The design process and complexity of existing safety controls are heavily determined by the geometrical properties of the environment, which affects the proof of convergence, design scalability, performance robustness, and numerical efficiency of the control. Hence, this paper proposes a variable structure control to isolate the environment's geometrical complexity from the control structure. A super-twisting algorithm is used to achieve accurate trajectory tracking and robust safety control. The safety control is designed solely based on distance measurement. First, a nominal safety model for obstacle avoidance is derived, where realistic system constraints are considered. The nominal model is well-suited for safety control design for obstacle avoidance, geofencing, and border patrol with analytically proven stability results. The safety control utilizes distance measurement to maintain a safe distance by compensating the robot's angular velocity. A supervisory logic is constructed to guarantee the overall stability and safety of the system. Operational safety and precision tracking are proven under parametric uncertainty and environmental uncertainty. The proposed design is modular with minimal tuning parameters, which reduces the computational burden and improves the control scalability. The effectiveness of the proposed method is verified against various case studies.
翻译:现有安全控制的设计过程和复杂性在很大程度上是由环境的几何特性决定的,这种特性影响到环境的趋同性、设计可缩放性、性能坚固性和数字效率的证明,因此,本文件建议采用可变的结构控制,将环境的几何复杂性与控制结构分开。使用超旋转算法来准确跟踪轨道和进行稳健的安全控制。安全控制完全根据距离测量来设计。首先,在考虑现实的系统限制的情况下,得出避免障碍的名义安全模型。名义模型非常适合使用安全控制设计来避免障碍、地理屏障和边界巡逻,并具有经过分析证实的稳定结果。安全控制利用距离测量来保持安全距离,补偿机器人的角速度。设计一种监督逻辑是为了保证系统的总体稳定性和安全。操作安全和精确跟踪在参数的偏差性不确定和环境不确定性下得到证明。拟议设计是模块化的,可降低计算负担,改进控制尺度。拟议方法的有效性要对照各种案例研究加以核实。