Sliding-mode position control of robot joint based on self-adaptive parameters adjusting

In this chapter an adaptive sliding mode controller for the Furuta pendulum is proposed. The Furuta pendulum is a class of underactuated mechanical systems commonly used in many control systems laboratories due to its complex stabilization which allows the analysis and design of different nonlinear and multivariable controllers that are useful in some fields such as aerospace and robotics. Sliding mode control has been extensively used in the control of mechanical systems as an alternative to other nonlinear control strategies such as backstepping, passivity based control etc. The design and implementation of an adaptive sliding mode controller for this kind of system is explained in this chapter, along with other sliding mode controller variations such as second order sliding mode (SOSMC) and PD plus sliding mode control (PD \(+\) SMC) in order to compare their performance under different system conditions. These control techniques are developed using the Lyapunov stability theorem and the variable structure design procedure to obtain asymptotically stable system trajectories. In this chapter the adaptive sliding mode consist of a sliding mode control law with an adaptive gain that makes the controller more flexible and reliable than other sliding mode control (SMC) algorithms and nonlinear control strategies. The adaptive sliding mode control (ASMC) of the Furuta pendulum, and the other SMC strategies shown in this chapter, are derived according to the Furuta’s pendulum dynamic equations making the sliding variables, position errors and velocity errors reach the zero value in a specified reaching time. The main reason of deriving two well known sliding mode control strategy apart from the proposed control strategy of this chapter (adaptive sliding mode control) is for comparison purposes and to evince the advantages and disadvantages of adaptive sliding mode control over other sliding mode control strategies for the stabilization of the Furuta pendulum. A chattering analysis of the three SMC variations is done, to examine the response of the system, and to test the performance of the ASMC in comparison with the other control strategies explained in this chapter.

In order to improve the robustness of the sliding mode control algorithm of the four-phase interleaved parallel Buck converter, an improved adaptive non-singular terminal sliding mode PI (ANTSMC-PI) dual closed-loop control strategy based on linearly expanding state observer (LESO) is proposed in this paper. First, two LESO observers are designed to estimate the matched and mismatched disturbance in the system dynamic model, respectively. Second, the estimates of the observers are Integrationed into the outer-loop controller, and an improved sliding-mode controller is proposed to achieve error-free tracking of the output voltage to the reference voltage; while the PI controller is used for the current inner loop to ensure the equal current flow in each phase of the system. Finally, the stability of the designed controller is demonstrated by using the lyapunov stability principle. The simulation in Matlab/Simulink platform shows that the proposed scheme can effectively reduce the output ripple and improve the system dynamic performance compared with the traditional non-singular terminal sliding-mode PI control strategy.

Three-phase voltage PWM rectifier is a multivariable, strong coupling, nonlinear multi-input and multi-output system. In the design of rectifier control systems, with PI control it is difficult to achieve the ideal control effect, the dynamic performance is poor, and the parameter computation is complex. Moreover, the traditional sliding mode control voltage outer loop suffers from the problem of chattering, which is difficult to solve. Responding to the above issues, a new type of variable speed reaching law is proposed, which is applied to the voltage outer loop sliding mode control, while the feedback linearization principle is introduced to the current inner loop, and a new type of double closed-loop sliding mode control system is obtained by applying the two theories to the design of the sliding mode controller. A simulation model is established in MATLAB/Simulink to compare the PI control, the SMC control and the V-SMC control strategy proposed in this paper (voltage outer loop V-SMC current inner loop FLC-SMC control), and the simulation results show that the rectifier under the new dual-closed-loop sliding mode control strategy has the advantages of good dynamic performance, strong robustness and strong anti-interference ability. At the same time, compared with the traditional sliding mode control strategy, the vibration suppression effect under the proposed control strategy is obvious. Finally, a 10 kW rectifier control system is built on a semi-physical hardware-in-the-loop experimental platform to further verify the correctness and superiority of the proposed control strategy.

This paper suggests a new hybrid control strategy, called Optimal Type II Fuzzy Sliding Mode (OT2FSM) control scheme, to realize the control of general uncertain chaotic systems. The proposed controller not only guaranties the stability and robustness against the lumped uncertainties caused by unmodeled dynamics and external disturbances, but also can significantly reduce the control chattering inherent in conventional sliding mode control. In the proposed controller, a novel heuristic algorithm namely particle swarm optimization with random inertia weight (RNW–PSO) is employed. To achieve an optimal performance, the parameters of the proposed controller as well as the input and output membership functions are optimized simultaneously by RNW–PSO. The globally asymptotic stability of the closed-loop system is mathematically proved. To evaluate the performance of the proposed controller, the results are compared with those obtained by Optimal H-infinity Adaptive PID (OHAPID) controller and an optimal Type-2 fuzzy proportional integral derivative (OT2FPID), which are the latest researches in the problem in hand. Simulation results show the effectiveness of the OT2FSM controller.

To improve the performance of the magnetorheological (MR) semi-active suspension system, a fractional-order sliding mode control (FOSMC) strategy is proposed to address the nonlinear problems caused by the external disturbances and changes in parameters of system. Firstly, The MR damper designed by the research team is applied to the vehicle’s MR semi-active suspension, and a one-fourth semi-active suspension dynamic model is established. Mechanical performance tests of the MR damper are conducted through tensile experiments, confirming its satisfactory mechanical characteristics and suitability for meeting the output damping force requirements of the vehicle’s semi-active suspension. To accurately convert the computed control force into the MR damper’s control current, an adaptive neuro-fuzzy inference system (ANFIS) inverse model of the MR damper is constructed. Comparative data analysis demonstrates the inverse model’s high accuracy and its ability to effectively meet the controller’s requirements. The proposed FOSMC strategy effectively reduces the chattering phenomenon associated with sliding mode control, leading to improved vibration-damping performance of the suspension. Subsequently, a simulation model and experimental platform are utilized to evaluate the performance of the proposed controller. Experimental results indicate that the FOSMC-controlled suspension outperforms the passive suspension, achieving significant reductions in body acceleration, suspension dynamic travel, and tire dynamic displacement by 27.4%, 7.3%, and 17.39%, respectively. Similarly, the semi-active suspension controlled by sliding mode control (SMC) also shows improvements compared to the passive suspension, with reductions in body acceleration, suspension dynamic travel, and tire dynamic displacement by 20.9%, 4.3%, and 5.2%, respectively. In summary, the FOSMC-controlled MR semi-active suspension exhibits superior damping performance compared to both the passive suspension and the SMC-controlled semi-active suspension, demonstrating the effectiveness of the proposed FOSMC controller.

During high-speed operation, a high-temperature superconducting pinning levitation (HTSPL) train must rely on independent eddy current brakes on its maglev bogies for distributed braking in the event of linear motor failure. To investigate the braking process and enhance its performance, the train is modeled as an interconnected system, with the modularly designed maglev bogies treated as subsystems. A comprehensive longitudinal dynamic model of the train is developed. Based on the desired braking acceleration corresponding to the current speed, combined with displacement and velocity feedback, control currents are applied to the brakes to achieve eddy current braking. However, this simple control strategy does not account for relative errors between maglev bogies or the transmission of longitudinal vibrations between carriages, posing safety risks. To address these issues, a ‘Look-Forward’ sliding mode control strategy is implemented under the same feedback conditions. A braking current control law is designed, and the range of control parameters is determined through Lyapunov stability analysis. Numerical simulations compare the braking performance of the two strategies. Results show that both strategies achieve a complete stop within acceptable time (135 s) and distance (9 km), although the time and distance under sliding mode control are slightly longer. With simple control, longitudinal acceleration and force exhibit superimposed vibrations at approximately 5 Hz and 30 Hz, adversely impacting train reliability and passenger comfort. In contrast, the ‘Look-Forward’ sliding mode control significantly reduces vibrations, achieving the desired synchronized braking effect among maglev bogies. However, there is room for parameter optimization, and other advanced control methods could be explored to address more complex operating conditions.

A self-organizing fuzzy controller to augment a sliding-mode control (SOFSMC) scheme for a class of nonlinear systems is proposed. The motivation behind this scheme is to combine the best features of self-organizing fuzzy control and sliding-mode control to achieve rapid and accurate tracking control of a class of nonlinear systems. The chatter encountered by most sliding-mode control schemes is greatly alleviated without sacrificing invariant properties. A stability analysis is presented; the design guidelines and the class of applicable systems are clearly identified. To verify the scheme, the authors performed experiments on its implementation in a magnetic levitation system. The results show that both alleviation of chatter and robust performance are achieved; the advantages of the scheme are indicated in comparison with the conventional sliding-mode design. >

In this paper, we present a simulation study of a wind system with a doubly fed induction machine driven by a variable pitch wind turbine. The objective of the work is to design a control algorithm based on the sliding mode control strategy allowing the control of both active and reactive power independently. The main goal achieved by the control strategy is to control the amount of active and reactive power produced by the doubly fed induction generator and injected in the main grid according to the power references derived from turbine's mechanical power and the grid operator. The simulation results have shown good performances concerning the tracking of the references both in transient and steady state. A comparative study between the proposed control strategy and the well known vector control strategy has been carried out and has shown the superiority of sliding mode control to track the given references.

To deal with the control problems of the three-phase PWM rectifier under the unbalanced grid voltage conditions, this paper proposes a modified direct power control strategy using adaptive sliding mode control algorithm with model of the PWM rectifier in stationary αβ frame. The active and reactive power dynamics of the PWM rectifier are linearized and decoupled based on the inverse system algorithm. Then a sliding mode control scheme is designed to improve the robustness and reduce the influences caused by the system parameters variations and load disturbances. In order to satisfy the state requirements, an adaptive law is introduced to the control strategy to reduce the sliding mode control gain on the premise that the system is stable. Simulation results confirm the feasibility of the proposed control strategy.

This article presents an original motion control strategy for robot manipulators based on the coupling of the inverse dynamics method with the so-called second-order sliding mode control approach. Using this method, in principle, all the coupling non-linearities in the dynamical model of the manipulator are compensated, transforming the multi-input non-linear system into a linear and decoupled one. Actually, since the inverse dynamics relies on an identified model, some residual uncertain terms remain and perturb the linear and decoupled system. This motivates the use of a robust control design approach to complete the control scheme. In this article the sliding mode control methodology is adopted. Sliding mode control has many appreciable features, such as design simplicity and robustness versus a wide class of uncertainties and disturbances. Yet conventional sliding mode control seems inappropriate to be applied in robotics since it can generate the so-called chattering effect, which can be destructive for the controlled robot. In this article, this problem is suitably circumvented by designing a second-order sliding mode controller capable of generating a continuous control law making the proposed sliding mode controller actually applicable to industrial robots. To build the inverse dynamics part of the proposed controller, a suitable dynamical model of the system has been formulated, and its parameters have been accurately identified relying on a practical MIMO identification procedure recently devised. The proposed inverse dynamics-based second-order sliding mode controller has been experimentally tested on a COMAU SMART3-S2 industrial manipulator, demonstrating the tracking properties and the good performances of the controlled system.

In this paper, because a adaptive fuzzy control is incorporated into the sliding mode control (SMC) to adaptively regulate the adaptive law of SMC, an adaptive fuzzy sliding mode controller (AFSMC) for brushless doubly fed machine (BDFM) adjustable speed system is presented. The proposed controller for BDFM eliminates the average chattering encountered by most SMC schemes, and employs the robustness and excellent static and dynamic performances of SMC. Simulation results show that the proposed control strategy is of the feasibility, correctness and effectiveness.

Chatter suppression is essential for achieving high precision and surface quality in machining processes. In this paper, a control strategy is presented for chatter suppression in cutting process in the presence of tool wear and parameter uncertainties. A single-degree-of-freedom model of a turning process in the orthogonal cutting configuration is used to set up the nonlinear delay differential equation of motion that includes the effects of tool flank wear. Uncertainties in cutting velocity, tool wear size and parameters of the dynamic model are included in the model of the cutting process. The force provided by a piezo-actuator is taken as the control input of the system. A sliding mode control scheme is used and an effective control law is derived that suppresses chatter. Results of stability analysis and sliding mode control for two distinct cases of sharp and worn tools are presented and compared, which show the effectiveness of the approach.

The exploitation of wind power will improve the energy structure and ease the power shortage, which is an effective approach to solving the world energy crisis. But the wind power generation system was a typical nonlinear system, which was hard to be controlled exactly by traditional controllers and the sliding mode control was proposed, the mathematical models of wind energy conversion system was created, which was combined with mechanical automation and electrical, the sliding mode control strategy was presented, the sliding surface was designed with equivalent controller and switching controller. The model and control strategy was established with MATLAB and the simulation result shows this control system with speed tracking performance, which can effectively implement maximum energy capture.

In this paper Sliding Mode Control (SMC) strategies are proposed for controller design of Unified Power Flow Controller (UPFC). The State-Space model of UPFC connected to a Single Machine Infinite Bus (SMIB) system is considered. Sliding Surface is designed by using regular form approach. Gao's reaching laws are applied to the state-space model of the system considered and the results are compared with each other. It is seen that the Gao's power rate reaching law is giving appropriate results. Simulation results thus obtained and comparison made by application of different strategies; using MATLAB and Simulink are presented.

This paper proposes a strategy of a new optimal sliding-mode control for flight control system with state constraints so that the system guarantees the optimal performance index. Besides, the strategy ensures strong robustness to the internal parametric uncertainty and the external disturbances. In order to have fast tran- sient response speed as well as good tracking accuracy, the integral of the time multiplied by the absolute dis- placement tracking error is introduced as the performance index. By analyzing the state constraints which are specifically the velocity tracking error constraint and the acceleration tracking error constraint, and the perfor- mance index, the parameters of sliding-mode surface and control law are obtained. Finally, the authors conduct the semi physical simulation on Qball-X4 quad-rotor helicopter, showing the effectiveness of the proposed strat- egy.