Disturbance Observer-Based Control for Nonlinear Systems

Disturbance-observer-based control (DOBC) is a robust feedback architecture for nonlinear systems that seeks to estimate and compensate external perturbations and modelling uncertainties in real time. Using an inner-loop observer, total disturbances are reconstructed through the inversion of a nominal plant model combined with a suitable filtering operation. The estimate drives a feedforward channel that attenuates disturbances before they degrade closed-loop performance. For nonlinear dynamics, DOBC frameworks typically integrate adaptive mechanisms, high-gain structures, backstepping or internal model principles to accommodate state-dependent disturbances, unmodelled nonlinearities and time-varying exogenous inputs. This separation of disturbance estimation from the main feedback controller simplifies design and tuning, yielding precise tracking, improved stability margins and reduced sensitivity to parameter variations. Applications span aerospace attitude control, robotic manipulators and precision motor drives, where global significance lies in achieving high performance under uncertainty and external perturbations.

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Research from all publishers

Recent advances have extended DOBC to discrete-time force control systems, combining an inner-loop disturbance observer with an outer-loop reaction force observer to enhance interaction stability and bandwidth in robotic manipulation tasks. High-order disturbance observers have been applied to space unmanned systems to suppress stochastic and high-dynamic uncertainties, coupling neural adaptive laws with stochastic stability analysis to maintain accurate attitude control under extreme perturbations. Innovations in noise-reduction observers have addressed nonlinear actuator control, allowing series DC motors to achieve reverse motion and precise speed regulation despite sensor noise and saturation effects by embedding a disturbance filter within a PI control scheme.

Disturbance Observer-Based Control for Nonlinear Systems publication trend

The graph below shows the total number of articles in disturbance observer-based control for nonlinear systems across all publications each year (not limited to Nature Index journals).

Technical terms

Disturbance Observer: A mechanism that estimates unknown inputs or perturbations acting on a system by using a nominal model and filtering strategy.

Nonlinear System: A dynamic system whose output is not a linear function of its input or state, often exhibiting complex behaviours such as saturation and coupling.

Backstepping: A recursive design method for controllers and observers in nonlinear systems that progressively stabilises subsystems.

Internal Model Principle: A control principle stating that perfect disturbance rejection requires embedding a model of the disturbance dynamics within the controller.

References

1. Disturbance-Observer-Based Control and Related Methods—An Overview. IEEE Transactions on Industrial Electronics (2016).
2. Output‐based disturbance rejection control for non‐linear uncertain systems with unknown frequency disturbances using an observer backstepping approach. IET Control Theory and Applications (2016).
3. Discrete-Time Analysis and Synthesis of Disturbance Observer-Based Robust Force Control Systems. IEEE Access (2021).
4. High-Order Disturbance Observer-Based Neural Adaptive Control for Space Unmanned Systems With Stochastic and High-Dynamic Uncertainties. IEEE Access (2021).
5. PI Speed Control with Reverse Motion of a Series DC Motor Based on the Noise Reduction Disturbance Observer. Actuators (2022).