor parameters. Stability and performance are analyzed, and an experimental comparison with a proportional-integral-based control scheme is reported.

Model predictive control of continuous-time nonlinear systems with piecewise constant control

Abstract: A new model predictive control (MPC) algorithm for nonlinear systems is presented. The plant under control, the state and control constraints, and the performance index to be minimized are described in continuous time, while the manipulated variables are allowed to change at fixed and uniformly distributed sampling times. In so doing, the optimization is performed with respect to sequences, as in discrete-time nonlinear MPC, but the continuous-time evolution of the system is considered as in continuous-time nonlinear MPC.

Synchronization of chaotic systems with parametric uncertainty using active sliding mode control

Abstract: This paper presents an active sliding mode control method for synchronizing two chaotic systems with parametric uncertainty. And a sufficient condition is drawn for the robust stability of the error dynamics, and is applied to guiding the design of the controllers. Finally, numerical results are used to show the robustness and effectiveness of the proposed control strategy.

Sliding mode state observation for non-linear systems

Abstract: In this paper a class of non-linear systems with uncertainty and a Lipschitz part is considered. The non-linear part satisfies the Lipschitz condition, whilst the uncertain part is a bounded function. A sliding mode observer is designed to yield feedforward compensation input to stabilize the error estimation system with and without a Lipschitz non-linearity. Sufficient conditions for stability of the Thau observer are also proposed. These conditions ensure the stability of the non-linear observer by selecting a suitable observer gain matrix. In general, when the system contains unmatched uncertainty, ultimate boundedness is obtained. The ultimate boundedness radius depends upon the defined ‘distance of the unmatched uncertainty’. Some sufficient conditions may ensure the stability of a non-linear observer for systems with uncertainties.

A novel Takagi-Sugeno-based robust adaptive fuzzy sliding-mode controller

Abstract: In this paper, a nonlinear dynamic system is first approximated by N fuzzy-based linear state-space subsystems. To track a trajectory dominant by a specific frequency, the reference models with desired amplitude and phase features are established by the same fuzzy sets of the system rule. Similarly, the same fuzzy sets of the system rule are employed to design robust fuzzy sliding-mode control (RFSMC) and adaptive fuzzy sliding-mode control (AFSMC). The difference between RFSMC and AFSMC is that AFSMC contains an updating law to learn system uncertainties and then an extra compensation is designed. It is different from the most previous papers to learn the whole nonlinear functions. As the norm of the sliding surface is inside of a defined set, the updating law starts; simultaneously, as it is outside of the other set, the updating law stops. For the purpose of smoothing the possibility of discontinuous control input, a transition between RFSMC and AFSMC is also assigned. Under the circumstances, the proposed control [robust adaptive fuzzy sliding-mode control (RAFSMC)] can automatically tune as a RFSMC or an AFSMC; then the advantages coming from the RFSMC and AFSMC are obtained. Finally, the stabilities of the overall system of RFSMC, AFSMC, and RAFSMC are verified by Lyapunov stability theory. The compared simulations among RFSMC, AFSMC, and RAFSMC are also carried out to confirm the usefulness of the proposed control scheme.

Robot control without velocity measurements: new theory and experimental results

Abstract: Most robust control schemes for rigid robots assume velocities measurements to be available. Although it is possible to measure velocities by using tachometers, this increases costs, and the signals delivered may be contaminated with noise. Since the use of encoders allows reading joint position pretty accurately, sometimes it is desirable to estimate joint velocities through an observer. This paper presents a robust control scheme designed in conjunction with a linear observer. Uniform ultimate boundedness for the tracking and observation errors are guaranteed. Experiments are included to support the theoretical results and to show that the performance of the new control-observer law is better, in comparison with well-known algorithms reported in the literature.

Optimizing nonlinear control allocation

Abstract: Control allocation is commonly utilized in overactuated mechanical systems in order to optimally generate a requested generalized force using a redundant set of actuators. Using a control-Lyapunov approach, we develop an optimizing control allocation algorithm in the form of a dynamic update law, for a general class of nonlinear systems. The asymptotically optimal control allocation in interaction with an exponentially stable trajectory-tracking controller guarantees uniform boundedness and uniform global exponential convergence.

Nonlinear chaos control in a permanent magnet reluctance machine

Abstract: The dynamics of a permanent magnet synchronous machine (PMSM) is analyzed. The study shows that under certain conditions the PMSM is experiencing chaotic behavior. To control these unwanted chaotic oscillations, a nonlinear controller based on the backstepping nonlinear control theory is designed. The objective of the designed control is to stabilize the output chaotic trajectory by forcing it to the nearest constant solution in the basin of attraction. The result is compared with a nonlinear sliding mode controller. The designed controller that based on backstepping nonlinear control was able to eliminate the chaotic oscillations. Also the study shows that the designed controller is mush better than the sliding mode control.

Neuro-sliding mode control with its applications to seesaw systems

Abstract: This paper proposes an approach of cooperative control that is based on the concept of combining neural networks and the methodology of sliding mode control (SMC). The main purpose is to eliminate the chattering phenomenon. Next, the system performance can be improved by using the method of SMC. In the present approach, two parallel Neural Networks are utilized to realize a neuro-sliding mode control (NSMC), where the equivalent control and the corrective control are the outputs of neural network 1 and neural network 2, respectively. Based on expressions of the SMC, the weight adaptations of neural network can be determined. Furthermore, the gradient descent method is used to minimize the control force so that the chattering phenomenon can be eliminated. Finally, experimental results are given to show the effectiveness and feasibility of the approach.

Sensorless control of PMSM in high speed range with iterative sliding mode observer

Abstract: This paper proposes two control algorithms for a sensorless speed control of a PMSM. One is a new low pass filter. This filter is designed to have the variable cutoff frequency according to the rotor speed. And the phase delay angle is so small as to be ignored not only in the low speed region but also in the high speed region including the field weakening region. Sensorless control of a PMSM can be guaranteed without any delay angle by using the proposed low pass filter. The other is a new iterative sliding mode observer (I-SMO). Generally the sliding mode observer (SMO) has the attractive features of the robustness to disturbances, and parameter variations. In the high speed region the switching gain of SMO must be large enough to operate the sliding mode stably. But the estimated currents and back EMF can not help having much ripple or chattering components especially in the high speed region including the flux weakening region. Using I-SMO can reduce chattering components of the estimated currents and back EMF in all speed regions without any help of the expensive hardware such as the high performance DSP and A/D converter. Experimental results show the usefulness of the proposed two algorithms for the sensorless drive system of a PMSM.