Control Method Research Articles

A novel predefined performance barrier function based adaptive sliding mode control method for RLV under mismatched disturbance

Purpose This paper aims to present a novel adaptive sliding mode control (ASMC) method based on the predefined performance barrier function for reusable launch vehicle under attitude constraints and mismatched disturbances. Design/methodology/approach A novel ASMC based on barrier function is adopted to deal with matched and mismatched disturbances. The upper bounds of the disturbances are not required to be known in advance. Meanwhile, a predefined performance function (PPF) with prescribed convergence time is used to adjust the boundary of the barrier function. The transient performance, including the overshoot, convergence rate and settling time, as well as the steady-state performance of the attitude tracking error are retained in the predetermined region under the barrier function and PPF. The stability of the proposed control method is analyzed via Lyapunov method. Findings In contrast to conventional adaptive back-stepping methods, the proposed method is comparatively simple and effective which does not need to disassemble the control system into multiple first-order systems. The proposed barrier function based on PPF can adjust not only the switching gain in an adaptive way but also the convergence time and steady-state error. And the efficiency of the proposed method is illustrated by conducting numerical simulations. Originality/value A novel barrier function based ASMC method is proposed to fit in the amplitude of the mismatched and matched disturbances. The transient and steady-state performance of attitude tracking error can be selected as prior control parameters.

A multi-point decentralized control for mitigating vibration of flexible space structures using reaction wheel actuators

The vibration with large amplitude and low frequency of the flexible space structures is prone to affect the attitude stability and pointing precision of the spacecraft. To mitigate the vibration of the flexible space structures, a multi-point decentralized control strategy using reaction wheel (RW) actuators is proposed and investigated in this paper. The motion equations of the solar array with multiple RW actuators are derived in modal coordinate representation. To suppress the overall response of the structure, the decentralized control strategy using RW actuators is designed based on the natural frequencies and mode shapes. The stability and the effect of closed-loop dynamic system is theoretically proved. The comparative studies under sun-pointing of the solar array and the rest-to-rest orbital maneuver conditions are presented to show the control performance of the RW actuators. The results indicate that, with 2% increase in total mass from the addition of the actuators, the vibration attenuation time can be decreased by 85.25% and 94.16% for the vibration excited by the sun-pointing and the rest-to-rest orbital maneuver, respectively. The experimental results demonstrate the effectiveness of the proposed decentralized control method. Theoretical analysis, numerical simulation and experimental study are conducted to demonstrate the validity of the proposed vibration mitigation approach and its potential application in the spacecraft design.

Current control for a supercapacitor-based battery equalization system

This paper presents a novel supercapacitor-based energy equalization system and discusses a new equalization current control method. The proposed battery equalization system is composed of a bidirectional boost–buck circuit, a switch matrix, and a supercapacitor, which can realize stable electric current transmission between batteries and supercapacitors. The buck or boost mode of the circuit is triggered automatically based on the threshold of the voltage drop between the battery and the supercapacitor. A modified control logic of the metal-oxide-semiconductor field-effect transistor is proposed to improve the efficiency of the circuit, and a model predictive control (MPC) algorithm is designed to track the target current. Simulation results indicate that for a conventional electric current transmitting circuit, the current fluctuates violently under a fixed pulse width modulation duty. In contrast, the proposed supercapacitor-based energy equalization system tracks the target current well under the control of the MPC controller. In a wide operating range, the transmission efficiency of the new energy equalization system with the modified control logic is 13.0% higher than that of the conventional electric current transmitting circuit with the original control logic.

A new target accessibility control method based on SMC

ABSTRACT In this paper, a sliding mode control method based on improved intelligent decision (IID-SMC) algorithm is proposed to improve the accuracy of the puncture needle to reach the target and reduce the time required in the puncture process. First of all, around the straight line of the puncture needle and the direction of the rotation of the needle, the independent control law is designed to realise the mutual decoupling and reduce the mutual interference. Secondly, the error range of this method in the process of puncture is analysed, and the upper bound of the error in the process of puncture is given. Finally, the method is verified by simulation and experiment platform.

A tube-based model predictive control method for intelligent vehicles path tracking

A tube-based model predictive control method for intelligent vehicles path tracking

41 Is there anything we can do to lessen the severity of PRRSv?

Abstract Veterinarians and the swine industry continue to battle PRRS virus (v), as demonstrated by both the MSHMP (Morrison Swine Health Monitoring Project) and the SDRS (Swine Disease Reporting System). Both systems depict a continued increase in PRRSv prevalence and percentage of positive cases. The PRRSv variants that are circulating today seem to be more severe, especially in the last 2 to 3 yr, with more significant health and production losses in the nursery and finishing phases for prolonged periods of time. The best thing that can be done is to avoid having the virus with a good bioexclusion plan and if sites become infected, a strong biocontainment plan to avoid contaminating more sites should be considered. Realizing that bioexclusion is not always possible and sites will become infected, there are methods to help to reduce the impact of the virus. With the concerns of recombination pushing the virus evolution along faster, more producers are working toward eliminating field viruses from their systems. The use of filtration both on sow farms and nurseries has become more common as well as an additional method of bioexclusion. In the face of an outbreak, obtaining an accurate diagnosis is still one of the most important things that we do. In farrow to wean farms, serum samples are generally used when clinical signs (e.g., abortions, off feed) are observed to target testing to specific animals that are more likely to allow for early detection. In nursery and finishing sites, the use of oral fluid has worked very well as a screening tool when there are clinical signs or problems within a group or flow. Fortunately, there are differential tests that can be used to identify field infection and vaccines strains (since most wean to finish pigs are vaccinated in pig dense areas). With severe strains, depopulation and repopulation strategies have become more popular as a control method, but the majority of herd would use a herd closure. However, the amount of time required for these closures is extending, which lengthens the impacts on sow farms. Among wean to finish systems, the use of depopulating and cleaning up the site is used most, with only routine down times. Anti-inflammatories can also be administered in the acute phase of the outbreak in addition to the use of antibiotics to control secondary bacterial infections, as well as providing a good environment to allow the pigs to better deal with the disease. It’s best to keep the virus out of the herd with a good bioexclusion program. However, when we do have outbreaks, anti-inflammatory and antibiotics to help the pigs through it are important to utilize as we work to eliminate the field virus from the herd.

A homotopy-based reinforcement learning scheme to optimal control for Markov switched interconnected systems

ABSTRACT In this paper, a homotopy-based reinforcement learning optimal control method is developed for Markov switched interconnected systems with unknown system dynamics. By utilising the subsystem decomposition method and parallel learning control method, the solution of the game coupled algebraic Riccati equations with jumping parameters is approximated. To dispense with the requirement of initial stability, a homotopy-based policy iteration is introduced, which can place unstable poles into a stable plane. In this regard, a model-free reinforcement learning method is presented to design the optimal controller for Markov switched interconnected systems. Finally, the effectiveness of the proposed method is verified by a numerical example and a practical example.

Quantum-inspired deep reinforcement learning for adaptive frequency control of low carbon park island microgrid considering renewable energy sources

The low carbon park islanded microgrid faces operational challenges due to the high variability and uncertainty of distributed renewable energy sources. These sources cause severe random disturbances that impair the frequency control performance and increase the regulation cost of the islanded microgrid, jeopardizing its safety and stability. This paper presents a data-driven intelligent load frequency control (DDI-LFC) method to address this problem. The method replaces the conventional LFC controller with an intelligent agent based on a deep reinforcement learning algorithm. To adapt to the complex islanded microgrid environment and achieve adaptive multi-objective optimal frequency control, this paper proposes the quantum-inspired maximum entropy actor-critic (QIS-MEAC) algorithm, which incorporates the quantum-inspired principle and the maximum entropy exploration strategy into the actor-critic algorithm. The algorithm transforms the experience into a quantum state and leverages the quantum features to improve the deep reinforcement learning’s experience replay mechanism, enhancing the data efficiency and robustness of the algorithm and thus the quality of DDI-LFC. The validation on the Yongxing Island isolated microgrid model of China Southern Grid (CSG) demonstrates that the proposed method utilizes the frequency regulation potential of distributed generation, and reduces the frequency deviation and generation cost.

Safe Autonomous Docking of Spacecraft: A RTT-conbined Output-constrained Recursive Control Method

Safe Autonomous Docking of Spacecraft: A RTT-conbined Output-constrained Recursive Control Method

Artificial neural network‐based adaptive control for nonlinear dynamical systems

SummaryThis research article presents an artificial neural network (ANN)‐based indirect adaptive control method for nonlinear dynamical systems. In this article, a modified Elman recurrent neural network (MERNN) is proposed as an identifier and controller for controlling nonlinear systems. The architecture of the proposed controller is a modified form of the existing Elman recurrent neural network. The parameter training of ANN‐based controllers is obtained by using the most popular optimization algorithm which is known as the back‐propagation algorithm. A comparative study includes Elman, Diagonal, Jordan, feed‐forward neural network (FFNN), and radial basis function network (RBFN)‐based controllers to compare with the proposed MERNN controller. To determine the controller's robustness, parameter variations, and disturbance signals have been considered. The performance analysis of the proposed controller is illustrated by two simulation examples. The simulation results reveal that MERNN can not only identify the unknown dynamics of the plant but also adaptively control it compared to the others.

Aerodynamic performance and wake development of NACA 0018 airfoil with serrated gurney flaps

Improving the aerodynamic performance of the airfoil is important for optimising the rotor efficiency of the vertical axis wind turbines. As a simple passive control method, the Gurney flap is widely used to improve the aerodynamic performance of airfoils. In this paper, we study the impact of applying a novel serrated gurney flap with different heights on the NACA 0018 airfoil. An improved delayed detached eddy simulation method is adopted to investigate the lift-enhancing mechanism of the serrated gurney flap and the evolution of the downstream vortex system. The results show that the serrated gurney flap can effectively increase the airfoil lift coefficient and the lift-to-drag ratio. The improvement of the serrated gurney flap on the aerodynamic performance of the airfoil is more pronounced at moderate angles of attack. Further analysis of the downstream wake shows that a pair of vortices wraps over both sides of the airfoil and rotates perpendicular to the wake flow, which is produced by the columnar vortex upstream of the flap. These vortices mixed with the wake and accelerated the dissipation of the separated vortex on the suction surface of the airfoil.

Optical-pulse-based reconfigurable phase control for independent beamforming and band fusion in a dual-band phased array receiver

This Letter proposes an optical-pulse-based reconfigurable phase control method, enabling a dual-band phased array receiver to operate in two modes: dual-band-independent operation and dual-band fusion. The method utilizes optical pulses and optical delay to compensate for phase differences across frequency bands. An electrical phase shifter is employed to compensate for phase residual in both bands. All phase operations to both bands are processed concurrently in one link, thereby maintaining inter-band phase coherence. Experimental results verify the ability of dual-band-independent beamforming and inter-band phase coherence maintaining. A four-channel dual-band (X- and Ku-band) phased array antenna (PAA) receiver is constructed to measure PAA patterns and demonstrate band fusion. The pulse compression results in all directions reveal a doubled improvement in range resolution, which shows the potential for enhancement of radar performance.

Nonlinear optimal control for robotic exoskeletons with electropneumatic actuators

Purpose To provide high torques needed to move a robot’s links, electric actuators are followed by a transmission system with a high transmission rate. For instance, gear ratios of 100:1 are often used in the joints of a robotic manipulator. This results into an actuator with large mechanical impedance (also known as nonback-drivable actuator). This in turn generates high contact forces when collision of the robotic mechanism occur and can cause humans’ injury. Another disadvantage of electric actuators is that they can exhibit overheating when constant torques have to be provided. Comparing to electric actuators, pneumatic actuators have promising properties for robotic applications, due to their low weight, simple mechanical design, low cost and good power-to-weight ratio. Electropneumatically actuated robots usually have better friction properties. Moreover, because of low mechanical impedance, pneumatic robots can provide moderate interaction forces which is important for robotic surgery and rehabilitation tasks. Pneumatic actuators are also well suited for exoskeleton robots. Actuation in exoskeletons should have a fast and accurate response. While electric motors come against high mechanical impedance and the risk of causing injuries, pneumatic actuators exhibit forces and torques which stay within moderate variation ranges. Besides, unlike direct current electric motors, pneumatic actuators have an improved weight-to-power ratio and avoid overheating problems. Design/methodology/approach The aim of this paper is to analyze a nonlinear optimal control method for electropneumatically actuated robots. A two-link robotic exoskeleton with electropneumatic actuators is considered as a case study. The associated nonlinear and multivariable state-space model is formulated and its differential flatness properties are proven. The dynamic model of the electropneumatic robot is linearized at each sampling instance with the use of first-order Taylor series expansion and through the computation of the associated Jacobian matrices. Within each sampling period, the time-varying linearization point is defined by the present value of the robot’s state vector and by the last sampled value of the control inputs vector. An H-infinity controller is designed for the linearized model of the robot aiming at solving the related optimal control problem under model uncertainties and external perturbations. An algebraic Riccati equation is solved at each time-step of the control method to obtain the stabilizing feedback gains of the H-infinity controller. Through Lyapunov stability analysis, it is proven that the robot’s control scheme satisfies the H-infinity tracking performance conditions which indicate the robustness properties of the control method. Moreover, global asymptotic stability is proven for the control loop. The method achieves fast convergence of the robot’s state variables to the associated reference trajectories, and despite strong nonlinearities in the robot’s dynamics, it keeps moderate the variations of the control inputs. Findings In this paper, a novel solution has been proposed for the nonlinear optimal control problem of robotic exoskeletons with electropneumatic actuators. As a case study, the dynamic model of a two-link lower-limb robotic exoskeleton with electropneumatic actuators has been considered. The dynamic model of this robotic system undergoes first approximate linearization at each iteration of the control algorithm around a temporary operating point. Within each sampling period, this linearization point is defined by the present value of the robot’s state vector and by the last sampled value of the control inputs vector. The linearization process relies on first-order Taylor series expansion and on the computation of the associated Jacobian matrices. The modeling error which is due to the truncation of higher-order terms from the Taylor series is considered to be a perturbation which is asymptotically compensated by the robustness of the control algorithm. To stabilize the dynamics of the electropneumatically actuated robot and to achieve precise tracking of reference setpoints, an H-infinity (optimal) feedback controller is designed. Actually, the proposed H-infinity controller for the model of the two-link electropneumatically actuated exoskeleton achieves the solution of the associated optimal control problem under model uncertainty and external disturbances. This controller implements a min-max differential game taking place between: (i) the control inputs which try to minimize a cost function which comprises a quadratic term of the state vector’s tracking error and (ii) the model uncertainty and perturbation inputs which try to maximize this cost function. To select the stabilizing feedback gains of this H-infinity controller, an algebraic Riccati equation is being repetitively solved at each time-step of the control method. The global stability properties of the H-infinity control scheme are proven through Lyapunov analysis. Research limitations/implications Pneumatic actuators are characterized by high nonlinearities which are due to air compressibility, thermodynamics and valves behavior and thus pneumatic robots require elaborated nonlinear control schemes to ensure their fast and precise positioning. Among the control methods which have been applied to pneumatic robots, one can distinguish differential geometric approaches (Lie algebra-based control, differential flatness theory-based control, nonlinear model predictive control [NMPC], sliding-mode control, backstepping control and multiple models-based fuzzy control). Treating nonlinearities and fault tolerance issues in the control problem of robotic manipulators with electropneumatic actuators has been a nontrivial task. Practical implications The novelty of the proposed control method is outlined as follows: preceding results on the use of H-infinity control to nonlinear dynamical systems were limited to the case of affine-in-the-input systems with drift-only dynamics. These results considered that the control inputs gain matrix is not dependent on the values of the system’s state vector. Moreover, in these approaches the linearization was performed around points of the desirable trajectory, whereas in the present paper’s control method the linearization points are related with the value of the state vector at each sampling instance as well as with the last sampled value of the control inputs vector. The Riccati equation which has been proposed for computing the feedback gains of the controller is novel, so is the presented global stability proof through Lyapunov analysis. This paper’s scientific contribution is summarized as follows: (i) the presented nonlinear optimal control method has improved or equally satisfactory performance when compared against other nonlinear control schemes that one can consider for the dynamic model of robots with electropneumatic actuators (such as Lie algebra-based control, differential flatness theory-based control, nonlinear model-based predictive control, sliding-mode control and backstepping control), (ii) it achieves fast and accurate tracking of all reference setpoints, (iii) despite strong nonlinearities in the dynamic model of the robot, it keeps moderate the variations of the control inputs and (iv) unlike the aforementioned alternative control approaches, this paper’s method is the only one that achieves solution of the optimal control problem for electropneumatic robots. Social implications The use of electropneumatic actuation in robots exhibits certain advantages. These can be the improved weight-to-power ratio, the lower mechanical impedance and the avoidance of overheating. At the same time, precise positioning and accurate execution of tasks by electropneumatic robots requires the application of elaborated nonlinear control methods. In this paper, a new nonlinear optimal control method has been developed for electropneumatically actuated robots and has been specifically applied to the dynamic model of a two-link robotic exoskeleton. The benefit from using this paper’s results in industrial and biomedical applications is apparent. Originality/value A comparison of the proposed nonlinear optimal (H-infinity) control method against other linear and nonlinear control schemes for electropneumatically actuated robots shows the following: (1) Unlike global linearization-based control approaches, such as Lie algebra-based control and differential flatness theory-based control, the optimal control approach does not rely on complicated transformations (diffeomorphisms) of the system’s state variables. Besides, the computed control inputs are applied directly on the initial nonlinear model of the electropneumatic robot and not on its linearized equivalent. The inverse transformations which are met in global linearization-based control are avoided and consequently one does not come against the related singularity problems. (2) Unlike model predictive control (MPC) and NMPC, the proposed control method is of proven global stability. It is known that MPC is a linear control approach that if applied to the nonlinear dynamics of the electropneumatic robot, the stability of the control loop will be lost. Besides, in NMPC the convergence of its iterative search for an optimum depends on initialization and parameter values selection and consequently the global stability of this control method cannot be always assured. (3) Unlike sliding-mode control and backstepping control, the proposed optimal control method does not require the state-space description of the system to be found in a specific form. About sliding-mode control, it is known that when the controlled system is not found in the input-output linearized form the definition of the sliding surface can be an intuitive procedure. About backstepping control, it is known that it cannot be directly applied to a dynamical system if the related state-space model is not found in the triangular (backstepping integral) form. (4) Unlike PID control, the proposed nonlinear optimal control method is of proven global stability, the selection of the controller’s parameters does not rely on a heuristic tuning procedure, and the stability of the control loop is assured in the case of changes of operating points. (5) Unlike multiple local models-based control, the nonlinear optimal control method uses only one linearization point and needs the solution of only one Riccati equation so as to compute the stabilizing feedback gains of the controller. Consequently, in terms of computation load the proposed control method for the electropneumatic actuator’s dynamics is much more efficient.

Long chain unsaturated fatty acids alter growth and reduce biofilm formation of Cronobacter sakazakii

AbstractCronobacter sakazakii is a foodborne pathogen predominately transmitted through contaminated dried foods and affects populations including neonates, infants, and the elderly. Following several recent outbreaks, it is now a notifiable infection in those under 12 months of age. Current control methods include strict manufacturing guidelines, with monitoring of this genus a legal requirement in powdered infant formula production. Fatty acids have long been known as antimicrobials, with long‐chain fatty acids increasingly identified as agents that target virulence factors. This study gives insight into the changes promoted by three long‐chain unsaturated fatty acids (oleic, linoleic, and α‐linolenic) on C. sakazakii growth, morphology, and biofilm formation. Each fatty acid was individually introduced to C. sakazakii 29544 both as a sole carbon source and as an addition to complex media. Following comparison to the untreated control, bacterial cells treated with these fatty acids showed a significant and media‐dependent impact on growth and biofilm inhibition. With further characterization, long‐chain fatty acids, including α‐linolenic acid, could be utilized as a control method with minimal safety constraints regarding their use in the food production environment.

Research on High-Stability Composite Control Methods for Telescope Pointing Systems under Multiple Disturbances

During the operation of space gravitational wave detectors, the constellation configuration formed by three satellites gradually deviates from the ideal 60° angle due to the periodic variations in orbits. To ensure the stability of inter-satellite laser links, active compensation of the breathing angle variation within the constellation plane is achieved by rotating the optical subassembly through the telescope pointing mechanism. This paper proposes a high-performance robust composite control method designed to enhance the robust stability, disturbance rejection, and tracking performance of the telescope pointing system. Specifically, based on the dynamic model of the telescope pointing mechanism and the disturbance noise model, an H∞ controller has been designed to ensure system stability and disturbance rejection capabilities. Meanwhile, employing the method of an H∞ norm optimized disturbance observer (HODOB) enhances the nonlinear friction rejection ability of the telescope pointing system. The simulation results indicate that, compared to the traditional disturbance observer (DOB) design, utilizing the HODOB method can enhance the tracking accuracy and pointing stability of the telescope pointing system by an order of magnitude. Furthermore, the proposed composite control method improves the overall system performance, ensuring that the stability of the telescope pointing system meets the 10 nrad/Hz1/2 @0.1 mHz~1 Hz requirement specified for the TianQin mission.

A soft robot tactile fingertip for grasping surface posture detection

Abstract The application field of robots is gradually extending from traditional industrial manufacturing to commercial services, medical care and other fields. Stable grasping is a necessary prerequisite for various complex robot application scenarios. The existing research on robot tactile sensor mainly focus on sensing tactile information, such as pressure or sliding. However, grasping surface posture as a tactile information that has a significant impact on the stability of grasping is often ignored. This study proposed a novel soft robot tactile fingertip that can not only detect the grasping force but also simultaneously detect the grasping surface posture. It is capable of recognizing 19 grasping surface postures in real-time using Mamdani fuzzy control method. The soft robot tactile fingertip has a simple structure and easy to fabricate at low cost. The application example of the two-finger mechanical hand using the soft tactile fingertip samples for stable grasping is demonstrated. This study shows that the soft robot tactile fingertip has great application prospects in the filed of robot intelligent grasping.

Chattering Free Sliding-Mode Controller Design for Underactuated Tower Cranes With Uncertain Disturbance

Tower cranes are widely used in various industrial sites and require a high level of anti-disturbance performance from the crane controller due to the variability of the application environment. Although sliding mode control is a typical anti-disturbance control method, most sliding mode controllers suffer from output chattering and do not reflect well under severe external disturbances. To address these issues from a practical application perspective, a finite time sliding mode control method using the super-twisting algorithm (STA) is proposed for underactuated tower cranes operating in the presence of external disturbances. The proposed method includes a finite-time chattering-free sliding mode controller that eases the output torque chattering problem and a finite-time sliding mode observer based on STA to observe the uncertain disturbances. The observed values are then applied to the controller through feedforward compensation. Experimental results show that the proposed control method effectively weakens output torque chattering, compensates for disturbance quickly, and accurately completes control tasks.

Self-Calibration Method of Displacement Sensor in AMB-Rotor System Based on Magnetic Bearing Current Control

Displacement sensors are the key components of the active magnetic bearing rotor (AMB-rotor) system to realize the closed-loop control of the rotor displacement. The aging and failure of the displacement sensor components will lead to the changes of sensor sensitivity and zero point, which can directly affect the suspension performance of the rotor and even cause the instability of the AMB-rotor system. Therefore, it is significant to calibrate the sensor regularly. This paper proposes a self calibration method based on the detection and control of the magnetic bearing current without additional calibration equipment and hardware circuits. In addition, a new control structure of the AMB-rotor system is proposed to achieve efficient calibration, which can control the rotor displacement based on current following control method. Finally, experimental results verify the effectiveness of the proposed method on the displacement sensor calibration.

Zero-Resistance-Branch Electrical Drainage System to Solve the Adverse Influence of Stray Current on Buried Pipelines

The buried pipeline's ground potential may be seriously shifted by the stray current leaking from the rail transit, leading to the problem of severe electrochemical corrosion on buried pipeline. For this, a zero-resistance- branch electrical drainage system is proposed to solve the adverse influence of stray current on buried pipeline just like the APF technology in power systems, mainly consisting of a negative resistance compensating converter (NRCC) and a grounding electrode, which can directly drain the stray current to the soil without connecting the rail system. Moreover, the equivalent interference circuit model of stray current is established, and the corrosion rule is analyzed in detail. Furthermore, based on the NRCC, the zero-resistance active drainage control method is proposed to realize the absorption of stray current. As the optimization objective of the control method, the disturbance component of pipe-to-soil potential is regulated to be approximately 0, and the zero-resistance branch at the disturbance frequency can be realized without directly detecting the value of the stray current. Then, the stray current can be transferred to the new drainage branch to mitigate its electrochemical corrosion on buried pipelines. Finally, the experimental results verify the effectiveness of the proposed electrical drainage system.

Heterogeneous Unmanned Swarm Formation Containment Control Based on Reinforcement Learning

In response to the problem of time-varying spherical formation control for a heterogeneous unmanned aerial vehicle (UAV) swarm system with dynamic uncertainty in the system model, this paper proposes an optimal distributed formation containment control method based on reinforcement learning. By combining the time-varying formation containment vector design with the distributed predefined time observer and constructing the augmented system of a multi-quadrotor UAV system and an observer, the problem of time-varying formation containment control in heterogeneous swarm systems is transformed into a stabilization problem. By introducing a value function with a discount factor, the stabilization problem of a heterogeneous UAV swarm system is transformed into an optimal control problem. Using the “actor-critic” neural network, combined with an off-policy reinforcement learning algorithm and distributed control methods, the solution to the formation containment controller is achieved in a data-driven manner. The stability of distributed observer and formation containment controller as well as the convergence of reinforcement learning algorithms are demonstrated using Lyapunov and related theory. The numerical simulation results demonstrate that the observation error of the designed distributed observer converges within a predefined time of 0.1 s, while the overall formation tracking error of the heterogeneous swarm converges within 2.74 s, thereby further validating the effectiveness and superiority of the designed control scheme.