Design of a static sliding mode controller for T-S fuzzy systems based on Quantized information

To eliminate the effect of the uncertain disturbances and improve the control accuracy of spacecraft Attitude Control System, a nonlinear control algorithm named nonsingular terminal sliding-mode feedback controller is proposed in this work, which is mainly made up of nonsingular terminal sliding-mode controller and sliding-mode feedback controller. In the first place, nonsingular terminal sliding-mode controller is designed, which guarantees global asymptotic convergence of the attitude in the presence of the uncertain perturbations from the space. Despite that, it is the influence of the uncertain disturbances that hinder the control accuracy. Then, in order to promote the control accuracy, the sliding-mode feedback controller based on the principle of minimum sliding-mode error is proposed, which is used to compensate the control errors of the nonsingular terminal sliding-mode controller caused by the uncertainties. Hence, the determination principle of the weighting matrix in sliding-mode feedback controller is discussed, and the algorithm structure of the sliding-mode feedback controller is also analyzed, which provides the theoretical basis for the sliding-mode feedback controller. By contrast, an adaptive fuzzy algorithm is designed and introduced into the nonsingular terminal sliding-mode controller to improve the control accuracy, which named the nonsingular terminal fuzzy sliding-mode controller. Last but not the least, several numerical examples are presented to demonstrate the efficacy of the proposed nonsingular terminal sliding-mode feedback controller. Simulation results confirm that the control accuracy of the nonsingular terminal sliding-mode feedback controller is higher than the nonsingular terminal sliding-mode controller and the same as nonsingular terminal fuzzy sliding-mode controller. Not only is the calculation of the nonsingular terminal fuzzy sliding-mode feedback controller smaller than nonsingular terminal fuzzy sliding-mode controller, the adjusted parameters are also fewer than nonsingular terminal fuzzy sliding-mode controller obviously. The numerical results clearly indicate that the proposed nonsingular terminal sliding-mode feedback controller based on the principle of minimum sliding-mode error can compensate control errors accurately and quickly; therefore, it can reduce the effect of the uncertainties from the space indirectly.

ABS(antilock brake system) is one of the most important active safety technology for modern vehicles which could enhance vehicle active safety. In this paper, an improved sliding mode control method based on reaching law has been proposed to solve the vibration problem in traditional sliding mode control. The ABS control strategy has been designed based on the sliding mode variable structure control. On this basis, the ABS single wheel depending on control strategy has been designed to ensure the braking stability. By hardware-in-loop simulation, the results demonstrate that ABS sliding mode variable structure control could enhance braking stability performance and improve the control effect on high friction and low friction road.

In this study, a proposed three phase quasi Z source inverter (QZSI) using Sliding Mode Control (SMC) method is presented. The two impedance source networks have been implemented to increase the nonlinear of system. These control algorithm and proposed topology have been offered to get fast and dynamic response in robust and stable position even though input voltage, references have been changed. According to the proposed model using SMC method, the design of related inverter has been run and observed the behavior of regarding system during simulation. In power electronics systems have included nonlinear loads such as switches, MOSFETs, diodes etc. These cause to negative effects on performance of related systems. On the other hand, generally both Z source (ZS) and quasi Z source (QZS) topologies are preferred, even if buck-boost inverters are designed. SMC method is one of the most popular control types which has provided to dynamic response in robust and stable position against to nonlinear and unstable changes. During the switching process for all parts of system, control method has overcome unintended output and completed control steps based on design structure. Also, the proposed topology has been simulated at MATLAB/SIMULINK.

Classical sliding mode controller is robust to model uncertainties and external disturbances. A sliding mode control method with a switching control low guarantees asymptotic stability of the system, but the addition of the switching control law introduces chattering in to the system. One way of attenuating chattering is to insert a saturation function inside of a boundary layer around the sliding surface. Unfortunately, this addition disrupts Lyapunov stability of the closed-loop system. Classical sliding mode control method has difficulty in handling unstructured model uncertainties. One can overcome this problem by combining a sliding mode controller and fuzzy system together. Fuzzy rules allow fuzzy systems to approximate arbitrary continuous functions. To approximate a time-varying nonlinear system, a fuzzy system requires a large amount of fuzzy rules. This large number of fuzzy rules will cause a high computation load. The addition of an adaptive law to a fuzzy sliding mode controller to online tune the parameters of the fuzzy rules in use will ensure a moderate computational load. Refer to this research; tuning methodology can online adjust both the premise and the consequence parts of the fuzzy rules. Since this algorithm for is specifically applied to a robot manipulator.

EP-based kinematic control and adaptive fuzzy sliding-mode dynamic control for wheeled mobile robots

PurposeThe purpose of this paper is to achieve high-precision sliding mode control without chattering; the control parameters are easy to adjust, and the entire controller is easy to use in engineering practice.Design/methodology/approachUsing double sliding mode surfaces, the gain of the control signal can be adjusted adaptively according to the error signal. A kind of sliding mode controller without chattering is designed and applied to the control of ultrasonic motors.FindingsThe results show that for a position signal with a tracking amplitude of 35 mm, the traditional sliding mode control method has a maximum tracking error of 0.3326 mm under the premise of small chattering; the boundary layer sliding mode control method has a maximum tracking error of 0.3927 mm without chattering, and the maximum tracking error of continuous switching adaptive sliding mode control is 0.1589 mm, and there is no chattering. Under the same control parameters, after adding a load of 0.5 kg, the maximum tracking errors of the traditional sliding mode control method, the boundary layer sliding mode control method and the continuous switching adaptive sliding mode control are 0.4292 mm, 0.5111 mm and 0.1848 mm, respectively.Originality/valueThe proposed method not only switches continuously, but also the amplitude of the switching signal is adaptive, while maintaining the robustness of the conventional sliding mode control method, which has strong engineering application value.

It is difficult to obtain the cam profile accurately in cam grinding because of the complicated contour, the grinding force fluctuate, the tracking performance of the servo system and other interferential factors. The tracking performance of the servo system has a great influence on the cam profile error and leads to the reduction of the cam profile precision. In order to reduce the profile error of cam and improve the machining accuracy, the tracking performance of each servo axis is improved by using sliding mode variable structure control method. The sliding mode variable structure controller adopting the method of proportional switching, quasi-sliding mode and dynamic switching function are designed respectively. The simulation analysis are carried out, and the results of simulation show that the tracking error can be reduced effectively using the sliding mode variable structure control in cam.

Variable structure control with sliding mode, which is commonly known as sliding mode control (SMC), is a nonlinear control strategy that is well known for its robust characteristics (Utkin, 1977). The main feature of SMC is that it can switch the control law very fast to drive the system states from any initial state onto a user-specified sliding surface, and to maintain the states on the surface for all subsequent time (Utkin, 1977), (Phuah et al., 2005 a). The conventional SMC has two disadvantages (Ertugrul & Kaynak, 2000), (Slotine & Sastry, 1983), which are the chattering phenomenon (Slotine & Sastry, 1983), (Young et al., 1999) and the difficulty in calculating the equivalent control law of SMC that requires a thorough knowledge of the parameters and dynamics of the nominal controlled plant (Ertugrul & Kaynak, 2000), (Slotine & Sastry, 1983), (Hussain & Ho, 2004). Many methods of SMC using neural networks (NN) have been proposed (Phuah et al., 2005 a), (Ertugrul & Kaynak, 2000), (Hussain & Ho, 2004), (Phuah et al., 2005 b), (Yasser et al., 2007), (Topalov et al., 2007). In this paper, sliding mode controls using NN are proposed to deal with the problem of eliminating the chattering effect and the difficulty in calculating the equivalent control law of SMC that requires a thorough knowledge of the parameters and dynamics of the nominal controlled plant. The first method of this method applies a method using a simplified form of the distance function proposed in (Phuah et al., 2005 a), (Phuah et al., 2005 b). Furthermore, the simplified distance function of our method uses a sliding surface in the space of the output error and its derivations, as proposed in (Yasser et al., 2006 a), (Yasser et al., 2006 c), instead of the space of the states error to construct a corrective control input. Thus, no observer is required in the proposed method. Moreover, we also propose the application of an NN to construct the equivalent control input of SMC. The weights of the NN are adjusted using a backpropagation algorithm as in (Yasser et al., 2006 b). Hence, a thorough knowledge of the parameters and dynamics of the nominal controlled plant is not required for calculating the equivalent control law. Finally, a stability analysis is carried out, and the effectiveness of this first control method is confirmed through computer simulations. This first method has been previously discussed in (Yasser et al., 2007). The second method of this paper applies an NN to produce the gain of the corrective control of SMC. Furthermore, the output of the switching function the corrective control of SMC is applied for the learning and training of the NN. There is no equivalent control of SMC is used in this second method. As in the first method, this second method applies a method using a sliding surface in the space of the output error and its derivations, as proposed in

In this paper, sliding mode control method is studied for controlling DC motor because of its robustness against model uncertainties and external disturbances, and also its ability in controlling nonlinear and MIMO systems. In this method, using high control gain to overcome uncertainties lead to occur chattering phenomena in control law which can excite unmodeled dynamics and maybe harm the plant. Different approaches, such as intelligent methods, are used to abate these drawbacks. In order to enhancement the sliding mode controller performance, we have used fuzzy logic. For this purpose, we have used a PID outer loop in the control law then the gains of the sliding term and PID term are tuned on-line by a fuzzy system, so the chattering is avoided and response of the system is improved against external load here. Presented simulation results confirm the above claims and demonstrate the performance improvement in this case.

This paper presents a robust fuzzy sliding mode control scheme and the additional compensator. The additional compensator relaying on the sliding-mode theory is used to improve the dynamical characteristics of the drive system. Sliding mode control method is studied for controlling DC motor because of its robustness against model uncertainties and external disturbances. In this method, using high control gain to overcome uncertainties lead to occur chattering phenomena in control law which can excite unmodeled dynamics and maybe harm the plant. In order to enhancement the sliding mode controller performance, we have used fuzzy logic. For this purpose, we have used a Fractional PID outer loop in the control law then the gains of the sliding term and Fractional PID term are tuned on-line by a fuzzy system, so the chattering is avoided and response of the system is improved against external load torque here. Presented implementation results on a DC motor confirm the above claims and demonstrate the performance improvement in this case.

For improving the robustness and control performance of permanent magnet synchronous motor control systems, a sliding mode variable structure control strategy with variable exponential reaching law is designed in this paper. The stability of the control strategy is also analyzed and proven in this paper. This method overcomes the shortcomings of PI control; it decreases the problem of severe buffeting in traditional sliding-mode variable structure controllers. Simulation and real experiments results show that the method is very effective.

Effective power regulation is critical for ensuring the stability and performance of Doubly Fed Induction Generator (DFIG)-based wind turbines. This study conducts a comparative study between two control methodologies: fuzzy logic control (FLC) and sliding mode control (SMC), to regulate power in DFIG-based wind turbines. The paper emphasizes the importance of power regulation in wind turbines and its impact on grid stability, presents mathematical equations governing DFIG-based wind turbine systems, encompassing machine equations, power equations, and control objectives related to power regulation. A comprehensive model of the DFIG-based wind turbine system is developed, accounting for dynamic machine behavior and grid interface considerations. The modeli ng process integrates relevant electrical and mechanical components, along with power regulation control strategies. Subsequently, FLC and SMC control methodologies are developed and implemented to regulate desired power. Detailed discussions on controller design and tuning are provided, aligning with specific power control requirements. The results highlight SMC’s effectiveness in achieving precise power regulation within DFIG-based wind turbines, showcasing its superior response characteristics. The study offers valuable insights into the advantages and trade-offs associated with each control approach, aiding researchers and practitioners in selecting the most suitable control methodology for their operational needs. In summary, this paper contributes to the field of wind turbine control systems through a comparative study of FLC and SMC controllers, focusing on regulating power in DFIG-based wind turbines. The findings demonstrate SMC’s superior performance in response, enhancing our understanding of control methodologies for optimizing wind turbine performance and grid integration in sustainable energy systems.

—Stability, robust and reliability are the main objectives to design a controller for highly nonlinear spherical motor. Most of linear and nonlinear controllers are stable, model-base controllers are reliable but in this group sliding mode controller is a robust controller. Therefore in this research sliding mode controller is used to design stable, robust and reliable controller. For intelligence part, the minimum rule base Proportional Integral Derivative (PID) Fuzzy hybrid guidance Controller for three dimensions spherical motor is presented in this research. Guidance control in a three dimensions spherical motor is performed by the robust sliding mode controllers producing the control signals which are applied to systems torque. Sliding mode controller has an important problem, namely chattering. In this research, chattering-free sliding mode controller is design as a robust guidance controller to their robust performance in a wide range of operating conditions. In this research the PID-like fuzzy controller can be constructed as a parallel structure of a PD-like fuzzy controller and a PI-like controller to have the minimum rule base. Nonlinear type robust sliding mode controller is used to modify PID fuzzy logic theory to design robust and reliable hybrid guidance methodology. This research is used to reduce or eliminate the fuzzy and conventional sliding mode controller problem based on minimum rule base fuzzy logic theory and modified it by sliding mode method to control of spherical motor system.

A novel Fuzzy PID-Variable Structure Adaptive Control is proposed for position tracking of Permanent Magnet Synchronous Motor which will be used in electric extremity exoskeleton robot. This novel control method introduces sliding mode variable structure control on the basis of traditional PID control. The variable structure term is designed according to the sliding mode surface which is designed by system state equation, so it could compensate for the disturbance and uncertainty. Considering the chattering of sliding mode system, the fuzzy inference method is adopted to adjust the parameters of PID adaptively in real time online, which can attenuate chattering and improve control precision and dynamic performance of system correspondingly. In addition, compared with the traditional sliding mode control, this method takes the fuzzy PID control item to replace the equivalent control item of sliding mode variable structure control, which could avoid the control performance reduction resulted from modeling error and parameter error of system. It is proved that this algorithm can converge to the sliding surface and guarantee the stability of system by Lyapunov function. Simulation results show that Fuzzy PID-Variable Structure Adaptive Control enjoys better control precision and dynamic performance compared with traditional control method, and it improves the robustness of system significantly. Finally, the effectiveness and practicability of the algorithm are verified by the method of Rapid Control Prototyping on the semiphysical simulation test bench.

In response to safety concerns pertaining to multi-UAV formation flights, a novel obstacle avoidance method based on an Improved Adaptive Artificial Potential field (IAAPF) is presented. This approach enhances UAV obstacle avoidance capabilities by utilizing segmented attraction potential fields refined with adaptive factors and augmented with virtual forces for inter-UAV collision avoidance. To further enhance the control and stability of multi-UAV formations, a Sliding Mode Control (SMC) method is integrated into the IAAPF-based obstacle avoidance framework. Renowned for its robustness and ability to handle system uncertainties and disturbances, the SMC method is combined with a feedback control system that utilizes inner and outer loops. The outer loop generates the desired path based on the leader’s state and control commands, while the inner loop tracks these trajectories and adjusts the follower UAVs’ motions. This design ensures that obstacle feedback is accounted for before the desired state information is received, enabling effective obstacle avoidance while maintaining formation integrity. Integrating leader-follower formation control techniques with SMC-based multi-UAV obstacle avoidance strategies ensures the effective convergence of the formation velocity and spacing to predetermined values, meeting the cooperative obstacle avoidance requirements of multi-UAV formations. Simulation results validate the efficacy of the proposed method in reaching otherwise unreachable destinations within obstacle-rich environments, while ensuring robust collision avoidance among UAVs.