This paper aims to develop a non-cascade speed control approach for permanent magnet synchronous motor (PMSM) systems based on the Takagi–Sugeno (T–S) fuzzy model. In non-cascade control structures, the lack of firsthand current references imposes a tricky challenge in dealing with current constraints from the circuit and unmatched disturbances caused by load torques. To this end, a virtual reference-based fuzzy non-cascade speed control scheme is proposed for PMSM systems. First, unmatched load torques are estimated by a fuzzy disturbance observer. And then, a novel virtual reference planner is constructed to inject the estimated unmatched disturbance into the control channel as feedback compensation. This improves anti-disturbance performance, while keeping the current re-sponse within the feasible domain and reducing speed overshoot. Furthermore, the non-cascade speed regulation problem is con-verted into a system stabilization problem and addressed by the composite control strategy based on the non-parallel distributed compensation. Finally, closed-loop stability with reduced con-servatism is ensured through the fuzzy Lyapunov functions and improved slack variables. Simulations and experiments show that the proposed scheme achieves excellent speed response without overcurrent even under mismatched load torque variations.

This article studies the consensus problem of multiple random mechanical/Euler-Lagrange systems. First, an event-triggered adaptive distributed observer is proposed. It can estimate both the system matrix and states of the leader. Compared with the existing works, the leader system contains unknown parameters, which makes the design of the observer challenging. Second, an event-triggered adaptive control method is proposed. The proposed method not only can deal with the random disturbance but also can save the energy and execution times of the actuators by event-triggered mechanisms. Finally, a practical application on a real multiple-joint robot is conducted. Each joint of the robot is regarded as a mechanical system. We show that by the presented controller, the angular position of each joint can track a reference signal despite uncertainties and random disturbances.

Uncertain disturbances increase the difficulty of robust tracking control for wheeled mobile robots (WMRs) in industrial scenarios, especially when exhibiting abrupt changes. This letter proposes an adaptive abrupt disturbance-rejection sliding mode controller (SMC). To address the increased variability in the disturbance boundaries caused by abrupt transitions, a new adaptive disturbance observer (ADOB) is designed to improve the tracking robustness and weaken the chattering of SMC by generating auxiliary system variables without depending on any prior boundary information about disturbance and its change rate. Then, a novel barrier function-based switching law is constructed to suppress the residual-disturbance estimation error of the ADOB at the transient state, which achieves the tradeoffs between the necessary sufficient gain and chattering by avoiding gain overestimation. The finite-time Lyapunov stability of the sliding variables and the estimated errors have been proved theoretically. The practical effectiveness is illustrated in experiments with the custom-developed WMRs.

This paper proposes a practical adaptive fuzzy backstepping control (FBC) scheme for the constrained locus tracking problem of a nonlinear cable-driven manipulator. Specifically, fuzzy logic systems aim to approximate unknown nonlinear terms, and the adaptive backstepping control achieves tracking of the desired motion state by recursively designing the virtual references and control laws. Compared with the existing FBC, the practicality is enhanced in the sense that: 1) Simultaneous compliance with prescribed performance and state constraints; 2) No need for the tricky process of finding feasibility conditions for virtual references under strict constraints; 3) Insensitive to system initial conditions for the tracking error convergence of the constrained system. These advanced features lie in the improvement of backstepping protocols through the novel coordinate transformation mechanism, the designed asymmetric barrier Lyapunov functions, and adaptive fixed-time control laws. Application and comparison studies based on a laboratory-developed cable-driven manipulator not only confirm the effectiveness but also show the advantages of the proposed scheme.

The actuator fault problems under saturation bring significant challenges to the stable and accurate tracking of wheeled mobile robots (WMRs) in industrial applications. This letter proposes a novel adaptive fault-tolerant control (FTC) method for WMR systems simultaneously considering uncertain multiple actuator faults, namely lock-in-place (LIP) and partial loss-of-effectiveness (LOE) faults, and saturation. First, a novel barrier function-based nonsingular terminal sliding mode controller is explored to address the actuator LIP failures and unknown dead zones. Then, a two-auxiliary-variable-based adaptive law is designed by estimating the boundary of the actuation effectiveness and saturation coefficient, and uniformly handles the actuator LOE fault and saturation. The adaptive fault-tolerant controller is constructed based on these adaptive laws, achieving the error/sliding variables finite-time convergence and being confined within a predetermined neighborhood of the origin. Finally, practical experiments demonstrate the effectiveness and advantages of the designed FTC scheme.

Industrial mobile robots easily experience actuator loss of some effectiveness and additive bias faults due to the working scenarios, resulting in unexpected performance degradation. This article proposes a novel adaptive fault-tolerant control (FTC) strategy for nonholonomic mobile robot systems subject to simultaneous actuator lock-in-place (LIP) and partial loss-of-effectiveness (LOE) faults. First, a nominal fractional-order sliding mode controller based on the designed exponential super-twisting reaching law is investigated to reduce the reaching phase time and eliminate the chattering. To address the time-varying LIP faults and uncertainties, a novel barrier function (BF)-based gain is explored to assist the super-twisting law. An estimator is designed to estimate the lower bound of the time-varying partial LOE fault coefficients, thus without requiring the boundary information of faults that is commonly requested in traditional FTC schemes. Combined with the nominal controller clubbed with BF and estimator-based LOE fault compensation term, the fault-tolerant controller is finally constructed. The proposed FTC scheme achieves fast convergence and the sliding variables can be confined in a predetermined neighborhood of the sliding manifold under actuator faults. The results show that the proposed controller has superior tracking performance under faulty conditions compared with other state-of-the-art adaptive FTC approaches.